Jeremy T. Kerr

Energy, water, and broad-scale geographic patterns of species richness

It is often claimed that we do not understand the forces driving the global diversity gradient. However, an extensive literature suggests that contemporary climate constrains terrestrial taxonomic richness over broad geographic extents. Here, we review the empirical literature to examine the nature and form of the relationship between climate and richness. Our goals were to document the support for the climatically based energy hypothesis, and within the constraints imposed by correlative analyses, to evaluate two versions of the hypothesis: the productivity and ambient energy hypotheses. Focusing on studies extending over 800 km, we found that measures of energy, water, or water-energy balance explain spatial variation in richness better than other climatic and non-climatic variables in 82 of 85 cases. Even when considered individually and in isolation, water/ energy variables explain on average over 60% of the variation in the richness of a wide range of plant and animal groups. Further, water variables usually represent the strongest predictors in the tropics, subtropics, and warm temperate zones, whereas energy variables (for animals) or water-energy variables (for plants) dominate in high latitudes. We conclude that the interaction between water and energy, either directly or indirectly (via plant productivity), provides a strong explanation for globally extensive plant and animal diversity gradients, but for animals there also is a latitudinal shift in the relative importance of ambient energy vs. water moving from the poles to the equator. Although contemporary climate is not the only factor influencing species richness and may not explain the diversity pattern for all taxonomic groups, it is clear that understanding water-energy dynamics is critical to future biodiversity research. Analyses that do not include water-energy variables are missing a key component for explaining broad-scale patterns of diversity.

Remotely sensed habitat diversity predicts butterfly species richness and community similarity in Canada

Although there is no shortage of potential explanations for the large-scale patterns of biological diversity, the hypothesis that energy-related factors are the primary determinants is perhaps most extensively supported, especially in cold-temperate regions. By using unusually high-resolution biodiversity and environmental data that have not previously been available, we demonstrate that habitat heterogeneity, as measured by remotely sensed land cover variation, explains Canadian butterfly richness better than any energy-related variable we measured across spatial scales. Although species-richness predictability declines with progressively smaller quadrat sizes, as expected, we demonstrate that most variability (>90%) in butterfly richness may be explained by habitat heterogeneity with secondary contributions from climatic energy. We also find that patterns of community similarity across Canada are strongly related to patterns of habitat composition but not to differences in energy-related factors. Energy should still be considered significant but its main role may be through its effects on within-habitat diversity and perhaps, indirectly, on the sorts of habitats that may be found in a region. Effects of sampling intensity and spatial autocorrelation do not alter our findings.

Climate change impacts on bumblebees converge across continents

Bucking the trend Responses to climate change have been observed across many species. There is a general trend for species to shift their ranges poleward or up in elevation. Not all species, however, can make such shifts, and these species might experience more rapid declines. Kerr et al. looked at data on bumblebees across North America and Europe over the past 110 years. Bumblebees have not shifted northward and are experiencing shrinking distributions in the southern ends of their range. Such failures to shift may be because of their origins in a cooler climate, and suggest an elevated susceptibility to rapid climate change. Science, this issue p. 177 Cool-adapted bumblebees are failing to shift their ranges in response to climate warming. For many species, geographical ranges are expanding toward the poles in response to climate change, while remaining stable along range edges nearest the equator. Using long-term observations across Europe and North America over 110 years, we tested for climate change–related range shifts in bumblebee species across the full extents of their latitudinal and thermal limits and movements along elevation gradients. We found cross-continentally consistent trends in failures to track warming through time at species’ northern range limits, range losses from southern range limits, and shifts to higher elevations among southern species. These effects are independent of changing land uses or pesticide applications and underscore the need to test for climate impacts at both leading and trailing latitudinal and thermal limits for species.

A GLOBAL EVALUATION OF METABOLIC THEORY AS AN EXPLANATION FOR TERRESTRIAL SPECIES RICHNESS GRADIENTS

We compiled 46 broadscale data sets of species richness for a wide range of terrestrial plant, invertebrate, and ectothermic vertebrate groups in all parts of the world to test the ability of metabolic theory to account for observed diversity gradients. The theory makes two related predictions: (1) In-transformed richness is linearly associated with a linear, inverse transformation of annual temperature, and (2) the slope of the relationship is near -0.65. Of the 46 data sets, 14 had no significant relationship; of the remaining 32, nine were linear, meeting prediction 1. Model I (ordinary least squares, OLS) and model II (reduced major axis, RMA) regressions then tested the linear slopes against prediction 2. In the 23 data sets having nonlinear relationships between richness and temperature, split-line regression divided the data into linear components, and regressions were done on each component to test prediction 2 for subsets of the data. Of the 46 data sets analyzed in their entirety using OLS regression, one was consistent with metabolic theory (meeting both predictions), and one was possibly consistent. Using RMA regression, no data sets were consistent. Of 67 analyses of prediction 2 using OLS regression on all linear data sets and subsets, two were consistent with the prediction, and four were possibly consistent. Using RMA regression, one was consistent (albeit weakly), and four were possibly consistent. We also found that the relationship between richness and temperature is both taxonomically and geographically conditional, and there is no evidence for a universal response of diversity to temperature. Meta-analyses confirmed significant heterogeneity in slopes among data sets, and the combined slopes across studies were significantly lower than the range of slopes predicted by metabolic theory based on both OLS and RMA regressions. We conclude that metabolic theory, as currently formulated, is a poor predictor of observed diversity gradients in most terrestrial systems.

PATTERNS AND CAUSES OF SPECIES ENDANGERMENT IN CANADA

Few studies have addressed patterns and causes of species endangerment at different resolutions and geographical extents. Using newly developed remote sensing and species distribution data sets, we examined the influence of both natural and anthropogenic factors on the density of terrestrial endangered species in Canada at two spatial scales. The first was at a national extent and the second was within a region of Canada (the mixed wood plains) where there are particularly large numbers of endangered species. We also examined the distribution of protected areas throughout Canada to determine their capacity to shelter endangered species. Land use, which is measured by 1-km resolution satellite data, is a strong predictor of endangered species densities at both scales of analysis. Land use integrates information on habitat loss to agriculture and land use intensity, an index of agricultural pollution. The amount of protected area in a region is unrelated to endangered species numbers except to the extent that areas with the most endangered species are, at best, nearly devoid of protected area. Newly legislated protections for endangered species are unlikely to bring much improvement to this conservation dilemma. Canadas endangered species legislation promotes cooperative conservation activities in areas where species endangerment is most pronounced but does little to protect remaining habitat.

TESTS OF THE MID-DOMAIN HYPOTHESIS : A REVIEW OF THE EVIDENCE

Geographic variation of species richness is strongly correlated with environmental gradients. However, random arrangement of species distributions within a bounded domain can also theoretically produce richness gradients without underlying environmental gradients. This mid-domain effect (MDE) could serve as the null hypothesis against which to test effects of environmental variables, or as a component of a multivariate explanation of species-richness patterns. Recent reviews have concluded that there is a substantial MDE signature in observed geographical patterns of richness, based on correlations between observed patterns of richness and the predictions of mid-domain models. However, the mid-domain hypothesis makes additional powerful predictions about how richness should vary through space, and about the slope of the relationship between predicted and observed richness. Very few studies have tested these more powerful MDE predictions. Here, we reexamine the published mid-domain literature for agreement between observed patterns of richness and MDE predictions. We find that 50 of 53 published studies of MDEs showed significant deviations from the predictions of mid-domain models. When observed richness is correlated with MDE predictions, there are nearly always strongly collinear environmental gradients (e.g., in the Americas, climatic favorability and MDE-predicted richness are both maximal in the middle). Interpolation in sparsely sampled data can also give rise to spurious, apparently strong, mid-domain effects (e.g., the classic study of the Madagascan rain forest). We conclude that observed broad-scale patterns of species richness are not consistent with the mid-domain hypothesis.

Mechanistic models for the spatial spread of species under climate change

Global climate change is a major threat to biodiversity. The most common methods for predicting the response of biodiversity to changing climate do not explicitly incorporate fundamental evolutionary and ecological processes that determine species responses to changing climate, such as reproduction, dispersal, and adaptation. We provide an overview of an emerging mechanistic spatial theory of species range shifts under climate change. This theoretical framework explicitly defines the ecological processes that contribute to species range shifts via biologically meaningful dispersal, reproductive, and climate envelope parameters. We present methods for estimating the parameters of the model with widely available species occurrence and abundance data and then apply these methods to empirical data for 12 North American butterfly species to illustrate the potential use of the theory for global change biology. The model predicts species persistence in light of current climate change and habitat loss. On average, we estimate that the climate envelopes of our study species are shifting north at a rate of 3.25 +/- 1.36 km/yr (mean +/- SD) and that our study species produce 3.46 +/- 1.39 (mean +/- SD) viable offspring per individual per year. Based on our parameter estimates, we are able to predict the relative risk of our 12 study species for lagging behind changing climate. This theoretical framework improves predictions of global change outcomes by facilitating the development and testing of hypotheses, providing mechanistic predictions of current and future range dynamics, and encouraging the adaptive integration of theory and data. The theory is ripe for future developments such as the incorporation of biotic interactions and evolution of adaptations to novel climatic conditions, and it has the potential to be a catalyst for the development of more effective conservation strategies to mitigate losses of biodiversity from global climate change.

Lepidopteran richness patterns in North America

AbstractA long-standing objective of ecology has been to explain the basis for diversity patterns. Empirical evidence suggests that regional variation in richness of both animals and plants depends strongly on energy availability. The generality of the richness-energy hypothesis is limited by the paucity of analyses of invertebrates, which are much more diverse than the more thoroughly investigated vertebrate taxa. In this study, we consider two groups of North American Lepidoptera for which large-scale distribution data are available: the Papilionidae (swallowtail butterflies) and forest lepidopterans (moths based on the Canadian Forest Insect Survey). Energy, as measured by potential evapotranspiration (PET), statistically explains between 61 and 72% of the variability in the richness patterns of the Lepidoptera we have examined. It is the single best predictor of the richness of these groups, and the relationships have a very similar form to richness-PET relationships observed earlier in vertebrate tax...

Evolutionary constraints on regional faunas: whom, but not how many

The latitudinal diversity gradient has been hypothesized to reflect past evolutionary dynamics driven by climatic niche conservation during cladogenesis, i.e. the tropical conservatism hypothesis. Here we show that the species diversity of treefrogs (Hylidae) across the western hemisphere is actually independent of evolutionary niche dynamics. We evaluated three key predictions of the tropical conservatism hypothesis that relate to the relationships between climate, species richness and the phylogenetic structure of regional treefrog faunas across the continental Americas. Species composition was dependent on the inability of some lineages to evolve cold tolerance, but the actual number of species in a region was strongly predicted by precipitation, not temperature. Moreover, phylogenetic structure was independent of precipitation. Thus, species in low-richness areas were no more closely related than species in highly diverse regions. These results provide no support for the tropical conservatism hypothesis. Instead, they show that regional species composition and richness are constrained by different climatic components, demonstrating that global biodiversity gradients can be independent of niche stasis during cladogenesis.

High Resolution Niche Models of Malaria Vectors in Northern Tanzania: A New Capacity to Predict Malaria Risk?

Background Malaria transmission rates in Africa can vary dramatically over the space of a few kilometres. This spatial heterogeneity reflects variation in vector mosquito habitat and presents an important obstacle to the efficient allocation of malaria control resources. Malaria control is further complicated by combinations of vector species that respond differently to control interventions. Recent modelling innovations make it possible to predict vector distributions and extrapolate malaria risk continentally, but these risk mapping efforts have not yet bridged the spatial gap to guide on-the-ground control efforts. Methodology/Principal Findings We used Maximum Entropy with purpose-built, high resolution land cover data and other environmental factors to model the spatial distributions of the three dominant malaria vector species in a 94,000 km2 region of east Africa. Remotely sensed land cover was necessary in each vectors niche model. Seasonality of precipitation and maximum annual temperature also contributed to niche models for Anopheles arabiensis and An. funestus s.l. (AUC 0.989 and 0.991, respectively), but cold season precipitation and elevation were important for An. gambiae s.s. (AUC 0.997). Although these niche models appear highly accurate, the critical test is whether they improve predictions of malaria prevalence in human populations. Vector habitat within 1.5 km of community-based malaria prevalence measurements interacts with elevation to substantially improve predictions of Plasmodium falciparum prevalence in children. The inclusion of the mechanistic link between malaria prevalence and vector habitat greatly improves the precision and accuracy of prevalence predictions (r2 = 0.83 including vector habitat, or r2 = 0.50 without vector habitat). Predictions including vector habitat are unbiased (observations vs. model predictions of prevalence: slope = 1.02). Using this model, we generate a high resolution map of predicted malaria prevalence throughout the study region. Conclusions/Significance The interaction between mosquito niche space and microclimate along elevational gradients indicates worrisome potential for climate and land use changes to exacerbate malaria resurgence in the east African highlands. Nevertheless, it is possible to direct interventions precisely to ameliorate potential impacts.