Aim Despite predictions of high extinction risk from climate change, range expansions have been documented more frequently than range retractions, prompting suggestions that species can endure climatic changes by persisting in cool or damp microclimates. We test whether such ‘microrefugia’ exist.
Location United Kingdom
Methods We examine fine-scale changes in plant communities of a coastal grassland over a 30 year period in which spring temperatures increased by 1.4ºC. We examine whether changes in community composition and local colonisations and extinctions are related to microclimatic conditions.
Results Our findings suggest that, while community reassembly was consistent with warming, changes were smaller on cooler, north-facing slopes. Closer inspection of patterns of species turnover revealed that species with low temperature requirements were able to persist on cooler slopes, while those with high moisture requirements suffered similar decreases in occupancy across all microclimates.
Main conclusions Our results suggest that cooler slopes may act as microrefugia, buffering the effects of increases in temperature on plant communities by delaying extinctions of species with low temperature requirements.

AbstractThe world’s warm deserts are predicted to experience disproportionately large temperature increases due to climate change, yet the impacts on global desert biodiversity remain poorly understood. Because species in warm deserts live close to their physiological limits, additional warming may induce local extinctions. Here, we combine climate change projections with biophysical models and species distributions to predict physiological impacts of climate change on desert birds globally. Our results show heterogeneous impacts between and within warm deserts. Moreover, spatial patterns of physiological impacts do not simply mirror air temperature changes. Climate change refugia, defined as warm desert areas with high avian diversity and low predicted physiological impacts, are predicted to persist in varying extents in different desert realms. Only a small proportion (<20%) of refugia fall within existing protected areas. Our analysis highlights the need to increase protection of refugial areas within the world’s warm deserts to protect species from climate change.

The existence of fine-grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed 'microrefugia'. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here, we present a model that is applied to provide fine-grained, multidecadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely derived environmental data were used to construct physical variables that capture the effects of terrain, sea surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom, to provide accurate (mean error = 1.21 °C; RMS error = 1.63 °C) hourly estimates of temperature at a resolution of 100 m for the period 1977-2014. We show that rates of warming vary across a landscape primarily due to long-term trends in weather conditions. Total warming varied from 0.87 to 1.16 °C, with the slowest rates of warming evident on north-east-facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost-free season varied from +11 to -54 days and the increase in annual growing degree-days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west-facing slopes. We emphasize the importance of multidecadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change.

AbstractClimate-driven geographic range shifts have been associated with transitions between dietary specialism and generalism at range margins. The mechanisms underpinning these often transient niche breadth modifications are poorly known, but utilisation of novel resources likely depends on phenological synchrony between the consumer and resource. We use a climate-driven range and host shift by the butterfly Aricia agestis to test how climate-driven changes in host phenology and condition affect phenological synchrony, and consider implications for host use.Our data suggest that the perennial plant which was the primary host before range expansion is a more reliable resource than the annual Geraniaceae upon which the butterfly has become specialised in newly colonised parts of its range. In particular, climate-driven phenological variation in the novel host Geranium dissectum generates a narrow and variable ‘window of opportunity’ for larval productivity in summer. Therefore, although climatic change may allow species to shift hosts and colonise novel environments, specialisation on phenologically-limited hosts may not persist at ecological margins as climate change continues. We highlight the potential role for phenological (a)synchrony in determining lability of consumer-resource associations at range margins, and the importance of considering causes of synchrony in biotic interactions when predicting range shifts.

Landscape-scale approaches are increasingly advocated for species conservation but ensuring landscape level persistence by enlarging the size of patches or increasing their physical connectivity is often impractical. Here, we test how such barriers can be overcome by management of habitat at the local (site-based) level, using a rare butterfly as an exemplar. We used four surveys of the entire UK distribution of the Lulworth Skipper (Thymelicus acteon) over 40 years to test how local habitat influences population density and colonization / extinction dynamics, and parameterized, validated and applied a metapopulation model to simulate effects of varying local habitat quality on regional persistence. We found the total number of populations in four distribution snapshots between 1978 and 2017 varied between 59-84, and from 1997 to 2017 34% of local populations showed turnover (colonization or extinction). Population density was closely linked to vegetation characteristics indicative of management, namely height and food plant frequency, both of which changed through time. Simulating effects of habitat quality on metapopulation dynamics 40 years into the future suggests coordinated changes to two key components of quality (vegetation height and food plant frequency) would increase patch occupancy above the range observed in the past 40 years (50-80%). In contrast, deterioration of either component below threshold levels leads to metapopulation retraction to core sub-networks of patches, or eventual extirpation. Our results indicate that changes to habitat quality can overcome constraints imposed by habitat patch area and spatial location on relative rates of colonization and local extinction, demonstrating the sensitivity of regional dynamics to targeted in situ management. Local habitat management therefore plays a key role in landscape-scale conservation. Monitoring of population density, and the monitoring and management of local (site-level) habitat quality, therefore represent effective and important components of conservation strategies in fragmented landscapes.

Abstract
. The expectation that places with suitable climate will lie outside the current range of many species has shaped 21st century conservation policy and led to predictions of numerous extinctions. We show that the magnitude of range shifts is often overestimated because the climate data typically used do not reflect the microclimatic conditions that many organisms experience. We model the historic (1977–1995) distributions of 302 plant taxa using both macro- and microclimate data and project these distributions forward to present day (2002–2020). Whereas macroclimate models predicted major range shifts (mean: 9.2 km per decade), microclimate models predicted localised shifts into favourable microclimate (mean: 88 m per decade) that more closely match observed patterns of establishment and extinction. In consequence, improving protecting of refugial populations within species’ existing geographic range is likely to be more effective for many species than assisted translocations and overhaul of protected area networks.

Aim Despite predictions of high extinction risk from climate change, range expansions have been documented more frequently than range retractions, prompting suggestions that species can endure climatic changes by persisting in cool or damp microclimates. We test whether such ‘microrefugia’ exist.
Location United Kingdom
Methods We examine fine-scale changes in plant communities of a coastal grassland over a 30 year period in which spring temperatures increased by 1.4ºC. We examine whether changes in community composition and local colonisations and extinctions are related to microclimatic conditions.
Results Our findings suggest that, while community reassembly was consistent with warming, changes were smaller on cooler, north-facing slopes. Closer inspection of patterns of species turnover revealed that species with low temperature requirements were able to persist on cooler slopes, while those with high moisture requirements suffered similar decreases in occupancy across all microclimates.
Main conclusions Our results suggest that cooler slopes may act as microrefugia, buffering the effects of increases in temperature on plant communities by delaying extinctions of species with low temperature requirements.

ABSTRACTMicroclimate information is often crucial for understanding ecological patterns and processes, including under climate change, but is typically absent from ecological and biogeographic studies owing to difficulties in obtaining microclimate data. Recent advances in microclimate modelling, however, suggest that microclimate conditions can now be predicted anywhere at any time using hybrid physically- and empirically-based models. Here, for the first time, we test the utility of this approach across a remote, inaccessible, and climate change threatened polar island ecosystem at ecologically relevant scales. Microclimate predictions were generated at a 100 × 100 m grain (at a height of 4 cm) across the island, with models parameterised using either meteorological observations from the island’s weather station (AWS) or climate reanalysis data (CRA). AWS models had low error rates and were highly correlated with observed seasonal and daily temperatures (root mean squared error of predicted seasonal average Tmean≤ 0.6 °C; Pearson’s correlation coefficient (r) for the daily Tmean≥ 0.86). By comparison, CRA models had a slight warm bias in all seasons and a smaller diurnal range in the late summer period thanin situobservations. Despite these differences, the modelled relationship between the percentage cover of the threatened endemic cushion plantAzorella macquariensisand microclimate varied little with the source of microclimate data (r = 0.97), suggesting that both model parameterisations capture similar patterns of spatial variation in microclimate conditions across the island ecosystem. Here, we have shown that the accurate prediction of microclimate conditions at ecologically relevant spatial and temporal scales is now possible using hybrid physically- and empirically-based models across even the most remote and climatically extreme environments. These advances will help add the microclimate dimension to ecological and biogeographic studies, which could be critical for delivering climate change-resilient conservation planning in climate-change exposed ecosystems.

Abstract
. Tropical forest biodiversity is potentially at high risk from climate change, but most species reside within or beneath the canopy, where they are buffered from extreme temperatures, implying that forest canopies may reduce the severity of warming impacts. Using a mechanistic microclimate model, we quantify hourly below-canopy climate conditions of 300,000 tropical forest locations globally between 1990–2019. We show that while temperature extremes are buffered below canopy, recent small increases in beneath-canopy temperature (<1ºC) have led to highly novel temperature regimes across most of the tropics. This is the case even within ecologically unfragmented areas, suggesting that tropical forests are sensitive to climate change. However, across the globe, some forest areas have experienced low climate novelty and thus serve as. important climate refugia. These areas require urgent protection and restoration. By conducting the first pan-tropical analyses of changes in below-canopy climatic conditions, we challenge the prevailing notion that tropical forest canopies reduce the severity of climate change impacts.

AbstractMicroclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high‐resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open‐access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution.

AbstractThe Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950–2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets: (1) the annual values during 1950–2021; (2) the average conditions for the 1991–2020 climatology; and (3) temporal trends over 1951–2021. The 72-year time series of various climate and event-type indices draws a comprehensive picture of the occurrence and recurrence of extreme weather events and climate variability of the changing Arctic bioclimate.

Abstract
Factors shaping arthropod and plant community structure at fine spatial scales are poorly understood. This includes microclimate, which likely plays a large role in shaping local community patterns, especially in heterogeneous landscapes characterised by high microclimatic variability in space and in time.
We explored differences in local microclimatic conditions and regional species pools in two subarctic regions: Kilpisjärvi in north‐west Finland and Varanger in north‐east Norway. We then investigated the relationship between fine‐scale climatic variation and local community characteristics (species richness and abundance) among plants and arthropods, differentiating the latter into two groups: flying and ground‐dwelling arthropods collected by Malaise and pitfall traps, respectively. Arthropod taxa were identified through DNA metabarcoding. Finally, we examined if plant richness can be used to predict patterns in arthropod communities.
Variation in soil temperature, moisture and snow depth proved similar between regions, despite differences in absolute elevation. For each group of organisms, we found that about half of the species were shared between Kilpisjärvi and Varanger, with a quarter unique to each region.
Plants and arthropods responded largely to the same drivers. The richness and abundance of both groups decreased as elevation increased and were positively correlated with higher soil moisture and temperature values. Plant species richness was a poor predictor of local arthropod richness, in particular for ground‐dwelling arthropods.
Our results reveal how microclimatic variation within each region carves pronounced, yet consistent patterns in local community richness and abundance out of a joint species pool.

AbstractThe world’s warm deserts are predicted to experience disproportionately large temperature increases due to climate change, yet the impacts on global desert biodiversity remain poorly understood. Because species in warm deserts live close to their physiological limits, additional warming may induce local extinctions. Here, we combine climate change projections with biophysical models and species distributions to predict physiological impacts of climate change on desert birds globally. Our results show heterogeneous impacts between and within warm deserts. Moreover, spatial patterns of physiological impacts do not simply mirror air temperature changes. Climate change refugia, defined as warm desert areas with high avian diversity and low predicted physiological impacts, are predicted to persist in varying extents in different desert realms. Only a small proportion (<20%) of refugia fall within existing protected areas. Our analysis highlights the need to increase protection of refugial areas within the world’s warm deserts to protect species from climate change.

Abstract


Microclimate models predict temperature and other meteorological variables at scales relevant to individual organisms. The broad application of microclimate models requires gridded macroclimatic variables as input. However, the spatial and temporal resolution of such inputs can be a limiting factor on the accuracy of microclimate predictions. Due to its fine resolution and accuracy, the ERA5 reanalysis dataset is emerging as the favoured resource for global historical weather and climate data and has great potential for aiding microclimate modelling.

Here we describe mcera5, an R language package that provides convenient access to, and wrangling of, the ERA5 climate datasets for use in microclimate models. Through this package, we provide functions to query ERA5 data for desired spatial and temporal extents, to correct for spatial biases and process outputs for easy interpretation by ecologists, thereby allowing faster and more accurate microclimate predictions.

By validating with empirical observations from multiple biomes globally, we demonstrate that the use of ERA5 climate forcing via mcera5 improves the prediction accuracy of soil moisture, air temperature and relative humidity as compared to forcing with other globally available data and offers comparable performance when predicting soil temperatures.

Through the provision of fine‐resolution ERA5 data, the mcera5 package fits into an ecosystem of tools for modelling microclimate in a spatio‐temporally explicit fashion, advancing our ability to efficiently predict microclimate for any place on Earth for the past, present or future. The package also provides convenient access to ERA5 datasets for a range of other applications.

. Climate-driven geographic range shifts have been associated with transitions between dietary specialism and generalism at range margins. The mechanisms underpinning these often transient niche breadth modifications are poorly known, but utilization of novel resources likely depends on phenological synchrony between the consumer and resource. We use a climate-driven range and host shift by the butterfly
. Aricia agestis
. to test how climate-driven changes in host phenology and condition affect phenological synchrony, and consider implications for host use. Our data suggest that the perennial plant that was the primary host before range expansion is a more reliable resource than the annual Geraniaceae upon which the butterfly has become specialized in newly colonized parts of its range. In particular, climate-driven phenological variation in the novel host
. Geranium dissectum
. generates a narrow and variable ‘window of opportunity' for larval productivity in summer. Therefore, although climatic change may allow species to shift hosts and colonise novel environments, specialization on phenologically limited hosts may not persist at ecological margins as climate change continues. We highlight the potential role for phenological (a)synchrony in determining lability of consumer–resource associations at range margins and the importance of considering causes of synchrony in biotic interactions when predicting range shifts.
.
. This article is part of the theme issue ‘Species’ ranges in the face of changing environments (Part II)’.

AbstractAimSpatial sampling biases in biodiversity data arise because of complex interactions between geography, species characteristics and human behaviour, including preferences for or against particular species or habitats; biases are therefore not necessarily independent of the environmental niches of species. We evaluate when correlations between spatial sampling biases and environmental niches are likely to affect species distribution models (SDMs) developed both with and without attempts to correct these biases.InnovationA virtual species and virtual ecologist framework was used to simulate biodiversity data with either no spatial sampling bias or biases that were correlated (positively or negatively) with one of the environmental variables used to define the environmental niches of the species. The environmental variables used to define the species niche were simulated with spatial autocorrelation operating at multiple spatial scales. Virtual samples were then used to model species distributions, with models evaluated based on their ability to rank the suitability of sites correctly.Main conclusionsCorrelations between spatial sampling bias and environmental niches frequently reduced the rank correlation of model predictions, but the relative importance of these effects varied with species type (greater decline in rank correlation as the environmental niche broadens) and data type (models built using detection/non‐detection data were less affected than those using detection‐only data). Bias‐correction effectiveness varied depending on the structure of the spatial bias but was also highly variable across methods and dependent on data type. The implications of these results are that spatial sampling bias is a greater concern for SDMs where: (1) the distribution of effort is non‐random with respect to an environmental gradient thought to be correlated with a species’ distribution; (2) the species being modelled has a broad environmental niche; and (3) the data for modelling contain only information on detections (i.e. presence only).

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

AbstractA core challenge in global change biology is to predict how species will respond to future environmental change and to manage these responses. To make such predictions and management actions robust to novel futures, we need to accurately characterize how organisms experience their environments and the biological mechanisms by which they respond. All organisms are thermodynamically connected to their environments through the exchange of heat and water at fine spatial and temporal scales and this exchange can be captured with biophysical models. Although mechanistic models based on biophysical ecology have a long history of development and application, their use in global change biology remains limited despite their enormous promise and increasingly accessible software. We contend that greater understanding and training in the theory and methods of biophysical ecology is vital to expand their application. Our review shows how biophysical models can be implemented to understand and predict climate change impacts on species' behavior, phenology, survival, distribution, and abundance. It also illustrates the types of outputs that can be generated, and the data inputs required for different implementations. Examples range from simple calculations of body temperature at a particular site and time, to more complex analyses of species' distribution limits based on projected energy and water balances, accounting for behavior and phenology. We outline challenges that currently limit the widespread application of biophysical models relating to data availability, training, and the lack of common software ecosystems. We also discuss progress and future developments that could allow these models to be applied to many species across large spatial extents and timeframes. Finally, we highlight how biophysical models are uniquely suited to solve global change biology problems that involve predicting and interpreting responses to environmental variability and extremes, multiple or shifting constraints, and novel abiotic or biotic environments.

AbstractClimate change can not only increase the exposure of organisms to higher temperatures but can also drive phenological shifts that alter their susceptibility to conditions at the onset of breeding cycles. Organisms rely on climatic cues to time annual life cycle events, but the extent to which climate change has altered cue reliability remains unclear. Here, we examined the risk of a “climate trap”—a climatically driven desynchronization of the cues that determine life cycle events and fitness later in the season in a temperate reptile, the European adder (Vipera berus). During the winter, adders hibernate underground, buffered against subzero temperatures, and re‐emerge in the spring to reproduce. We derived annual spring‐emergence trends between 1983 and 2017 from historical observations in Cornwall, UK, and related these trends to the microclimatic conditions that adders experienced. Using a mechanistic microclimate model, we computed below‐ and near‐ground temperatures to derive accumulated degree‐hour and absolute temperature thresholds that predicted annual spring‐emergence timing. Trends in annual‐emergence timing and subsequent exposure to ground frost were then quantified. We found that adders have advanced their phenology toward earlier emergence. Earlier emergence was associated with increased exposure to ground frost and, contradicting the expected effects of macroclimate warming, increased post‐emergence exposure to ground frost at some locations. The susceptibility of adders to this “climate trap” was related to the rate at which frost risk diminishes relative to advancement in phenology, which depends on the seasonality of climate. We emphasize the need to consider exposure to changing microclimatic conditions when forecasting biological impacts of climate change.

Context: Climate change will alter the global distribution of climatically suitable space for many species, including agricultural crops. In some locations, warmer temperatures may offer opportunities to grow novel, high value crops, but non-climatic factors also inform agricultural decision-making. These non-climatic factors can be difficult to quantify and incorporate into suitability assessments, particularly for uncertain futures. Objective: to demonstrate how qualitative and quantitative techniques can be combined to assess crop suitability with consideration for climatic and non-climatic factors. Methods: We carried out a horizon scanning exercise that used Delphi methodology to identify possible novel crops for a region in south-west England. We show how the results of the expert panel assessment could be combined with a crop suitability model that only considered climate to identify the best crops to grow in the region. Results and conclusions: Whilst improving climate and crop models will enhance the ability to identify environmental constraints to growing novel crops, we propose horizon scanning as a useful tool to understand constraints on crop suitability that are beyond the parameterisation of these models and that may affect agricultural decisions. Significance: a similar combination of qualitative and quantitative approaches to assessing crop suitability could be used to identify potential novel crops in other regions and to support more holistic assessments of crop suitability in a changing world.

Protected area networks seek to ensure the persistence of multiple species, but their area and extent are limited by available land and conservation resources. Prioritising sites based on their quality, quantity, size, or connectivity is often proposed; potentially using the occupancy and metapopulation dynamics of individual threatened species as surrogates for network effectiveness. However, the extent to which the dynamics of species with overlapping habitat requirements differ, and the implications of this for the optimal network designs for multiple species, are rarely tested. We parameterise metapopulation models for 5 papyrus-specialist birds occupying a network of papyrus swamp in Uganda, each of which possess subtly different ecological characteristics and habitat preferences. We estimate how each responds to different strategies based on prioritising patch size, number, quality and connectivity. The optimal approach differed depending on the metapopulation structure and characteristics of each species. The rank order of strategies also varied with the overall wetland area available and the desired persistence threshold. For individual species, prioritising habitat quality achieved the highest levels of persistence and population size for an equivalent amount of land area conserved. However, connected patches showed greatest overlap across species, thus the most effective strategy to conserve multiple species in the same network prioritised habitat connectivity. This emphasises the importance of individual species' characteristics using the same habitat networks in conservation planning, and demonstrates the utility of prioritising protected sites based on the spatial connectivity of habitat patches, when aiming to conserve multiple species with differing or uncertain habitat requirements.

Abstract
. Context
. Microclimate (fine-scale temperature variability within metres of Earth’s surface) is highly influential on terrestrial organisms’ ability to survive and function. Understanding how such local climatic conditions vary is challenging to measure at adequate spatio-temporal resolution. Microclimate models provide the means to address this limitation, but require as inputs, measurements, or estimations of multiple environmental variables that describe vegetation and terrain variation.
.
. Objectives
. To describe the key components of microclimate models and their associated environmental parameters. To explore the potential of drones to provide scale relevant data to measure such environmental parameters.
.
. Methods
. We explain how drone-mounted sensors can provide relevant data in the context of alternative remote sensing products. We provide examples of how direct micro-meteorological measurements can be made with drones. We show how drone-derived data can be incorporated into 3-dimensional radiative transfer models, by providing a realistic representation of the landscape with which to model the interaction of solar energy with vegetation.
.
. Results
. We found that for some environmental parameters (i.e. topography and canopy height), data capture and processing techniques are already established, enabling the production of suitable data for microclimate models. For other parameters such as leaf size, techniques are still novel but show promise. For most parameters, combining spatial landscape characterization from drone data and ancillary data from lab and field studies will be a productive way to create inputs at relevant spatio-temporal scales.
.
. Conclusions
. Drones provide an exciting opportunity to quantify landscape structure and heterogeneity at fine resolution which are in turn scale-appropriate to deliver new microclimate insights.
.

Aim: Microclimate information is often crucial for understanding ecological patterns and processes, including under climate change, but is typically absent from ecological and biogeographic studies owing to difficulties in obtaining microclimate data. Recent advances in microclimate modelling, however, suggest that microclimate conditions can now be predicted anywhere at any time using hybrid physically and empirically based models. Here, we test these methods across a sparsely vegetated and topographically diverse sub-Antarctic island ecosystem (Macquarie Island). Innovation: Microclimate predictions were generated at a height of 4 cm above the surface on a 100 × 100 m elevation grid across the island for the snow-free season (Oct–Mar), with models driven by either climate reanalysis data (CRA) or CRA data augmented with meteorological observations from the island's automatic weather station (AWS+CRA). These models were compared with predictions from a simple lapse rate model (LR), where an elevational adjustment was applied to hourly temperature measurements from the AWS. Prediction errors tended to be lower for AWS+CRA-driven models, particularly when compared to the CRA-driven models. The AWS+CRA and LR models had similar prediction errors averaged across the season for Tmin and Tmean, but prediction errors for Tmax were much smaller for the former. The within-site correlation between observed and predicted daily Tmean was on average >0.8 in all months for AWS+CRA predictions and >0.7 in all months for LR predictions, but consistently lower for CRA predictions. Main conclusions: Prediction of microclimate conditions at ecologically relevant spatial and temporal scales is now possible using hybrid models, and these often provide added value over lapse rate models, particularly for daily extremes and when driven by in situ meteorological observations. These advances will help add the microclimate dimension to ecological and biogeographic studies and aid delivery of climate change-resilient conservation planning in climate change-exposed ecosystems.

Context: Against a background of unprecedented climate change, humanity faces the challenge of how to increase global food production without compromising the natural environment. Crop suitability models can indicate the best locations to grow different crops and, in doing so, support efficient use of land to leave space for, or share space with, nature. However, challenges in downscaling the climate data needed to drive these models to make predictions for the future has meant that they are often run using national or regional climate projections. At finer spatial scales, variation in climate conditions can have a substantial influence on yield and so the continued use of coarse resolution climate data risks maladaptive agricultural decisions. Opportunities to grow novel crops, for which knowledge of local variation in microclimate may be critical, may be missed. Objective: We demonstrate how microclimate information can be acquired for a region and used to run a mechanistic crop suitability model under present day and possible future climate scenarios. Methods: We use microclimate modelling techniques to generate 100 m spatial resolution climate datasets for the south-west of the UK for present day (2012–2017) and predicted future (2042–2047) time periods. We use these data to run the mechanistic crop model WOrld FOod STudies (WOFOST) for 56 crop varieties, which returns information on maximum crop yields for each planting month. Results and conclusions: over short distances, we find that the highest attainable yields vary substantially and discuss how these differences mean that field-level assessments of climate suitability could support land-use decisions, enabling food production whilst protecting biodiversity. Significance: We provide code for running WOFOST in the WofostR R package, thus enabling integration with microclimate models and meaning that our methodology could be applied anywhere in the world. As such, we make available to anyone the tools to predict climate suitability for crops at high spatial resolution for both present day and possible future climate scenarios.

AbstractEcological research heavily relies on coarse‐gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub‐canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate‐change‐related impacts on forest‐floor biodiversity and functioning, high‐resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near‐surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub‐canopy temperature at 15 cm above the surface and free‐air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub‐canopy air temperatures differ substantially from free‐air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high‐resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub‐canopy temperature maps will enable future research to model below‐canopy biological processes and patterns, as well as species distributions more accurately.

Species distribution models (SDMs) have played a pivotal role in predicting how species might respond to climate change. These models most often rely on correlative methods, whereby a statistical relationship between species’ known occurrences and the climate of those locations is determined and then extrapolated to predict future distributions under climate change scenarios. Such modelling approaches, which seek to find and recreate patterns in species distributions, are not directly associated with the physiological processes that ultimately underlie species’ responses to climate. By incorporating these processes more explicitly into SDMs, the proximal limitations on species distributions can be better understood and subsequent predictions will be more robust over space and time.
This thesis presents research to promote and support the integration of physiological processes into SDMs. It explores major themes in model construction and use and demonstrates how process-based (mechanistic) models might be applied to predict future crop suitability.
In Chapter 2, I review the plant SDM literature and find that physiologically important variables are frequently neglected in models. Ten physiologically relevant variables for plants are identified and in Chapter 3, I present a new global climate classification (CCS) that accounts for variation in these aspects of climate. I show how the popular Köppen CCSs, for which boundaries of zones were chosen to reflect major vegetation patterns, do not entirely reflect the physiological processes that determine plant distributions. I discuss how predictions of climate-driven changes in plant distributions may be unreliable in areas where zone assignment using physiologically relevant variables is different to that of the Köppen systems.
In Chapter 4, I demonstrate the use of microclimate modelling techniques to generate 100m spatial resolution climate data for present and future time periods. I use these data to run the mechanistic crop model WOrld FOod STudies (WOFOST) and show how, by capturing spatial variation in climate suitability, microclimate data could provide better approximations of predicted yields and inform agricultural decision-making. Then, in Chapter 5, I show that incorporating interannual variability into climate suitability assessments or understanding the extent to which average climate data might obscure this variance is also important to consider, even when using mechanistic models.
Finally, I consider how mechanistic crop models might be applied to inform agricultural decisions. In Chapter 6, I demonstrate how the results from a mechanistic crop model may be combined with an expert-informed qualitative assessment of crop suitability to give a holistic understanding of the best crops to grow based on climatic and non-climatic factors. In Chapter 7, I examine how climate-driven changes to crop suitability may lead to conflict between agricultural land use and conservation. I model global crop suitability for current and future time periods and show that agricultural expansion is a major threat to remaining wilderness. I conclude that to protect wilderness and its many values, agricultural systems will need to be transformed.
Overall, this thesis shows why physiological process should become central in endeavours to understand the effects of climate change on species distributions and presents methods to achieve this in ecological research. It shows how reliable predictions of the impacts of climate change on crop suitability could help reconcile food security and conservation goals.

Species distribution models (SDMs) have played a pivotal role in predicting how species might respond to climate change. These models most often rely on correlative methods, whereby a statistical relationship between species’ known occurrences and the climate of those locations is determined and then extrapolated to predict future distributions under climate change scenarios. Such modelling approaches, which seek to find and recreate patterns in species distributions, are not directly associated with the physiological processes that ultimately underlie species’ responses to climate. By incorporating these processes more explicitly into SDMs, the proximal limitations on species distributions can be better understood and subsequent predictions will be more robust over space and time.
This thesis presents research to promote and support the integration of physiological processes into SDMs. It explores major themes in model construction and use and demonstrates how process-based (mechanistic) models might be applied to predict future crop suitability.
In Chapter 2, I review the plant SDM literature and find that physiologically important variables are frequently neglected in models. Ten physiologically relevant variables for plants are identified and in Chapter 3, I present a new global climate classification (CCS) that accounts for variation in these aspects of climate. I show how the popular Köppen CCSs, for which boundaries of zones were chosen to reflect major vegetation patterns, do not entirely reflect the physiological processes that determine plant distributions. I discuss how predictions of climate-driven changes in plant distributions may be unreliable in areas where zone assignment using physiologically relevant variables is different to that of the Köppen systems.
In Chapter 4, I demonstrate the use of microclimate modelling techniques to generate 100m spatial resolution climate data for present and future time periods. I use these data to run the mechanistic crop model WOrld FOod STudies (WOFOST) and show how, by capturing spatial variation in climate suitability, microclimate data could provide better approximations of predicted yields and inform agricultural decision-making. Then, in Chapter 5, I show that incorporating interannual variability into climate suitability assessments or understanding the extent to which average climate data might obscure this variance is also important to consider, even when using mechanistic models.
Finally, I consider how mechanistic crop models might be applied to inform agricultural decisions. In Chapter 6, I demonstrate how the results from a mechanistic crop model may be combined with an expert-informed qualitative assessment of crop suitability to give a holistic understanding of the best crops to grow based on climatic and non-climatic factors. In Chapter 7, I examine how climate-driven changes to crop suitability may lead to conflict between agricultural land use and conservation. I model global crop suitability for current and future time periods and show that agricultural expansion is a major threat to remaining wilderness. I conclude that to protect wilderness and its many values, agricultural systems will need to be transformed.
Overall, this thesis shows why physiological process should become central in endeavours to understand the effects of climate change on species distributions and presents methods to achieve this in ecological research. It shows how reliable predictions of the impacts of climate change on crop suitability could help reconcile food security and conservation goals.

. The consequences of climate change for biogeographic range dynamics depend on the spatial scales at which climate influences focal species directly and indirectly via biotic interactions. An overlooked question concerns the extent to which microclimates modify specialist biotic interactions, with emergent properties for communities and range dynamics. Here, we use an in-field experiment to assess egg-laying behaviour of a range-expanding herbivore across a range of natural microclimatic conditions. We show that variation in microclimate, resource condition and individual fecundity can generate differences in egg-laying rates of almost two orders of magnitude in an exemplar species, the brown argus butterfly (
. Aricia agestis
. ). This within-site variation in fecundity dwarfs variation resulting from differences in average ambient temperatures among populations. Although higher temperatures did not reduce female selection for host plants in good condition, the thermal sensitivities of egg-laying behaviours have the potential to accelerate climate-driven range expansion by increasing egg-laying encounters with novel hosts in increasingly suitable microclimates. Understanding the sensitivity of specialist biotic interactions to microclimatic variation is, therefore, critical to predict the outcomes of climate change across species' geographical ranges, and the resilience of ecological communities.
.

Climate strongly influences ecological patterns and processes at scales ranging from local to global. Studies of ecological responses to climate usually rely on data derived from weather stations, where temperature and humidity may differ substantially from that in the microenvironments in which organisms reside. To help remedy this, we present a model that leverages first principles physics to predict microclimate above, within, and below the canopy in any terrestrial location on earth, made freely available as an R software package. The model can be run in one of two modes. In the first, heat and vapour exchange within and below canopy are modelled as transient processes, thus accounting for fine temporal-resolution changes. In the second, steady-state conditions are assumed, enabling conditions at hourly intervals or longer to be estimated with greater computational efficiency. We validated both modes of the model with empirical below-canopy thermal measurements from several locations globally, resulting in hourly predictions with mean absolute error of 2.77 °C and 2.79 °C for the transient and steady-state modes respectively. Alongside the microclimate model, several functions are provided to assist data assimilation, as well as different parameterizations to capture a variety of habitats, allowing flexible application even when little is known about the study location. The model's modular design in a programming language familiar to ecological researchers provides easy access to the modelling of site-specific climate forcing, in an attempt to more closely unify the fields of micrometeorology and ecology.

AbstractMotivationMore than half of Earth's species are contained in a mere 1.4% of its land area, but the climates of many of these biodiversity hotspots are projected to disappear as a consequence of anthropogenic climate change. There is growing recognition that spatio‐temporal patterns of climate in biodiversity hotspots have shaped biological diversity over a variety of historical time‐scales, yet these patterns are rarely taken into account in assessments of the vulnerability of biodiversity hotspots to future climate change. In our review, we synthesize the climatic processes that have led to the diversification of hotspots and interpret what this means in the context of anthropogenic climate change. We demonstrate the importance of mesoclimatic processes and fine‐scale topographical heterogeneity, in combination with climatic variability, in driving speciation processes and maintaining high levels of diversity. We outline why these features of hotspots are crucial to understanding the impacts of anthropogenic climate change and discuss how recent advances in predictive modelling enable vulnerability to be understood better.LocationGlobal.Main conclusionsWe contend that many, although not all, biodiversity hotspots have climate and landscape characteristics that create fine‐scale spatial variability in climate, which potentially buffers them from climatic changes. Temporally, many hotspots have also experienced stable climates through evolutionary time, making them particularly vulnerable to future changes. Others have experienced more variable climates, which is likely to provide resilience to future changes. Thus, in order to identify risk for global biodiversity, we need to consider carefully the influence of spatio‐temporal variability in climate. However, most vulnerability assessments in biodiversity hotspots are still reliant on climate data with coarse spatial and temporal resolution. Higher‐resolution forecasts that account for spatio‐temporal variability in climate and account better for the physiological responses of organisms to this variability are much needed to inform future conservation strategies.

A considerable body of scientific evidence shows that the world is currently suffering a biodiversity crisis driven by anthropogenic factors such as land-use change, environmental pollution and climate change. Our knowledge of this crisis is incomplete, however, particularly when it comes to the most diverse multi-cellular organisms on the planet, the insects. Although there is evidence of decline in the abundance, distribution and biomass of many insect species, recent attempts to extrapolate these to global scales and encourage a policy response have been met with scepticism. More data are required, together with reliable methods to integrate and interpret them. In parallel, evidence-based conservation initiatives are urgently needed to address the biodiversity crisis.

Citizen science has great promise for gathering much-needed data on insect trends and for engaging the public in biodiversity conservation. Citizen science has undergone a rapid rise in popularity over the past two decades, increasing the capacity for cost-effective, spatially-extensive biodiversity monitoring, while also raising awareness and commitment to nature conservation among participating members of the public. However, citizen science approaches can also present challenges, such as reductions in data quality, constraints in sampling strategies and in the onward reuse of data.

In this thesis, citizen science monitoring of Great Britain’s (GB) moths and butterflies is examined as a case study, assessing some of the benefits and limitations of increased participation and demonstrating applications of citizen science data in determining species trends, drivers of change and estimates of extinction risk.

Overall moth abundance has decreased in GB, probably mainly as a result of habitat degradation, while climate change has enabled the range expansion of some species (Chapter 2). Much remains to be learnt about other potential drivers of change, such as chemical pollution and artificial light at night (Chapter 2). I demonstrated the efficacy of citizen science by calculating GB distribution trends for 673 moth species for the first time, finding that 260 species had undergone statistically significant long-term declines compared with 160 that had increased significantly (Chapter 3). The geographical patterns of change were consistent with expected responses to land-use, nutrient enrichment and climatic change (Chapter 3). I also utilised citizen-science derived monitoring data for 485 Lepidoptera species to investigate the impact of insect population variability on the assessment of Red List extinction risk using 10-year trends as specified by the International Union for Conservation of Nature procedure (Chapter 5). I concluded that for these taxa, strict use of 10-year trends produces Red List classifications that are unacceptably biased by the start year (Chapter 5).

In Chapter 4, I showed that mass-participation citizen science data obtained using a simple sampling protocol produced comparable estimates of butterfly species abundance to data collected through standardized monitoring undertaken by experienced volunteers. Resulting increases in participation, along with the associated benefits of public engagement and awareness raising, need not have a detrimental impact on the ability to detect abundance trends in common butterfly species. However, citizen science participation may affect the onward use of data, unless this is considered at the outset. I found that despite support in principle for open access to distribution records of butterflies and moths, most citizen scientists were much more cautious in practice, preferring to limit the spatial resolution of records, particularly of threatened species, and restrict commercial reuse of data (Chapter 6).

Overall, these results demonstrate the potential for citizen science, involving both expert volunteer naturalists and inexperienced members of the public, to address the global biodiversity knowledge gap through generating meaningful trend estimates for insect species and elucidating the drivers of change.

AbstractThe impacts of the changing climate on the biological world vary across latitudes, habitats and spatial scales. By contrast, the time of day at which these changes are occurring has received relatively little attention. As biologically significant organismal activities often occur at particular times of day, any asymmetry in the rate of change between the daytime and night‐time will skew the climatic pressures placed on them, and this could have profound impacts on the natural world. Here we determine global spatial variation in the difference in the mean annual rate at which near‐surface daytime maximum and night‐time minimum temperatures and mean daytime and mean night‐time cloud cover, specific humidity and precipitation have changed over land. For the years 1983–2017, we derived hourly climate data and assigned each hour as occurring during daylight or darkness. In regions that showed warming asymmetry of >0.5°C (equivalent to mean surface temperature warming during the 20th century) we investigated corresponding changes in cloud cover, specific humidity and precipitation. We then examined the proportional change in leaf area index (LAI) as one potential biological response to diel warming asymmetry. We demonstrate that where night‐time temperatures increased by >0.5°C more than daytime temperatures, cloud cover, specific humidity and precipitation increased. Conversely, where daytime temperatures increased by >0.5°C more than night‐time temperatures, cloud cover, specific humidity and precipitation decreased. Driven primarily by increased cloud cover resulting in a dampening of daytime temperatures, over twice the area of land has experienced night‐time warming by >0.25°C more than daytime warming, and has become wetter, with important consequences for plant phenology and species interactions. Conversely, greater daytime relative to night‐time warming is associated with hotter, drier conditions, increasing species vulnerability to heat stress and water budgets. This was demonstrated by a divergent response of LAI to warming asymmetry.

The fingerprints of anthropogenic climate change are increasingly visible in myriad ecological events and processes, from physiology to population dynamics and species’ distributions. In particular, the timing of life cycle events (phenology) is widely regarded as a sensitive indicator of ecological responses to climate change. Phenological responses to climate change, such as advanced timing of reproduction or lengthened activity periods, are widespread but vary markedly within and between species. These changes can alter the abiotic conditions and biotic interactions to which organisms are exposed, and determine the time available for population growth, which ultimately underpins species’ distributions. Consequently, there are many means by which phenological change may influence population dynamics and distribution. However, such relationships are rarely explicitly tested, and their underlying mechanisms are relatively unexplored.
In this thesis, I therefore aimed to investigate the relationships between phenology, population dynamics and distribution. I also sought to examine how these may be affected by climate and mediated by biotic interactions, and to highlight potential community-level consequences of these relationships. I use butterflies as a model system, in part due to their sensitivity to environmental change and their status as indicators of insects and the state of terrestrial biodiversity. Here, I develop modelling approaches which can detect relationships between phenology, population dynamics and environmental drivers, and that are adaptable to other study systems. I further demonstrate how the model outputs can be used to investigate drivers of species’ range dynamics. I also identify specific biotic interactions that may underpin changes to species’ population dynamics following climate-driven phenological change.
I first investigate the relationships between climate, phenology and population dynamics for a community of butterfly species. I demonstrate community-wide phenological advances in response to warm spring-summer temperatures, which may contribute to temporal synchrony in community dynamics under climate change. However, relative community composition is likely to vary between years as species’ population dynamics respond idiosyncratically to environmental variation. Critically, I highlight that early emergence is associated with population growth in some species over an elevational gradient, and suggest that a robust understanding of population dynamic responses to climate change may require knowledge of the relationship between phenology and population dynamics, and how it is affected by climate change.
In the following chapters I address the potential role of phenological synchrony between a butterfly and its larval host plants in driving changes in population dynamics and range expansion. In Chapters 3 and 4 I present the results of field-based observational and experimental research on the brown argus butterfly Aricia agestis in the UK, particularly in populations where the species uses annual host plants of the family Geraniaceae. I first assay environment-driven variation in butterfly egg-laying behaviour on its ephemeral annual host plants. I show that climatic effects on dietary specialist species will depend on the interaction between direct effects of climate on behaviours (such as egg-laying), and indirect effects mediated by changes in the availability of preferred high-quality plant resources. I then investigate the climatic drivers of quality and phenology in these host plant resources. I demonstrate that climatic variation and change may generate a narrow phenological window of opportunity for exploitation by the consumer, with a potential for trophic asynchrony.
In Chapter 5 I apply a novel modelling approach to investigate the scope for phenological change and climatic conditions to alter consumer population dynamics and distribution, focusing on the recent dynamics of the brown argus in the UK. I identify relationships between phenology and population dynamics that are consistent with the occurrence of population bottlenecks resulting from climate-driven asynchrony with ephemeral resources. I then demonstrate that patterns of phenology which improve consumer:resource synchrony are associated with consumer range expansion over a 25-year period.
These findings provide a valuable insight into the relations between phenology, population dynamics and distribution, and the mechanisms that underpin these relationships. They suggest that a more complete understanding of the ecological effects of environmental change will require simultaneous consideration of the direct and indirect effects of climate on a diverse suite of interrelated processes that act from the individual to the (meta-)population level.

Most studies on the biological effects of future climatic changes rely on seasonally aggregated, coarse-resolution data. Such data mask spatial and temporal variability in microclimate driven by terrain, wind and vegetation, and ultimately bear little resemblance to the conditions that organisms experience in the wild. Here, I present the methods for providing fine-grained, hourly and daily estimates of current and future temperature and soil moisture over decadal timescales. Observed climate data and spatially coherent probabilistic projections of daily future weather were disaggregated to hourly and used to drive empirically calibrated physical models of thermal and hydrological microclimates. Mesoclimatic effects (cold-air drainage, coastal exposure and elevation) were determined from the coarse-resolution climate surfaces using thin-plate spline models with coastal exposure and elevation as predictors. Differences between micro and mesoclimate temperatures were determined from terrain, vegetation and ground properties using energy balance equations. Soil moisture was computed in a thin upper layer and an underlying deeper layer, and the exchange of water between these layers was calculated using the van Genuchten equation. Code for processing the data and running the models is provided as a series of R packages. The methods were applied to the Lizard Peninsula, United Kingdom, to provide hourly estimates of temperature (100 m grid resolution over entire area, 1 m for a selected area) for the periods 1983-2017 and 2041-2049. Results indicated that there is a fine-resolution variability in climatic changes, driven primarily by interactions between landscape features and decadal trends in weather conditions. High-temporal resolution extremes in conditions under future climate change were predicted to be considerably less novel than the extremes estimated using seasonally aggregated variables. The study highlights the need to more accurately estimate the future climatic conditions experienced by organisms and equips biologists with the means to do so.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

Abstract


Legislation commonly mandates the mitigation of impacts to biodiversity in planning and development processes, with potential impacts identified through some form of ecological impact assessment. Yet, protections for biodiversity are frequently undermined because the distributions of priority species are poorly known in most locations at the spatial scales required to inform planning decisions (i.e. c. 1–100 ha).

Planning applications are often screened against opportunistic records to determine potential impacts to priority species. However, raw occurrence records provide information only on where a species has been detected and cannot be used to indicate if a species is likely to be absent from a site.

Inferences drawn from these data on the likelihood of a species being present at a site can only be correctly interpreted through an appropriate species distribution modelling (SDM) framework that ensures assumptions about the data and models are formalised and documented. We argue that SDM frameworks must be integrated into ecological impact assessments to improve support for biodiversity protections within planning and development processes.

Biases and uncertainties in opportunistic data create modelling challenges, but recent methodological advances can minimise their impacts on predictions. We advocate co‐production with practitioners of SDM tools, mapping products and best‐practice guidelines specific to planning processes.

Policy implications. The integration of species distribution modelling frameworks into ecological impact assessments will strengthen biodiversity protections in planning and development processes by ensuring methodological transparency and rigour in the interpretation of species occurrence data.

AbstractMany analyses of biological responses to climate rely on gridded climate data derived from weather stations, which differ from the conditions experienced by organisms in at least two respects. First, the microclimate recorded by a weather station is often quite different to that near the ground surface, where many organisms live. Second, the temporal and spatial resolutions of gridded climate datasets derived from weather stations are often too coarse to capture the conditions experienced by organisms. Temporally and spatially coarse data have clear benefits in terms of reduced model size and complexity, but here we argue that coarse‐grained data introduce errors that, in biological studies, are too often ignored. However, in contrast to common perception, these errors are not necessarily caused directly by a spatial mismatch between the size of organisms and the scale at which climate data are collected. Rather, errors and biases are primarily due to (a) systematic discrepancies between the climate used in analysis and that experienced by organisms under study; and (b) the non‐linearity of most biological responses in combination with differences in climate variance between locations and time periods for which models are fitted and those for which projections are made. We discuss when exactly problems of scale can be expected to arise and highlight the potential to circumvent these by spatially and temporally down‐scaling climate. We also suggest ways in which adjustments to deal with issues of scale could be made without the need to run high‐resolution models over wide extents.

Citizen science plays an increasingly important role in biodiversity research and conservation, enabling large volumes of data to be gathered across extensive spatial scales in a cost-effective manner. Open access increases the utility of such data, informing land-use decisions that may affect species persistence, enhancing transparency and encouraging proliferation of research applications. However, open access provision of recent, fine-scale spatial information on the locations of species may also prompt legitimate concerns among contributors regarding possible unintended negative conservation impacts, violations of privacy and commercial exploitation of volunteer-gathered data. Here we canvas the attitudes towards open access of contributors (104 regional co-ordinators and 510 recorders) of species occurrence records to two of the largest citizen science biodiversity recording schemes, the UK’s Butterflies for the New Millennium project and National Moth Recording Scheme. We find that while the majority of participants expressed support for open access in principle, most were more cautious in practice, preferring to limit the spatial resolution of records, particularly of threatened species, and restrict commercial reuse of data. In addition, citizen scientists’ opinions differed between UK countries, taxonomic groups and the level of involvement volunteers had in the schemes. In order to maintain successful and democratic citizen science schemes, organisers, funders and data users must understand and respect participants’ expectations and aspirations regarding open data while seeking to optimise data use for scientific and societal benefits.

Species-focused conservation planning is often based on reducing local extinction risk at key sites. However, with increasing levels of habitat fragmentation and pressures from climate change and overexploitation, surrounding landscapes also influence the persistence of species populations, and their effects are increasingly incorporated in conservation planning and management for both species and communities. Here, we present a framework based on metapopulation dynamics in fragmented landscapes, for quantifying the survival (resistance) and reestablishment of species populations following localized extinction events (resilience). We explore the application of this framework to guide the conservation of a group of threatened bird species endemic to papyrus (Cyperus papyrus) swamps in East and Central Africa. Using occupancy data for five species collected over two years from a network of wetlands in Uganda, we determine the local and landscape factors that influence local extinction and colonization, and map expected rates of population turnover across the network to draw inferences about the locations that contribute most to regional resistance and resilience for all species combined. Slight variation in the factors driving extinction and colonization between individual papyrus birds led to species-specific differences in the spatial patterns of site-level resistance and resilience. However, despite this, locations with the highest resistance and/or resilience overlapped for most species and reveal where resources could be invested for multispecies persistence. This novel simplified framework can aid decision making associated with conservation planning and prioritization for multiple species residing in overlapping, fragmented habitats; helping to identify key sites that warrant urgent conservation protection, with consideration of the need to adapt and respond to future change.

Although the number of studies discerning the impact of climate change on ecological systems continues to increase, there has been relatively little sharing of the lessons learnt when accumulating this evidence. At a recent workshop entitled ‘Using climate data in ecological research’ held at the UK Met Office, ecologists and climate scientists came together to discuss the robust analysis of climate data in ecology. The discussions identified three common pitfalls encountered by ecologists: 1) selection of inappropriate spatial resolutions for analysis; 2) improper use of publically available data or code; and 3) insufficient representation of the uncertainties behind the adopted approach. Here, we discuss how these pitfalls can be avoided, before suggesting ways that both ecology and climate science can move forward. Our main recommendation is that ecologists and climate scientists collaborate more closely, on grant proposals and scientific publications, and informally through online media and workshops. More sharing of data and code (e.g. via online repositories), lessons and guidance would help to reconcile differing approaches to the robust handling of data. We call on ecologists to think critically about which aspects of the climate are relevant to their study system, and to acknowledge and actively explore uncertainty in all types of climate data. and we call on climate scientists to make simple estimates of uncertainty available to the wider research community. Through steps such as these, we will improve our ability to robustly attribute observed ecological changes to climate or other factors, while providing the sort of influential, comprehensive analyses that efforts to mitigate and adapt to climate change so urgently require.

Savanna ecosystems are an integral part of the African landscape and sustain the livelihoods of millions of people. Woody encroachment in savannas is a widespread phenomenon but its causes are widely debated. We review the extensive literature on woody encroachment to help improve understanding of the possible causes and to highlight where and how future scientific efforts to fully understand these causes should be focused. Rainfall is the most important determinant of maximum woody cover across Africa, but fire and herbivory interact to reduce woody cover below the maximum at many locations. We postulate that woody encroachment is most likely driven by CO2 enrichment and propose a two-system conceptual framework, whereby mechanisms of woody encroachment differ depending on whether the savanna is a wet or dry system. In dry savannas, the increased water-use efficiency in plants relaxes precipitation-driven constraints and increases woody growth. In wet savannas, the increase of carbon allocation to tree roots results in faster recovery rates after disturbance and a greater likelihood of reaching sexual maturity. Our proposed framework can be tested using a mixture of experimental and earth observational techniques. At a local level, changes in precipitation, burning regimes or herbivory could be driving woody encroachment, but are unlikely to be the explanation of this continent-wide phenomenon.

The existence of fine-grain climate heterogeneity has prompted suggestions that species may be able to survive future climate change in pockets of suitable microclimate, termed 'microrefugia'. However, evidence for microrefugia is hindered by lack of understanding of how rates of warming vary across a landscape. Here, we present a model that is applied to provide fine-grained, multidecadal estimates of temperature change based on the underlying physical processes that influence microclimate. Weather station and remotely derived environmental data were used to construct physical variables that capture the effects of terrain, sea surface temperatures, altitude and surface albedo on local temperatures, which were then calibrated statistically to derive gridded estimates of temperature. We apply the model to the Lizard Peninsula, United Kingdom, to provide accurate (mean error = 1.21 °C; RMS error = 1.63 °C) hourly estimates of temperature at a resolution of 100 m for the period 1977-2014. We show that rates of warming vary across a landscape primarily due to long-term trends in weather conditions. Total warming varied from 0.87 to 1.16 °C, with the slowest rates of warming evident on north-east-facing slopes. This variation contributed to substantial spatial heterogeneity in trends in bioclimatic variables: for example, the change in the length of the frost-free season varied from +11 to -54 days and the increase in annual growing degree-days from 51 to 267 °C days. Spatial variation in warming was caused primarily by a decrease in daytime cloud cover with a resulting increase in received solar radiation, and secondarily by a decrease in the strength of westerly winds, which has amplified the effects on temperature of solar radiation on west-facing slopes. We emphasize the importance of multidecadal trends in weather conditions in determining spatial variation in rates of warming, suggesting that locations experiencing least warming may not remain consistent under future climate change.

Landscape-scale approaches to conservation stem largely from the classic ideas of reserve design: encouraging bigger and more sites, enhancing connectivity among sites, and improving habitat quality. Trade-offs are imposed between these four strategies by the limited resources and opportunities available for conservation programmes, including the establishment and management of protected areas, and wildlife-friendly farming and forestry. Although debate regarding trade-offs between the size, number, connectivity and quality of protected areas was prevalent in the 1970–1990s, the implications of the same trade-offs for ongoing conservation responses to threats from accelerating environmental change have rarely been addressed. Here, we reassess the implications of reserve design theory for landscape-scale conservation, and present a blueprint to help practitioners to prioritise among the four strategies. We consider the new perspectives placed on landscape-scale conservation programmes by twenty-first century pressures including climate change, invasive species and the need to marry food security with biodiversity conservation. A framework of the situations under which available theory and evidence recommend that each of the four strategies be prioritized is provided, seeking to increase the clarity required for urgent conservation decision-making.

The cultivation of grapevines for winemaking, known as viticulture, is widely cited as a climate-sensitive agricultural system that has been used as an indicator of both historic and contemporary climate change. Numerous studies have questioned the viability of major viticulture regions under future climate projections. We review the methods used to study the impacts of climate change on viticulture in the light of what is known about the effects of climate and weather on the yields and quality of vineyard harvests. Many potential impacts of climate change on viticulture, particularly those associated with a change in climate variability or seasonal weather patterns, are rarely captured. Key biophysical characteristics of viticulture are often unaccounted for, including the variability of grapevine phenology and the exploitation of microclimatic niches that permit successful cultivation under suboptimal macroclimatic conditions. We consider how these same biophysical characteristics permit a variety of strategies by which viticulture can adapt to changing climatic conditions. The ability to realize these strategies, however, is affected by uneven exposure to risks across the winemaking sector, and the evolving capacity for decision-making within and across organizational boundaries. The role grape provenance plays in shaping perceptions of wine value and quality illustrates how conflicts of interest influence decisions about adaptive strategies within the industry. We conclude by considering what lessons can be taken from viticulture for studies of climate change impacts and the capacity for adaptation in other agricultural and natural systems.

The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020-2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements.

© 2015 British Ecological Society. Successful conservation will increasingly depend on our ability to help species cope with climate change. While there has been much attention on accommodating or assisting range shifts, less has been given to the alternative strategy of helping species survive climate change through in situ management. Here we provide a synthesis of published evidence examining whether habitat management can be used to offset the adverse impacts on biodiversity of changes in temperature, water availability and sea-level rise. Our focus is on practical methods whereby the local environmental conditions experienced by organisms can be made more suitable. Many studies suggest that manipulating vegetation structure can alter the temperature and moisture conditions experienced by organisms, and several demonstrate that these altered conditions benefit species as regional climatic conditions become unsuitable. The effects of topography on local climatic conditions are even better understood, but the alteration of topography as a climate adaptation tool is not ingrained in conservation practice. Trials of topographic alteration in the field should therefore be a priority for future research. Coastal systems have the natural capacity to keep pace with climate change, but require sufficient sediment supplies and space for landward migration to do so. There is an extensive literature on managed realignment. While the underlying rationale is simple, successful implementation requires careful consideration of elevation and past land use. Even with careful management, restored habitats may not attain the physical and biological attributes of natural habitats. Synthesis and applications. The recent literature provides a compelling case that some of the adverse effects of climate change can be offset by appropriate management. However, much of the evidence for this is indirect and too few studies provide empirical tests of the long-term effectiveness of these management interventions. It is clear from the existing evidence that some techniques have a higher risk of failure or unexpected outcomes than others and managers will need to make careful choices about which to implement. We have assessed the strength of evidence of these approaches in order to demonstrate to conservation professionals the risks involved.

Extracting sediment cores for palaeoecological and archaeological investigations has occurred extensively across England since the early 20th century. Surprisingly, there has been comparatively little collation of these valuable publications and potential sources of data; for example, a search on the European Pollen Database (1st Aug 2014 edition) found just 118 core sites for the whole of Great Britain. Here, using a combination of systematic meta-searching and knowledge of the unpublished (‘grey’) literature, we have assembled a meta-database of some 763 sediment cores for palaeoecological records, documented across 273 scientific studies. The majority of these (>90 %) were sediment cores upon which pollen analyses had been performed, but other types of evidence, such as plant macrofossil and faunal records were also identified. We are making this meta-database publicly available, in the hope that it will assist further investigations into Holocene vegetation history, palaeoecology, geoarchaeology and environmental change.

Extracting sediment cores for palaeoecological and archaeological investigations has occurred extensively across England since the early 20th century. Surprisingly, there has been comparatively little collation of these valuable publications and potential sources of data; for example, a search on the European Pollen Database (1st Aug 2014 edition) found just 118 core sites for the whole of Great Britain. Here, using a combination of systematic meta-searching and knowledge of the unpublished (‘grey’) literature, we have assembled a meta-database of some 763 sediment cores for palaeoecological records, documented across 273 scientific studies. The majority of these (>90 %) were sediment cores upon which pollen analyses had been performed, but other types of evidence, such as plant macrofossil and faunal records were also identified. We are making this meta-database publicly available, in the hope that it will assist further investigations into Holocene vegetation history, palaeoecology, geoarchaeology and environmental change.

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.

Microclimate has been known to drive variation in the distribution and abundance of insects for some time. Until recently however, quantification of microclimatic effects has been limited by computing constraints and the availability of fine-scale biological data. Here, we tested fine-scale patterns of persistence/extinction in butterflies and moths against two computed indices of microclimate derived from Digital Elevation Models: a summer solar index, representing fine-scale variation in temperature, and a topographic wetness index, representing fine-scale variation in moisture availability. We found evidence of microclimate effects on persistence in each of four 20 × 20 km British landscapes selected for study (the Brecks, the Broads, Dartmoor, and Exmoor). Broadly, local extinctions occurred more frequently in areas with higher minimum or maximum solar radiation input, while responses to wetness varied with landscape context. This negative response to solar radiation is consistent with a response to climatic warming, wherein grid squares with particularly high minimum or maximum insolation values provided an increasingly adverse microclimate as the climate warmed. The variable response to wetness in different landscapes may have reflected spatially variable trends in precipitation. We suggest that locations in the landscape featuring cooler minimum and/or maximum temperatures could act as refugia from climatic warming, and may therefore have a valuable role in adapting conservation to climatic change.

Microclimate has been known to drive variation in the distribution and abundance of insects for some time. Until recently however, quantification of microclimatic effects has been limited by computing constraints and the availability of fine-scale biological data. Here, we tested fine-scale patterns of persistence/extinction in butterflies and moths against two computed indices of microclimate derived from Digital Elevation Models: a summer solar index, representing fine-scale variation in temperature, and a topographic wetness index, representing fine-scale variation in moisture availability. We found evidence of microclimate effects on persistence in each of four 20 × 20 km British landscapes selected for study (the Brecks, the Broads, Dartmoor, and Exmoor). Broadly, local extinctions occurred more frequently in areas with higher minimum or maximum solar radiation input, while responses to wetness varied with landscape context. This negative response to solar radiation is consistent with a response to climatic warming, wherein grid squares with particularly high minimum or maximum insolation values provided an increasingly adverse microclimate as the climate warmed. The variable response to wetness in different landscapes may have reflected spatially variable trends in precipitation. We suggest that locations in the landscape featuring cooler minimum and/or maximum temperatures could act as refugia from climatic warming, and may therefore have a valuable role in adapting conservation to climatic change.

Papyrus Cyperus papyrus swamps sustain the livelihoods of millions of people, but threats to this habitat have never been quantified formally. Birds are useful indicators of threats that cannot be measured directly. Using satellite imagery classification and habitat associated modelling, we quantify drainage and present International Union for Conservation of Nature (IUCN) Red List assessments for the eight taxa most closely associated with this habitat. We show that, between 1984-1987 and 1999-2001 the areal extent of papyrus declined by 6.7 % from 1,643 to 1,532 km2. Papyrus-specialist avifauna has undergone much greater declines, due in part to fragmentation effects and in part to geographical overlap between areas of highest population densities and areas that have experienced greatest habitat loss. Our assessment does not alter the IUCN Red List status of any full species, but it improves current knowledge of the drivers of their extinction risk. Papyrus gonolek Laniarius mufumbiri should remain at least near threatened, but on the basis of population decline rather than a purported small and decreasing range size, and papyrus yellow warbler Chloropeta gracilirostris should remain vulnerable, but again due to declines rather than on the basis of previous under-estimates of population size. Other species should remain listed as least concern. However, taxonomically, likely specifically, distinct populations of papyrus yellow warbler in Zambia and Kenya are highly threatened and should be listed as endangered and critically endangered respectively. We propose several conservation priorities and discuss means of achieving these in a manner consistent with maintaining the livelihoods of people. © 2013 Springer Science+Business Media Dordrecht.

There has been considerable recent concern about the plight of seabirds globally, as many species have declined substantially. In the UK there are statutory needs to monitor seabirds at sea, particularly in light of new offshore areas being designated for conservation and plans for major offshore wind farm developments. However, the extent to which at-sea surveys are capable of detecting changes in abundance and options for improving survey protocols have received little attention. We investigate the power of detecting changes in numbers using at-sea surveys. Using data collected as part of a visual aerial seabird survey programme that covered areas of 'Round 2' offshore wind farm developments in UK waters, we quantify the variability and characterize the statistical properties of count data. By generating random datasets with the same properties as real data, we estimated the power of being able to detect various declines (50, 33, 25, 15 and 10%) and assessed the effects of survey duration and frequency and of spatial scale and variability in bird numbers. The results indicate that the survey design protocols used for the UK 'Round 2' offshore wind farm visual aerial seabird survey programme do not provide adequate means of detecting changes in numbers, even when declines are in excess of 50% and assumptions regarding certainty are relaxed to < 80%. Extending the duration, frequency and spatial extent of surveys would increase the probability of detecting changes, but not to a desirable level (e.g. > 0.8). The primary reason why there is a low probability of being able to detect consistent directional changes is that seabird numbers fluctuate greatly at any given location. Means of explaining this fine-scale variability are required, especially if small changes in populations are to be detected. Incorporating hydrodynamic variables into trend analysis might increase the power of detecting changes. Failure to detect changes in seabird numbers should not be taken to mean that no changes are occurring. © 2012 British Ornithologists' Union.

Soil moisture and surface water conditions are key determinants of plant community composition and ecosystem function, and predicting such conditions is an important step in understanding the ecological consequences of environmental change. Typically, hydrological models that use real landscape features do not simulate water conditions at the fine spatial and temporal scales that are meaningful to many plant species and ecological processes. We present a hydrological model that simulates daily soil moisture and surface water conditions at a spatial resolution of 1m×1m. The model is applied to 16km 2 of the Lizard Peninsula, UK. The model is kept computationally efficient by combining a simple lumped parameter basin approach with the distributed hydrological effects of basin topography. We also model the complex flows occurring between small basins. Code for running the model using R statistical software is provided as supplementary material. As inputs, the model uses widely available daily weather variables, 1m×1m resolution digital elevation data (LiDAR) and some simple vegetation and soil characteristics identifiable from aerial photographs. Our results indicate that when inter-basin water exchanges and the distributed effects of topography within each basin are not accounted for, the model performs less well than just assuming average conditions in time or space. However, modelling inter-basin water flow also substantially increases computer run-time. The full model is capable of correctly simulating a broad range of hydrological and soil moisture conditions, providing accurate predictions for areas that range from permanently wet through to permanently dry, as well as for ephemeral wetlands with highly variable water levels. We discuss some potential ecological applications of the model, for example in guiding conservation management. © 2012 Elsevier B.V.

Information on seasonal changes in waterbird numbers in coastal East Africa is limited, but crucial for estimating global flyway populations and targeting conservation efforts. The Sabaki River Mouth is an important site for waterbirds in the region. We counted waterbirds at the site monthly from April 2004 to February 2005. Our counts confirmed the importance of the site for the vulnerable Madagascar Pratincole Glareola ocularis and for Saunders's Tern Sterna saundersi, with 3% and 1%, respectively, of the flyway populations hosted. We detected internationally important (>1% of the biogeographic population) numbers of Curlew Sandpipers Calidris ferruginea. Other species occurred in near-internationally important numbers and, given the high turnover that occurs during migration, it is likely that internationally important numbers of these species used the site. Thus, we highlight the international importance of Sabaki River Mouth as a key stop-over site for waterbirds on the West Asian-East African flyway. We also provide new insights into the presence and abundance of commonly occurring waterbird species, which help to elucidate appropriate conservation policies. © 2012 Copyright NISC (Pty) Ltd.

The coastal forests of East Africa are a hotspot
of avian diversity and endemism, but surveys of the birds associated with coastal forests in southern Tanzania are lacking. In Kilwa District, logging for timber has, and continues to substantially modify the structure of these forests and plans for biofuel. cultivation threaten large tracts of relatively undisturbed forest. At present, no baseline information on the birds present in this region has been collected and the likely impacts of logging and deforestation are poorly understood. The primary purpose of this study was to remedy this situation by providing insight into the habitat associations of species and where possible, map and document the status of species within the region. We document and map the presence of three near-threatened and 11 biome-restricted species and map the presence of the endemic Reichenow’s Batis Batis reichenow. We also document the presence of a previously undiscovered population of Green Barbet Cryptolybia woodwardii. Our results confirm that most species of conservation interest are capable of occupying a range of forest and miombo habitat types, but most were only present in or adjacent to extensive tracts of forest. We thus postulate that habitat loss from biofuels poses a more immediate and greater threat to birds than changes in structure from logging.

1. Overexploited fisheries threaten many species that depend on the exploited resource. Shorebird populations are in decline globally and here we describe how changing shellfishery management and nutrient inputs have had dramatic influence on waterbird communities on an internationally important wetland. 2. Cockle Cerastoderma edule and mussel Mytilus edulis fisheries conflict with shorebirds by removing prey and increasing mortality amongst non-target benthic invertebrates. Under intense dredging pressure, evidence suggests that benthic invertebrates such as worms, with rapid growth and short-generation times, should predominate over species such as bivalves, with slower growth and longer generation times. 3. We investigated the change in the waterbird assemblage in the Wash, eastern England, between 1981-1982 and 2002-2003. This period was characterized by heavy fishing pressure on mussels and cockles, ultimately leading to a crash in the mussel stocks. 4. During the study period, the waterbird assemblage underwent a gradual change from one dominated by those species with a high proportion of bivalves or 'other' prey (e.g. crustaceans, fish) in their diet to those with a higher proportion of worms. This gradual change was punctuated by major shifts, corresponding to three winters when oystercatcher Haemotopus ostralegus mortality was 5-13 times normal winter levels. 5. Oystercatcher, knot Calidris canutus and shelduck Tadorna tadorna showed the highest levels of decline. Since the last major oystercatcher mortality event in 1996-1997, the assemblage has not shifted back to that observed prior to the major crash in the mussel stock in 1992. 6. Changes in the waterbird assemblage were significantly related to mussel and cockle stock levels and, to a lesser extent, nutrient levels. Although correlative, evidence from this study indicates that fisheries caused shifts towards a waterbird community dominated by species with a high proportion of worms in their diet. 7.Synthesis and applications. Mechanical shellfisheries directly conflict with the nature conservation interest of sites holding internationally important waterbird populations. Removal of the mussel beds in the Wash led to major shifts in the waterbird assemblage, with a shift towards worm-feeders. Setting annual quotas that provide sufficient food for shellfish-eating birds is essential to maintain the favourable status of this and other internationally important wetlands where shellfish are exploited.

Detecting coherent signals of climate change is best achieved by conducting expansive, long-term studies. Here, using counts of waders (Charadrii) collected from ca. 3500 sites over 30 years and covering a major portion of western Europe, we present the largest-scale study to show that faunal abundance is influenced by climate in winter. We demonstrate that the 'weighted centroids' of populations of seven species of wader occurring in internationally important numbers have undergone substantial shifts of up to 115km, generally in a northeasterly direction. To our knowledge, this shift is greater than that recorded in any other study, but closer to what would be expected as a result of the spatial distribution of ecological zones. We establish that year-to-year changes in site abundance have been positively correlated with concurrent changes in temperature, but that this relationship is most marked towards the colder extremities of the birds' range, suggesting that shifts have occurred as a result of range expansion and that responses to climate change are temperature dependent. Many attempts to model the future impacts of climate change on the distribution of organisms, assume uniform responses or shifts throughout a species' range or with temperature, but our results suggest that this may not be a valid approach. We propose that, with warming temperatures, hitherto unsuitable sites in northeastern Europe will host increasingly important wader numbers, but that this may not be matched by declines elsewhere within the study area. The need to establish that such changes are occurring is accentuated by the statutory importance of this taxon in the designation of protected areas. © 2008 the Authors Journal compilation © 2008 Blackwell Publishing.

Long-distance migrations are among the wonders of the natural world, but this multitaxon review shows that the characteristics of species that undertake such movements appear to make them particularly vulnerable to detrimental impacts of climate change. Migrants are key components of biological systems in high latitude regions, where the speed and magnitude of climate change impacts are greatest. They also rely on highly productive seasonal habitats, including wetlands and ocean upwellings that, with climate change, may become less food-rich and predictable in space and time. While migrants are adapted to adjust their behaviour with annual changes in the weather, the decoupling of climatic variables between geographically separate breeding and nonbreeding grounds is beginning to result in mistimed migration. Furthermore, human land-use and activity patterns will constrain the ability of many species to modify their migratory routes and may increase the stress induced by climate change. Adapting conservation strategies for migrants in the light of climate change will require substantial shifts in site designation policies, flexibility of management strategies and the integration of forward planning for both people and wildlife. While adaptation to changes may be feasible for some terrestrial systems, wildlife in the marine ecosystem may be more dependent on the degree of climate change mitigation that is achievable

Throughout the world, but particularly in tropical regions habitat loss and disturbance are considered detrimental to biodiversity. We examine the effects of disturbance by harvesting, burning and habitat fragmentation on six bird species associated with papyrus (Cyperus papyrus) swamps. The presence or absence of these species was verified in 93 wetlands in southern Uganda between June and August 2003. Disturbance was estimated directly by observation and indirectly from examining vegetation structure. Habitat fragmentation was quantified by delineating swamps on Landsat ETM images and applying 'Fragstats' to calculate relevant patch metrics. The occurrence of all six species was affected positively by increased swamp size, but birds were more likely to occur in small swamps at high altitude. The shape and proximity of swamps to neighbouring wetlands had little effect on occurrence. As altitude, habitat fragmentation and disturbance were correlated, determining avian responses to disturbance was problematic. However, the occurrence of all species was affected by disturbance, often showing unimodal responses, if disturbance was not considered in conjunction with habitat fragmentation. When the effects of habitat fragmentation and disturbance were analysed together, only the occurrences of papyrus yellow warbler and white-winged warbler were affected (positively) by disturbance. Results suggest that papyrus-dwelling passerines, except papyrus gonolek, are tolerant of low intensities of disturbance, a novel finding in the tropics. We recommend that policy-makers do not prohibit harvesting, thus generating good will and encouraging rural householders to comply with additional conservation policy. © 2005 Elsevier Ltd. All rights reserved.

To manage and conserve wildlife populations effectively it is necessary to use methods that identify the often non-linear trends in populations, have an inbuilt assessment of trend quality and can analyse count data from a range of spatial scales. We present a method of trend analysis using generalised additive models. These produce smoothed indices of abundance that can be used to assess population change from one or more sites or time periods, with any number of estimates of abundance per index period. We apply this method to count data collected under the Wetland Bird Survey, a national scheme that monitors waterbirds in the United Kingdom. To highlight declining populations, ‘alerts’ were raised if the population decline was equal to or greater than 50%. Significance was determined using bootstrapped confidence intervals for analyses that included many sites, or a novel Monte-Carlo method for single site analyses. The impact of missing data, species count variability and the number of months used to calculate the population change was greater at individual sites than for national datasets, which were relatively insensitive to changes in the above parameters. For single sites it is essential that three or more counts be made per index period if reliable estimates of population change are required. We propose that the method presented could be applied to a wide range of national or other monitoring schemes for a variety of taxa

Despite the importance of Ugandan wetlands in sustaining rural livelihoods, widespread drainage and habitat degradation has occurred. In this paper, we examine the important factors contributing to unsustainable levels of resource use and habitat destruction around Lake Bunyonyi in southwest Uganda. The results indicate that, despite apprehension about a lack of awareness of the hidden costs of wetland drainage amongst rural householders, information failure contributes little to misuse of swamp resources in swamps fringing Lake Bunyonyi. Instead, wetlands are degraded because the benefits of sustainable use are often not accrued by those that incur the costs of misuse. High population densities and resulting land pressures have led to considerable translocation of rural householders, which has contributed to breakdown of collaborative management. Previously, many swamps were considered to be under common ownership and individuals co-operated, but recently property rights structures have shifted to open access where individuals pursue selfish strategies. Our results also suggest that private ownership would discriminate against the poorest sectors of society. Analysis of Lorenz curves suggest swamp products (papyrus and fish) result in a reduction of income inequality within the local economy. Similarly an improvement in the Gini Coefficient from 0.137 to 0.356 is observed if the contribution of swamp goods to household incomes is included in analyses. The role of swamp products (papyrus, fish and crops grown in the swamp) in smoothing annual fluctuations in income, and reducing the mismatch between, income and expenditure are examined. This is particularly important given the timing of papyrus harvests in relation to when school fees are paid and the absence of credit facilities. The implications and relevance of these results to policy makers are discussed.

Wetlands in Uganda have undergone considerable decline over the last thirty years as a result of clearance for agriculture and over-use of wetland resources. In this paper we examine the effects of papyrus harvesting and swamp reclamation on the net present value of papyrus swamps fringing Lake Bunyonyi in southwest Uganda. The value of harvested papyrus, crops and fish obtained from the swamp was modelled in relation to swamp area, using a production function approach. Parameter values were estimated from interview data. Results indicated that the net present value of swamps was maximised when between 27-33% of the swamp is utilised for harvesting, but when optimal cultivation levels were less than 2%. These findings lend support to the premise that conserving biodiversity has an economic basis. Assuming a 5% discount rate, the maximum net present value of goods derived from the swamps were estimated at between US$11.2 thousand ha-1 and US$24.0 thousand ha-1, depending on the method used to measure value. Relative to potential global benefits of papyrus ecosystems through, for example, carbon sequestration, these values are relatively small. Potential conflicts between the interests of local people and the international community are therefore discussed. The optimal ratio of harvesting, cultivation and conservation is comparatively robust to most model parameter estimates. However, a reduction in wages or the perceived value of people's time, leads to a large increase in optimal levels of harvesting and cultivation, trapping people into a vicious circle of poverty. These results are discussed in relation to wetland policy in Uganda.