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Broad-scale spatial patterns of species richness are very strongly correlated with climatic variables. If there is a causal link, i.e. if climate directly or indirectly determines patterns of richness, then when the climatic variables change, richness should change in the manner that spatial correlations between richness and climate would predict. The present study tests this prediction using seasonal changes in climatic variables and bird richness. We used a grid of equal area quadrats (37 000 km2) covering North and Central America as far south as Nicaragua. Summer and winter bird distribution data were drawn from monographs and field guides. Climatic data came from published sources. We also used remotely sensed NDVI (normalized difference vegetation index — a measure of greenness). Bird species richness changes temporally (between summer and winter) in a manner that is close to, but statistically distinguishable from, the change one would predict from models relating the spatial variation in richness at a single time to climatic variables. If one further takes into account the seasonal changes in NDVI and within-season variability of temperature and precipitation, then winter and summer richness follow congruent, statistically indistinguishable patterns. Our results are consistent with the hypothesis that climatic variables (temperature and precipitation) and vegetation cover directly or indirectly influence patterns of bird species richness. [ABSTRACT FROM AUTHOR]

Aim The increased incidence of large fires around much of the world in recent decades raises questions about human and non-human drivers of fire and the likelihood of increased fire activity in the future. The purpose of this paper is to outline a conceptual framework for examining where human-set fires and feedbacks are likely to be most pronounced in temperate forests world-wide and to establish and test a methodology for evaluating this framework using palaeoecological records. Location Tasmania, north-western USA, southern South America and New Zealand. Methods We outline a conceptual framework for predicting the sensitivity of ecosystems to human impacts on fire regimes and then use a circum- Pacific comparison of existing historical reconstructions of fire, climate, human settlement and vegetation to evaluate this approach. Results Previous research investigating important controls on fire activity shows that the sensitivity of temperate ecosystems to human-set fires is modulated by the frequency of natural fire occurrence, fuel moisture and fuel type and availability. Palaeoecological data from four temperate regions suggest that the effects of anthropogenic burning are greatest where fire is naturally rare, vegetation is poorly adapted to fire and fuel biomass is abundant and contiguous. Alternatively, where fire activity is naturally high and vegetation is well adapted to fire, evidence of human influence on fire and vegetation is less obvious. Main conclusions Palaeofire records suggest that the most dynamic and persistent ecosystem transitions occur where human activities increase landscape flammability through fire-vegetation feedbacks. Rapid forest transitions in biomass-rich ecosystems such as New Zealand and areas of Tasmania and southern South America illustrate how landscapes experiencing few fires can shift past tipping points to become fire-prone landscapes with new alternative stable state communities. Comparisons of palaeoecological data from different regions with similar biophysical gradients but different human settlement histories can provide new opportunities for understanding ecosystem vulnerability to fire-climate-human interactions. [ABSTRACT FROM AUTHOR]

Aim Climate change has the potential to have an impact on the distribution of ticks and tick-borne diseases. This paper identifies the changes in climate suitability for the tick Rhipicephalus (Boophilus) microplus in the Americas by analysing climate data for the period 1950–99. Location The model was applied to the American continent. Methods A model based on Environmental Niche Modelling was used on a gridded (0.5°) long-term (1950–99) climate data set. A map of the core range of the species was constructed, and areas where habitat suitability (HS) changes suddenly over short time periods were identified as regions of high sensitivity. Tendency of climate in the continent was evaluated and scenarios constructed for 2025 and 2050. Results Regions of high sensitivity included the southern USA, Mexico and western and central Argentina. Analysis of climate variables in these regions identified water vapour pressure deficit and evaporation as underlying the high sensitivity of habitat suitability in the USA and Mexico, and showed that episodes of high variability are linked to the El Niño Southern Oscillation. Projections of the tendency of HS as observed for the 1950–99 period point to an increase in this value in parts of the southern USA and in central Argentina, a finding that can be attributed to the progressive increase in minimum and yearly averaged temperatures. Conclusions Short-term changes in climate may drive the system into unstable situations with sudden changes in habitat suitability for the target tick in specific zones of the Americas. Results suggest an increased abiotic (climate) suitability for R. microplus in areas whose habitat is currently unsuitable for this species. [ABSTRACT FROM AUTHOR]

Aim: Given the influence of seasonality on most ecological systems, an emerging research area attempts to understand how community network structure is shaped by seasonal climatic variations. To do so, most researchers conduct their analyses using open networks due to the high cost associated with constructing their own community networks. However, unwanted structural differences from the unique sampling and construction methods used to create each open network likely make comparing these networks a difficult task. Here, with the largest set of open bipartite networks collected to date, we test whether seasonal climatic variations explain network structure while additionally accounting for construction/sampling differences between networks. Location: Trying to approach global. Time period: Contemporary. Major taxa studied: Plants and animals. Methods: Using 723 open bipartite networks, we test whether temperature and/or precipitation seasonality explains (un)weighted metrics of nestedness, modularity or specialization across plant–pollinator, seed‐dispersal, plant–ant, host–parasite or plant–herbivore systems. Results: Generally, seasonality only weakly explained network structure: at most 16% of the variation in weighted metrics and 5% of the variation in unweighted metrics. Instead, a control for sampling bias in networks, sampling intensity, often better explained many of the network structural metrics. When limiting our analyses to only intensely sampled networks, however, about 33% of the variation in weighted modularity and specialization was explained by seasonality, but only in plant–pollinator networks. Main conclusions: Altogether, we do not find strong evidence that seasonality explains network structure. Our study also highlights the large amount of structural differences in open networks, likely from the many different sampling and network construction techniques adopted by researchers when constructing networks. Hence, a definitive test for the relationship between network structure and seasonality across large spatial extents will require a dataset free from sampling and other biases, where networks are derived from a consistent sampling protocol that appropriately characterizes communities. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim The network structure of food webs plays an important role in the maintenance of diversity and ecosystem functioning in ecological communities. Previous research has found that ecosystem size, resource availability, assembly history and biotic interactions can potentially drive food web structure. However, the relative influence of climatic variables that drive broad-scale biogeographic patterns of species richness and composition has not been explored for food web structure. In this study, we assess the influence of broad-scale climatic variables in addition to known drivers of food web structure on replicate observations of a single aquatic food web, sampled from the leaves of the pitcher plant ( Sarracenia purpurea), at different geographic sites across a broad latitudinal and climatic range. Location Using standardized sampling methods, we conducted an extensive 'snapshot' survey of 780 replicated aquatic food webs collected from the leaves of the pitcher plant S. purpurea at 39 sites from northern Florida to Newfoundland and westward to eastern British Columbia. Methods We examined correlations of 15 measures of food web structure at the pitcher and site scales with geographic variation in temperature and precipitation, concentrations of nutrients from atmospheric nitrogen deposition, resource availability, ecosystem size and the abundance of the pitcher plant mosquito ( Wyeomyia smithii), a potential keystone species. Results At the scale of a single pitcher plant leaf, linkage density, species richness, measures of chain length and the proportion of omnivores in a web all increased with pitcher volume. Linkage density and species richness were greater at high-latitude sites, which experience low mean temperatures and precipitation and high annual variation in both of these variables. At the site scale, variation in 8 of the 15 food web metrics decreased at higher latitudes, and variation in measures of chain length increased with the abundance of mosquitoes. Main conclusions Ecosystem size and climatic variables related to latitude were most strongly correlated with network structure of the Sarracenia food web. However, in spite of large sample sizes, thorough standardized sampling and the large geographic extent of the survey, even the best-fitting models explained less than 40% of the variation in food web structure. In contrast to biogeographic patterns of species richness, food web structure was largely independent of broad-scale climatic variables. The large proportion of unexplained variance in our analyses suggests that stochastic assembly may be an important determinant of local food web structure. [ABSTRACT FROM AUTHOR]

Aim: Climatic variation has long been regarded as a primary source of morphological variation. However, there is mixed support for the adherence of reptiles to ecogeographical hypotheses, such as Bergmann's rule (body size decreases with temperature) and Allen's rule (limb length increases with temperature). We quantified body and limb morphology among the diverse Australian gecko fauna (4 families, 30 genera, 226 of the 231 described species) to investigate environmental correlates of morphological variation in this radiation. Location: Australia. Major taxa studied: Geckos (Squamata: Gekkota; the families Gekkonidae, Carphodactylidae, Diplodactylidae and Pygopodidae). Methods: We measured 20 external features of ethanol‐preserved museum specimens. We investigated whether principal component axes of morphology were correlated with three key environmental variables, and the microhabitat occupied by each species. Results: Morphology varied greatly among Australian gecko families and genera, although there was a strong phylogenetic signal in morphology. After accounting for phylogeny, morphology was correlated with a species' microhabitat use. Saxicolous species and species with variable microhabitat requirements (i.e., generalists) had larger body dimensions than terrestrial species. Saxicolous species also had longer proportional forelimbs and hindlimbs than terrestrial species. Main conclusions: Our results highlight the importance of phylogeny and microhabitat use in shaping the morphology of Australian geckos. We find little evidence that Australian geckos adhere to Bergmann's rule or Allen's rule, suggesting that these ecogeographical hypotheses provide limited insight into the adaptive potential of lizard species to altered environmental conditions. [ABSTRACT FROM AUTHOR]

Aim: Knowledge of the drivers of ecosystem changes in the past is key to understanding present ecosystem responses to changes in climate, fire regimes and anthropogenic impacts. Northern Hemisphere‐focussed studies suggest that climate and human activities drove turnover during the Holocene in temperate ecosystems. Various drivers have been invoked to explain changes in Southern Hemisphere temperate vegetation, but the region lacks a quantitative assessment of these drivers. To better understand the regional drivers of past diversity, we present a quantitative meta‐analysis study of turnover and richness during the lateglacial and Holocene in Australian temperate ecosystems. Location: South‐east Australia (Tasmania, Bass Strait, SE mainland). Methods: We conducted a meta‐analysis study of 24 fossil pollen records across south‐east Australian temperate ecosystems, applying an empirical turnover threshold to fossil records to identify periods of major turnover for the first time in Australia. We tested pollen richness as a proxy for vegetation richness to estimate past richness and applied this to fossil pollen data. The resulting reconstructions were compared to independent records of climate, sea‐level change and fire through generalized linear modelling. Results and conclusion: Our results show changes in available moisture and sea level drove turnover and richness in most parts of SE Australia in the past, explaining up to c. 97% deviance. However, fire mainly drove turnover in Bass Strait. Our richness reconstructions also support the intermediate disturbance hypothesis, suggesting that high biodiversity was partially maintained by anthropogenic‐managed fire regimes. While temperature change is considered key to Northern Hemisphere palaeodiversity, past turnover and richness in Southern Hemisphere temperate ecosystems responded mainly to moisture availability and sea‐level change (considering its role in modulating regional oceanic climate). [ABSTRACT FROM AUTHOR]

Aim The aim was to assess the sensitivity of butterfly population dynamics to variation in weather conditions across their geographical ranges, relative to sensitivity to density dependence, and determine whether sensitivity is greater towards latitudinal range margins. Location Europe. Time period 1980-2014. Major taxa studied Butterflies. Methods We use long-term (35 years) butterfly monitoring data from > 900 sites, ranging from Finland to Spain, grouping sites into 2° latitudinal bands. For 12 univoltine butterfly species with sufficient data from at least four bands, we construct population growth rate models that include density dependence, temperature and precipitation during distinct life-cycle periods, defined to accommodate regional variation in phenology. We use partial R2 values as indicators of butterfly population dynamics' sensitivity to weather and density dependence, and assess how these vary with latitudinal position within a species' distribution. Results Population growth rates appear uniformly sensitive to density dependence across species' geographical distributions, and sensitivity to density dependence is typically greater than sensitivity to weather. Sensitivity to weather is greatest towards range edges, with symmetry in northern and southern parts of the range. This pattern is not driven by variation in the magnitude of weather variability across the range, topographic heterogeneity, latitudinal range extent or phylogeny. Significant weather variables in population growth rate models appear evenly distributed across the life cycle and across temperature and precipitation, with substantial intraspecific variation across the geographical ranges in the associations between population dynamics and specific weather variables. Main conclusions Range-edge populations appear more sensitive to changes in weather than those nearer the centre of species' distributions, but density dependence does not exhibit this pattern. Precipitation is as important as temperature in driving butterfly population dynamics. Intraspecific variation in the form and strength of sensitivity to weather suggests that there may be important geographical variation in populations' responses to climate change. [ABSTRACT FROM AUTHOR]

Aim Global biomes are often classified by mean annual temperature and precipitation, but there is significant overlap between biomes, making it difficult to interpret the role of climate in the distribution of biomes globally. Climate predictability (including long-term reliability of both seasonality and inter-annual variability) varies considerably between biomes and regulates biodiversity distribution, adaptation and evolution, but its global pattern has rarely been investigated. The aim of this study was to characterize climatic space quantitatively for major biomes of the world using temperature and precipitation predictability, and to interpret its biological implications under future climate change. Location Global. Time Period 1901-2012. Methods We calculated global gridded temperature and precipitation predictability based on an information theory approach, and compared climatic spaces defined by these measures within and across biomes. Results We show that temperature predictability has a clear latitudinal gradient, whereas precipitation predictability is geographically variable. We further show that temperature and precipitation predictability form distinct climatic spaces for major biomes across the globe, and importantly, temperature and precipitation predictability can robustly distinguish biomes that are overlapping in mean annual climate statistics. Main conclusions Climatic space created by temperature and precipitation predictability supplements the traditional biome-specific climatic spaces created by annual mean temperature and total precipitation. Quantifying measures of climate predictability helps us to understand adaptation strategies adopted by local organisms within and across biomes. Our results show that quantifying climate predictability is a simple and effective way to delineate more robustly biome climate space and its influences on macroecology and evolutionary biology, which in turn could underpin conservation efforts under future climate change, especially when prevailing climates are comparable in terms of magnitude. [ABSTRACT FROM AUTHOR]

Aim Theoretical and empirical studies have shown that climate is a major determinant of species richness, yet the importance of climate relative to local site conditions remains unclear in forest ecosystems across large regions. Furthermore, little is known about how climate and local site conditions affect species evenness and understorey plant diversity. Location Canadian forest (42°37′ to 68°14′ N; 53°25′ to 134°46′ W; 4 to 2170 m elevation). Methods Using national, broad-scale forest inventory data, we tested the influence of growing degree days ( GDD), climate moisture index ( CMI), soil drainage class ( SDC) and stand age ( SA) on plant diversity across Canada's forests. Diversity was assessed on variable plot sizes from 125 to 500 m2 for canopy tree and total plant species, and from 100 to 400 m2 for understorey plants. Results Our models accounted for 47, 30 and 49% of total variation in canopy tree species richness, Simpson's dominance index and total plant species richness, respectively. After accounting for the effects of plot size and management history, canopy richness increased with GDD and CMI and peaked at intermediate SDC and SA. Simpson's dominance index decreased with increasing GDD and CMI and was lowest at intermediate SDC and SA. Total species richness was most strongly related to SDC and was highest on imperfectly drained soils. Climatic controls on species richness of understorey strata were generally weaker than those on canopy richness. Main conclusions Our results for canopy richness along a mainly longitudinal gradient demonstrate the positive effects of energy on tree species diversity and show evidence for the effects of local site conditions and secondary succession on diversity. Furthermore, our results show that the extent of the influence of climate and local site conditions on plant species diversity can strongly differ between vegetation strata. [ABSTRACT FROM AUTHOR]

Aim Large trees (d.b.h. ≥ 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location Pan-tropical. Methods Aboveground biomass ( AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights ( AICc-wi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) ± 105.0 ( SD) Mg ha−1] versus Palaeotropical forests (Africa 418.3 ± 91.8 Mg ha−1; Asia 393.3 ± 109.3 Mg ha−1). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees. [ABSTRACT FROM AUTHOR]

Aim Our aims were: (1) to separately evaluate the elevational patterns of β-diversity for nestedness, species richness difference and replacement, (2) to identify the drivers of β-diversity patterns by testing the effect of geographical and environmental distance (human population, temperature and land-use), and (3) to compare the response on native versus alien species to elucidate mechanisms of community assembly along elevational gradients. Location Two mountain regions ( Bergamo- Brescia and Trento) in the Italian Alps. Methods We used two floristic datasets in which species composition was sampled within two regular grids. First, we extracted species elevational range and quantified species composition nestedness along the elevational gradient. Second, we partitioned β-diversity into its species richness difference and replacement components and tested drivers using regression on distance matrix and hierarchical partitioning. All analyses were performed on natives and aliens, separately. Results For aliens, we found lack of mountain specialists (i.e. species with a distribution range restricted to high elevations), large nestedness, large species richness difference and low species replacement between low and high elevations. All findings point in the same direction: a great majority of alien species were introduced to the lowlands and only a subset of this community spread up the mountains. Both human pressures and temperature selection were important processes underpinning the observed filtering, while geographical and land-use distances were not important. Natives present contrasting patterns with large replacement along the elevation gradients indicating different mechanisms of community assembly. Main conclusions The relatively large alien species replacement in the lowlands indicated the presence of a pool of species that may potentially invade the temperate mountains in the future. Investigations of the identity of alien species occurring in the lowlands and their climatic pre-adaptation might provide tools to prevent invasions in the mountains by predicting the potential invaders and their future elevational distribution. [ABSTRACT FROM AUTHOR]

Aim Concern about climate change, with the subsequent emergence of carbon markets and policy initiatives such as REDD (reducing carbon emissions by decreasing deforestation and forest degradation), have focused attention on assessing and monitoring terrestrial carbon reserves. Most effort has focused on above-ground forest biomass. Soil has received less attention despite containing more carbon than above-ground terrestrial biomass and the atmosphere combined. Our aim was to explore how well soil carbon concentration could be estimated on three continents from existing climate, topography and vegetation-cover data. Location Peru, Brazil, Argentina, Australia, China. Methods Soil carbon concentration and leaf area index ( LAI) as well as GIS-derived climate and topography variables for 65 temperate and 43 tropical, forest and woodland ecosystems, were either directly measured or estimated from freely available global datasets. We then used multiple regressions to determine how well soil carbon concentration could be predicted from LAI, climate and topography at a given site. We compared our measurements with top soil carbon estimates from the Food and Agriculture Organization of the United Nations ( FAO) harmonized world soil map. Results Our empirical model based on estimates of temperature, water availability and plant productivity provided a good estimate of soil carbon concentrations ( R2 = 0.79). In contrast, the values of topsoil carbon concentrations from the FAO harmonized world soil map correlated poorly with the measured values of soil carbon concentration ( R2 = 0.0011). Main conclusions The lack of correlation between the measured values of soil carbon and the values from the FAO harmonized world soil map indicate that substantial improvements in the production of soil carbon maps are needed and possible. Our results demonstrate that the inclusion of freely available GIS data offers improved estimates of soil carbon and will allow the creation of more accurate soil carbon maps. [ABSTRACT FROM AUTHOR]

Aim Climatic niche breadth (the range of climatic conditions that a species experiences over space and time) is a fundamental topic in ecology, biogeography and evolution. But what determines the climatic niche width of species? In 1967, Janzen suggested that climatic niche widths for temperature were determined by levels of seasonal fluctuation in temperature at each locality, such that niche breadths are narrow in tropical species and broad in temperate species. However, it is unclear whether climatic niche breadths of species are determined more by seasonal variability within sites as opposed to climatic variation between sites across the species' range. We address this question here. Location Global. Methods We analysed three vertebrate clades (plethodontid salamanders, hylid frogs and phrynosomatid lizards) for which we had phylogenetic information and climatic data from localities throughout each species' geographic range, collectively including 409 species. We tested how climatic niche breadths of localities (i.e. temporal variation) are related to overall species climatic niche breadths (i.e. temporal and spatial variation) using phylogenetic comparative methods, focusing both on temperature extremes and precipitation. Results Across the three clades, we find that niche breadths for single localities generally span most of the species' climatic niche breadth, and are strongly correlated with overall species niche breadths. However, species with wider climatic niches also tend to show greater climatic divergence between localities. Main conclusions The extent to which the climatic niche breadths of species are determined by variation within localities versus spatial variation between localities has been largely unexplored. Our results suggest that within-locality seasonal variation explains most variation in climatic niche breadths among species. However, between-locality variation and local adaptation may also play some role. These results require more general testing, but have several important implications. [ABSTRACT FROM AUTHOR]

Aim To compare the geographical distributions of two tick-borne pathogens vectored by different tick species, to examine the relative importance of climate, land cover and host density in structuring these distributions, and to assess the spatial variability of these environmental constraints across the species ranges. Location South-central and south-eastern North America. Methods Presence/absence data for two tick-borne pathogens, Ehrlichia chaffeensis and Anaplasma phagocytophilum, were obtained for 567 counties from a regional data base based on white-tailed deer ( Odocoileus virginianus) serology. Environmental variables describing climate, land cover and deer density were calculated for these counties. Global logistic regression analysis was used to screen the environmental variables and select a parsimonious subset of predictors. Local analysis was carried out using geographically weighted regression (GWR) to explore spatial variability in the parameters of the regression models. Cluster analysis was applied to the GWR output to identify zones with distinctive species–habitat relationships. Results Global habitat models for E. chaffeensis and A. phagocytophilum included temperature, humidity, precipitation and forest cover as explanatory variables. The E. chaffeensis model also included forest fragmentation, whereas the A. phagocytophilum model included deer density. Local analyses revealed that climate was the primary correlate of pathogen presence in the eastern portion of the study area, whereas forest cover and fragmentation constrained the western range boundaries. Habitat relationships for all variables were weak in and around the Mississippi Delta. Main conclusions Efforts to model pathogen and disease ranges, and to predict shifts in response to global change should consider future scenarios of land-cover change as well as climate change, and should address the possibility of spatial heterogeneity in species–habitat relationships. The methods presented here outline an approach for objectively delineating geographical zones with similar species–environment relationships, which can then be used to stratify landscapes for the purposes of further explanatory and predictive modelling. [ABSTRACT FROM AUTHOR]

Aim To determine the relationship between the distribution of climate, climatic heterogeneity and pteridophyte species richness gradients in Australia, using an approach that does not assume potential relationships are spatially invariant and allows for scale effects (extent of analysis) to be explicitly examined. Location Australia, extending from 10° S to 43° S and 112° E to 153° E. Method Species richness within 50 × 50 km grid cells was determined using point distribution data. Climatic surfaces representing the distribution and availability of water and energy at 1 km and 5 km cell resolutions were obtained. Climate at the 50 km resolution of analysis was represented by their mean and standard deviation in that area. Relationships were assessed using geographically weighted linear regression at a range of spatial bandwidths to investigate scale effects. Results The parameters and the predictive strength of all models varied across space at all extents of analysis. Overall, climatic variables representing water availability were more highly correlated to pteridophyte richness gradients in Australia than those representing energy. Their variance in cells further increased the strength of the relationships in topographically heterogeneous regions. Relationships with water were strong across all extents of analysis, particularly in the tropical and subtropical parts of the continent. Water availability explained less of the variation in richness at higher latitudes. Main conclusions This study brings into question the ability of aspatial and single-extent models, searching for a unified explanation of macro-scaled patterns in gradients of diversity, to adequately represent reality. It showed that, across Australia, there is a positive relationship between pteridophyte species richness and water availability but the strength and nature of the relationship varies spatially with scale in a highly complex manner. The spatial variance, or actual complexity, in these relationships could not have been demonstrated had a traditional aspatial global regression approach been used. Regional scale variation in relationships may be at least as important as more general relationships for a true understanding of the distribution of broad-scale diversity. [ABSTRACT FROM AUTHOR]

Aims To describe the pattern of mean body size of native mammals in Europe, and to investigate its relationships with environmental predictors related to four hypotheses: (1) dispersal; (2) heat conservation; (3) heat dissipation; and (4) resource availability. Location Continental western Europe and Great Britain. Methods We used range maps to estimate the mean body size (average log mass) of mammals in 386 cells of 12,100 km2 each. Environmental conditions in each cell were quantified using nine historical, climatic and primary production variables. We attempted to tease apart the effects of these variables using correlation, multiple regression and spatial autocorrelation analyses. Results In the part of the continent covered by ice during the Pleistocene, body mass decreases southwards, and annual average temperature explains 73% of the variance in body size, consistent with the heat-conservation hypothesis. However, in warmer, non-glaciated areas the best predictor is an estimate of seasonality in plant production, but it explains only 18% of the variance. Carnivores, omnivores and herbivores show similar relationships, but the pattern for herbivores is substantially weaker than for the other groups. Main conclusions Overall, the relationship between mean body size and temperature is non-linear, being strong in cold environments but virtually disappearing above a temperature threshold. [ABSTRACT FROM AUTHOR]

Aim To produce a statistical stratification of the European environment, suitable for stratified random sampling of ecological resources, the selection of sites for representative studies across the continent, and to provide strata for modelling exercises and reporting. Location A ‘Greater European Window’ with the following boundaries: 11° W, 32° E, 34° N, 72° N. Methods Twenty of the most relevant available environmental variables were selected, based on experience from previous studies. Principal components analysis (PCA) was used to explain 88% of the variation into three dimensions, which were subsequently clustered using an ISODATA clustering routine. The mean first principal component values of the classification variables were used to aggregate the strata into Environmental Zones and to provide a basis for consistent nomenclature. Results The Environmental Stratification of Europe (EnS) consists of 84 strata, which have been aggregated into 13 Environmental Zones. The stratification has a 1 km2 resolution. Aggregations of the strata have been compared to other European classifications using the Kappa statistic, and show ‘good’ comparisons. The individual strata have been described using data from available environmental databases. The EnS is available for noncommercial use by applying to the corresponding author. Main conclusions The Environmental Stratification of Europe has been constructed using tried and tested statistical procedures. It forms an appropriate stratification for stratified random sampling of ecological resources, the selection of sites for representative studies across the continent and for the provision of strata for modelling exercises and reporting at the European scale. [ABSTRACT FROM AUTHOR]

Abstract To model the effects of global climate phenomena on avian population dynamics, we must identify and quantify the spatial and temporal relationships between climate, weather and bird populations. Previous studies show that in Europe, the North Atlantic Oscillation (NAO) influences winter and spring weather that in turn affects resident and migratory landbird species. Similarly, in North America, the El Niño/Southern Oscillation (ENSO) of the Pacific Ocean reportedly drives weather patterns that affect prey availability and population dynamics of landbird species which winter in the Caribbean. Here we show that ENSO- and NAO-induced seasonal weather conditions differentially affect neotropical- and temperate-wintering landbird species that breed in Pacific North-west forests of North America. For neotropical species wintering in western Mexico, El Niño conditions correlate with cooler, wetter conditions prior to spring migration, and with high reproductive success the following summer. For temperate wintering species, springtime NAO indices correlate strongly with levels of forest defoliation by the larvae of two moth species and also with annual reproductive success, especially among species known to prey upon those larvae. Generalized linear models incorporating NAO indices and ENSO precipitation indices explain 50–90% of the annual variation in productivity reported for 10 landbird species. These results represent an important step towards spatially explicit modelling of avian population dynamics at regional scales. [ABSTRACT FROM AUTHOR]