The climate envelope may not be empty

ABSTRACTAim Recently, a flurry of studies have focused on the extent to which geographical patterns of diversity fit mid‐domain effect (MDE) null models. While some studies find strong support for MDE null models, others find little. We test two hypotheses that might explain this variation among studies: small‐ranged groups of species are less likely than large‐ranged species to show mid‐domain peaks in species richness, and mid‐domain null model predictions are less robust for smaller spatial extents than for larger spatial extents.Location We analyse data sets from elevational, riverine, continental and other domains from around the world.Methods We use a combination of Spearman rank correlations and binomial tests to examine whether differences within and among studies and domains in the predictive power of MDE null models vary with spatial scale and range size.Results Small‐ranged groups of species are less likely to fit mid‐domain predictions than large‐ranged groups of species. At large spatial extents, diversity patterns of taxonomic groups with large mean range sizes fit MDE null model predictions better than did diversity patterns of groups with small mean range sizes. MDE predictions were more explanatory at larger spatial extents than at smaller extents. Diversity patterns at smaller spatial extents fit MDE predictions poorly across all range sizes. Thus, MDE predictions should be expected to explain patterns of species richness when ranges and the scale of analysis are both large.Main conclusions Taken together, the support for these hypotheses offers a more sophisticated model of when MDE predictions should be expected to explain patterns of species richness, namely when ranges and the scale of analysis are both large. Thus the circumstances in which the MDE is important are finite and apparently predictable.

When a scientist performs a statistical hypothesis test, there are three steps to consider. The first is computing a statistic from data, the second is finding or estimating the probability distribution of that statistic under the null hypothesis, and the third is comparing the computed statistic to its null distribution, resulting in a p-value. In the field of microbial ecology, various statistics are used in inferring networks of interactions between microbes from time series data, such as correlation between time series, estimated coefficients when the data is fitted to a generalized Lotka-Volterra model, and local similarity. However, there has been little discussion of different methods of finding a null distribution of these statistics, and often these null distributions are found in an ad-hoc and undefended way. We assess different commonly used statistics in combination with different methods of estimating null distributions to infer causal relationships between simulated microbes in time series data. We estimate null distributions in two ways. The first is by generating surrogate time series data, which preserves most statistical properties of our data while adhering to the null model. Since there are many methods of generating surrogate data, and they all come with different assumptions about the original data, we have chosen to test multiple surrogate data types with different statistics. The second null distribution estimation method we benchmark is a parametric test that is paired with the Pearson correlation statistic and produces a null distribution with the data's estimated effective degrees of freedom, thus accounting for autocorrelation. We show that our choice of null distribution estimation method can be used to minimize false positives, while choice of statistic affects the test's statistical power. As such, both pieces of the statistical test ought to be considered.

Forest bird abundance in Europe has remained stable overall, unlike farmland species which have declined dramatically in recent decades. However, this apparent stability may hide large variations among species and geographical regions. We aimed to determine if forest bird species with varying life histories and biome distributions show different population trends. We used functional traits and specialisation indices to study changes in abundance and distribution of European forest bird populations. For each species, we used European‐level estimates of total abundance change over the last 40 years and changes in two components of spatial distribution: range change (i.e. area shrinkage or expansion) and distribution shift (i.e. latitudinal adjustments), both over the last 30 years. We also considered specialist groups of different biomes (i.e. boreal, temperate, Mediterranean and biome generalists) separately. We showed that boreal forest species have declined in abundance and range area, while Mediterranean and temperate species have increased in abundance and range, possibly as the result of warmer temperatures and forest expansion in these regions. The decline of boreal forest species may result from changes in forest structure and composition due to forestry practices, increasing temperatures and colonisation by warm‐dwelling species. Among boreal species, mixed forest specialists (i.e. those preferring a mix of broadleaf and coniferous trees) declined the most in abundance and range and shifted northwards. In contrast, for vertebrate carnivores (i.e. birds of prey), we observed an increase in abundance among Mediterranean species and a southward expansion among all species. Our findings suggest that forest bird species in Europe may be influenced by the combined effects of land use and climate change, with these impacts varying across biomes. Our results highlight the need for maintaining and restoring key forest habitats (e.g. through increased protected areas and extensive management) and halting or limiting climate change, especially for boreal species.

Antimicrobial resistance profiles of Escherichia coli from common European wild bird species

In a recent article (Colwell et al. 2004; hereafter CRG), we reviewed all studies of the mid-domain effect (MDE) published up to that time and responded to earlier critiques of MDE by (among others) Hawkins and Diniz-Filho (2002) and Zapata et al. (2003). The discussion continues here with comments on our article by Hawkins, DinizFilho, and Weiss (2005; hereafter HDW) and by Zapata, Gaston, and Chown (2005; hereafter ZGC). In this article, we respond to HDW and ZGC. Null models and null hypotheses. ZGC defend their view of MDE models as null hypotheses subject to falsification. In contrast, proponents of MDE theory have always held that richness patterns have multiple causes. For example, referring to the effect of geometric (boundary) constraints on geographic patterns of species richness, Colwell and Lees (2000, p. 79) stated that “the question is not whether geometry affects such patterns, but by how much.” We view any assessment of the role of geometric constraints as a problem of estimating the magnitude of the contribution (if any) of MDE to richness patterns (“how much”). Just as with other candidate causes of richness patterns (e.g., climatic, topographic, or historical drivers), the appropriate null hypothesis (if any) is that MDE makes no contribution to richness patterns, not that MDE uniquely and fully accounts for richness patterns. It is for this reason that we distinguish between MDE as a model and the hypotheses that can be framed regarding its predictions.

Genetic diversity within species may promote resilience to environmental change, yet little is known about how such variation is distributed at broad geographic scales. Here we develop a novel Bayesian methodology to analyse multi-species genetic diversity data in order to identify regions of high or low genetic diversity. We apply this method to co-distributed taxa from Australian marine waters. We extracted published summary statistics of population genetic diversity from 118 studies of 101 species and > 1000 populations from the Australian marine economic zone. We analysed these data using two approaches: a linear mixed model for standardised data, and a mixed beta-regression for unstandardised data, within a Bayesian framework. Our beta-regression approach performed better than models using standardised data, based on posterior predictive tests. The best model included region (Integrated Marine and Coastal Regionalisation of Australia (IMCRA) bioregions), latitude and latitude squared. Removing region as an explanatory variable greatly reduced model performance (delta DIC 23.4). Several bioregions were identified as possessing notably high genetic diversity. Genetic diversity increased towards the equator with a ‘hump’ in diversity across the range studied (−9.4 to −43.7°S). Our results suggest that factors correlated with both region and latitude play a role in shaping intra-specific genetic diversity, and that bioregion can be a useful management unit for intra-specific as well as species biodiversity. Our novel statistical model should prove useful for future analyses of within species genetic diversity at broad taxonomic and geographic scales.

MotivationBirds are an extremely diverse group in terms of adaptations to environmental conditions, which is reflected in their life histories and ecological traits. Recently, functional aspects of avian diversity have been used frequently in comparative analyses as well as in community ecology studies; thus, open access to complete datasets of traits will be valuable. We focused on European bird species and compiled information about crucial ecological traits. This dataset is thus useful for research investigating large‐scale patterns in European avifauna and can be used in various analyses in evolutionary ecology, macroecology or conservation biology.Main types of variables containedWe chose several types of avian traits, such as morphological (e.g., weight, wing, bill or tarsus length), reproductive (e.g., clutch size, egg mass, incubation period or type of young) and behavioural traits (type of nest, mating system or type of parental care), dietary (e.g., folivore, granivore, insectivore or carnivore) and habitat preferences (e.g., deciduous/coniferous forest, reed or grassland).Spatial location and grainEurope; all breeding bird species (n = 499).Major taxa and level of measurementIn total, we created a dataset for 499 bird species breeding in Europe and 34 key life‐history traits represented in 85 variables. As a primary source of information we used the comprehensive handbook The birds of the Western Palearctic. The traits provide information about species‐specific mean values. We did not record values for different geographical subspecies (i.e., the trait value always represents the average for the whole breeding area of a particular species).Software formatThe data file is in ASCII text, tab delimited, not compressed.

Savanna trees in Namibia—Factors controlling their distribution at the arid end of the spectrum

Linking species, traits and habitat characteristics of Collembola at European scale

Species respond dynamically to climate change and exhibit time lags. Consequently, species may not occupy their full climatic niche during range shifting. Here, we assessed climate niche tracking during recent range shifts of European and UnitedStates (US) birds. Using data from two European bird atlases and from the North American Breeding Bird Survey betweenthe 1980s and 2010s, we analysed range overlap and climate niche overlap based on kernel density estimation. Phylogenetic multiple regression was used to assess the effect of species morphological, ecological and biogeographic traits on range and niche metrics. European birds shifted their ranges north and north-eastwards, US birds westwards. Range unfilling was lower than expected by null models, and niche expansion was more common than niche unfilling. Also, climate niche tracking was generally lower in US birds and poorly explained by species traits. Overall, our results suggest that dispersal limitations were minor in range shifting birds in Europe and theUSA while delayed extinctions from unfavourable areas seem more important. Regional differences could be related to differences in land use history and monitoring schemes. Comparative analyses of range and niche shifts provide a useful screening approach for identifying the importance of transient dynamics and time-lagged responses to climate change. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

BackgroundThe typical objective of Genome-wide association (GWA) studies is to identify single-nucleotide polymorphisms (SNPs) and corresponding genes with the strongest evidence of association (the 'most-significant SNPs/genes' approach). Borrowing ideas from micro-array data analysis, we propose a new method, named RS-SNP, for detecting sets of genes enriched in SNPs moderately associated to the phenotype. RS-SNP assesses whether the number of significant SNPs, with p-value P ≤ α, belonging to a given SNP set is statistically significant. The rationale of proposed method is that two kinds of null hypotheses are taken into account simultaneously. In the first null model the genotype and the phenotype are assumed to be independent random variables and the null distribution is the probability of the number of significant SNPs in greater than observed by chance. The second null model assumes the number of significant SNPs in depends on the size of and not on the identity of the SNPs in . Statistical significance is assessed using non-parametric permutation tests.ResultsWe applied RS-SNP to the Crohn's disease (CD) data set collected by the Wellcome Trust Case Control Consortium (WTCCC) and compared the results with GENGEN, an approach recently proposed in literature. The enrichment analysis using RS-SNP and the set of pathways contained in the MSigDB C2 CP pathway collection highlighted 86 pathways rich in SNPs weakly associated to CD. Of these, 47 were also indicated to be significant by GENGEN. Similar results were obtained using the MSigDB C5 pathway collection. Many of the pathways found to be enriched by RS-SNP have a well-known connection to CD and often with inflammatory diseases.ConclusionsThe proposed method is a valuable alternative to other techniques for enrichment analysis of SNP sets. It is well founded from a theoretical and statistical perspective. Moreover, the experimental comparison with GENGEN highlights that it is more robust with respect to false positive findings.

QuestionsIs the incidence of root hemiparasitic plants in non‐forest vegetation associated with high diversity? Are root hemiparasites more associated with species‐rich vegetation than other species?LocationCzech Republic.MethodsPlot size‐corrected species richness, Shannon diversity and Pielou's evenness were computed for a representative set of 18 101 vegetation plots representing all main types of terrestrial open (non‐forest) habitats of the country. Null models of species richness assuming occurrence of a random species with given occurrence frequency, reflecting higher incidence probability in species‐rich plots, were constructed for 16 common root hemiparasitic species. The null model distribution of species richness was subsequently compared with the actual mean species richness of plots containing the respective root hemiparasites. Median values of plot Shannon diversity and evenness were computed for each species in the database. Values obtained for plots containing individual root hemiparasites were compared with distribution of values for other species in the database.ResultsThe occurrence of 11 of 16 root hemiparasites studied was associated with high species richness significantly more than under random expectations; three species were negatively associated. Three root hemiparasites were among the top 5% of all species associated with high species richness and Shannon diversity, and eight were among the top 25%. Almost 50% of the top 1% most species‐rich plots contained at least one root hemiparasitic species.ConclusionsWe demonstrated a positive association between the incidence of most root hemiparasites and diversity of non‐forest terrestrial plant communities at a broad landscape scale. This finding scales up the results of experimental studies that showed some root hemiparasites act as ecosystem engineers, increasing vegetation diversity. Root hemiparasites should be regarded as important biodiversity indicators and potential drivers of biodiversity. As such, conserving their wild populations or promoting their establishment should become a goal of nature conservation and ecological restoration.

AimTo analyse the diversity and distribution of oceanic pelagic cephalopods along the eastern Pacific Ocean assessing the existence of biogeographic structuring, and the role of physical variables in generating geographical patterns. We hypothesized that the control by environmental factors, and the effect of geometric constraints, determine the range size and limits of distribution of oceanic cephalopods along the eastern Pacific Ocean, generating a latitudinal gradient in species richness.LocationEastern Pacific Ocean (60°N – 60°S), from the Gulf of Alaska to the Southern Ocean.MethodsBased on a literature review and >5,000 records obtained from collections, we constructed a presence–absence matrix including 61 latitudinal bands (2° each) along the Eastern Pacific, and estimated species richness and range endpoints at each band. Biogeographic units were determined by means of multivariate analyses. Species richness was compared with null model predictions in order to test for the existence of geometric constraints using the Mid‐Domain Null model. The effects on species richness of environmental variables (temperature, salinity and oxygen) were evaluated separately for surface and depth (0–1,000 m) data, by means of ordinary least squares regression and simultaneous autoregressive models. Rapoport's pattern was assessed by applying the Stevens’ method and the range midpoint method.ResultsSpecies richness was high across the tropics and decreased towards the both poles. We identified five biogeographic units, highlighting two major distribution breaks at 40°N and 42°S. Species richness was strongly related with environmental variables, although the combined variables accounted for a large fraction of the variance between 0 and 1,000 m (R2 = 0.99), while temperature was the best single predictor at the surface (R2 = 0.98). Species richness curves showed a mid‐domain effect (MDE), and the mean latitudinal range was higher in the tropics and at warm latitudes, generating an inverse Rapoport's pattern.Main conclusionsAlong the eastern Pacific Ocean oceanic cephalopods exhibit both a clear biogeographic patterning and an interhemispheric (poleward decreasing) diversity gradient, which appear strongly related with physical factors and external forcing, as well as with a MDE as a seemingly consequence of the naturally bounded domain of the Eastern Pacific.

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or “footprint”) of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

Giant salamanders are the world’s largest amphibians and keystone predators in riverine ecosystems where they face global declines. Identifying environmental variables influencing their distribution is, therefore, an essential step for their conservation. This study aims to assess the current habitat suitability and distribution of the Japanese giant salamander (Andrias japonicus) and to predict changes under future climate scenarios. We used species distribution models (SDMs) over a 282,916 km² area, including 477 high-resolution occurrence data of giant salamanders and seven remote-sensing environmental predictors (climatic, topographic and land use). We projected the prediction maps, identified the most contributing variables and calculated the shifts of suitable areas for three periods (2050, 2070 and 2090) under projected climatic conditions. Climatic variables highly contributed to the distribution of giant salamanders (76% of the total), with preferences for areas with moderate precipitations during cold and wet seasons and mild summer temperatures. A moderately steep surrounding environment was favourable for salamanders, whereas the land-use variables had less influence. Future climate predictions indicate a major decrease of suitable areas. Altogether, our results highlight the habitat preferences of giant salamanders at a broad scale and the negative impact of climate change on future suitable areas. These findings provide important steps for upcoming conservation actions for this threatened species in delineating favourable distribution ranges and priority areas that should be directly affected by climate change. Finally, they emphasise the need for new research at a fine scale on disturbances to the aquatic habitat to enhance the conservation of giant salamanders. We used a species distribution model (MaxEnt), high-resolution occurrence data and remote sensing data (climatic, topographic and land use) to identify suitable habitats for the Japanese giant salamander in Japan. The most suitable environments for the Japanese giant salamander are located both within and beyond its current distribution range, with the ‘Japanese Alps’ forming an impassable natural barrier. Among the variables studied, precipitation of the warmest quarter, precipitation of the coldest quarter, mean temperature of the warmest quarter and mean temperature of the wettest quarter were the most important environmental predictors of the species’ distribution. Climate change is expected to severely reduce the potential suitable geographical areas for the Japanese giant salamander in the future. The present work calls for new surveys based on the projected maps to improve the mapping of salamander distribution and to focus on ecological features and threats at the aquatic habitat level to understand the risks to their populations.