Geographic range estimates and environmental requirements for the harpy eagle derived from spatial models of current and past distribution

Understanding species–environment relationships is key to defining the spatial structure of species distributions and develop effective conservation plans. However, for many species, this baseline information does not exist. With reliable presence data, spatial models that predict geographic ranges and identify environmental processes regulating distribution are a cost‐effective and rapid method to achieve this. Yet these spatial models are lacking for many rare and threatened species, particularly in tropical regions. The harpy eagle (Harpia harpyja) is a Neotropical forest raptor of conservation concern with a continental distribution across lowland tropical forests in Central and South America. Currently, the harpy eagle faces threats from habitat loss and persecution and is categorized as Near‐Threatened by the International Union for the Conservation of Nature (IUCN). Within a point process modeling (PPM) framework, we use presence‐only occurrences with climatic and topographical predictors to estimate current and past distributions and define environmental requirements using Ecological Niche Factor Analysis. The current PPM prediction had high calibration accuracy (Continuous Boyce Index = 0.838) and was robust to null expectations (pROC ratio = 1.407). Three predictors contributed 96% to the PPM prediction, with Climatic Moisture Index the most important (72.1%), followed by minimum temperature of the warmest month (15.6%) and Terrain Roughness Index (8.3%). Assessing distribution in environmental space confirmed the same predictors explaining distribution, along with precipitation in the wettest month. Our reclassified binary model estimated a current range size 11% smaller than the current IUCN range polygon. Paleoclimatic projections combined with the current model predicted stable climatic refugia in the central Amazon, Guyana, eastern Colombia, and Panama. We propose a data‐driven geographic range to complement the current IUCN range estimate and that despite its continental distribution, this tropical forest raptor is highly specialized to specific environmental requirements.     

Parapatric species and the implications for climate change studies: a case study on hares in Europe

Parapatry is a biogeographical term used to refer to organisms whose ranges do not overlap, but are immediately adjacent to each other; they only co‐occur – if at all – in a narrow contact zone. Often there are no environmental barriers in the contact zones, hence competitive interaction is usually advocated as the factor that modulates species distribution ranges. Even though the effects of climate change on species distribution have been widely studied, few studies have explored these effects on the biogeographical relationships between closely related, parapatric, species. We modelled environmental favourability for three parapatric hare species in Europe – Lepus granatensis, L. europaeus and L. timidus – using ecogeographical variables and projected the models into the future according to the IPCC A2 emissions scenario. Favourabilities for present and future scenarios were combined using fuzzy logic with the following aims: (i) to determine the biogeographical relationships between hare species in parapatry, that is L. granatensis/L. europaeus and L. europaeus/L. timidus and (ii) to assess the effects of climate change on each species as well as on their interspecific interactions. In their contact area L. granatensis achieved higher favourability values than L. europaeus, suggesting that if both species have a similar population status, the former species may have some advantages over the latter if competitive relationships are established. Climate change had the most striking effect on the distribution of L. timidus, especially when interspecific interactions with L. europaeus were taken into account, which may compromise the co‐existence of L. timidus. The results of this study are relevant not only for understanding the distribution patterns of the hares studied and the effects of climate change on these patterns, but also for improving the general application of species distribution models to the prediction of the effects of climate change on biodiversity.     

Mutualism influences species distribution predictions for a bromeliad‐breeding anuran under climate change

Ecological niche models, or species distribution models, have been widely used to identify potentially suitable areas for species in future climate change scenarios. However, there are inherent errors to these models due to their inability to evaluate species occurrence influenced by non‐climatic factors. With the intuit to improve the modelling predictions for a bromeliad‐breeding treefrog (Phyllodytes melanomystax, Hylidae), we investigate how the climatic suitability of bromeliads influences the distribution model for the treefrog in the context of baseline and 2050 climate change scenarios. We used point occurrence data on the frog and the bromeliad (Vriesea procera, Bromeliaceae) to generate their predicted distributions based on baseline and 2050 climates. Using a consensus of five algorithms, we compared the accuracy of the models and the geographic predictions for the frog generated from two modelling procedures: (i) a climate‐only model for P. melanomystax and V. procera; and (ii) a climate‐biotic model for P. melanomystax, in which the climatic suitability of the bromeliad was jointly considered with the climatic variables. Both modelling approaches generated strong and similar predictive power for P. melanomystax, yet climate‐biotic modelling generated more concise predictions, particularly for the year 2050. Specifically, because the predicted area of the bromeliad overlaps with the predictions for the treefrog in the baseline climate, both modelling approaches produce reasonable similar predicted areas for the anuran. Alternatively, due to the predicted loss of northern climatically suitable areas for the bromeliad by 2050, only the climate‐biotic models provide evidence that northern populations of P. melanomystax will likely be negatively affected by 2050.     

Habitat distribution modelling,under the present climatic scenario,of the threatened endemic Iberian Delphinium fissum subsp. sordidum (Ranunculaceae) and implications for its conservation

We modelled the potential habitat of a threatened species D. fissum subsp. sordidum, an endemic hemicryptophyte with a disjunct distribution in the Iberian Peninsula. Maxent was used to predict the subspecies habitat suitability by relating field sample-based distributional information with environmental and topographic variables. Our results suggest that the model performed well, predicting with high accuracy the current distribution of the species. The variables that most contributed to the model were Mean Temperature of Wettest Quarter (MTWtQ), Precipitation of Warmest Quarter (PWmQ), Temperature Annual Range (TAR) and Slope (Slo). These variables are biological significant for the taxon, as they have decisive influence in the critical stages of germination and fruiting. The current and potential distributional areas identified by the model fall mainly in regions with some degree of environmental protection, with some exceptions. A recovery plan for the species should be considered. Species Distribution Modelling cannot substitute long-term monitoring programmes, yet it is a useful tool for identifying appropriate areas of taxon occurrence, and thus allow for efficient use of the economic and human resources.     

Reproduction as a bottleneck to treeline advance across the circumarctic forest tundra ecotone

The fundamental niche of many species is shifting with climate change, especially in sub‐arctic ecosystems with pronounced recent warming. Ongoing warming in sub‐arctic regions should lessen environmental constraints on tree growth and reproduction, leading to increased success of trees colonising tundra. Nevertheless, variable responses of treeline ecotones have been documented in association with warming temperatures. One explanation for time lags between increasingly favourable environmental conditions and treeline ecotone movement is reproductive limitations caused by low seed availability. Our objective was to assess the reproductive constraints of the dominant tree species at the treeline ecotone in the circumpolar north. We sampled reproductive structures of trees (cones and catkins) and stand attributes across circumarctic treeline ecotones. We used generalized linear mixed models to estimate the sensitivity of seed production and the availability of viable seed to regional climate, stand structure, and species‐specific characteristics. Both seed production and viability of available seed were strongly driven by specific, sequential seasonal climatic conditions, but in different ways. Seed production was greatest when growing seasons with more growing degree days coincided with years with high precipitation. Two consecutive years with more growing degree days and low precipitation resulted in low seed production. Seasonal climate effects on the viability of available seed depended on the physical characteristics of the reproductive structures. Large‐coned and ‐seeded species take more time to develop mature embryos and were therefore more sensitive to increases in growing degree days in the year of flowering and embryo development. Our findings suggest that both moisture stress and abbreviated growing seasons can have a notable negative influence on the production and viability of available seed at treeline. Our synthesis revealed that constraints on predispersal reproduction within the treeline ecotone might create a considerable time lag for range expansion of tree populations into tundra ecosystems.     

Prey switching as a means of enhancing persistence in predators at the trailing southern edge

Understanding the effects of climate change on species’ persistence is a major research interest; however, most studies have focused on responses at the northern or expanding range edge. There is a pressing need to explain how species can persist at their southern range when changing biotic interactions will influence species occurrence. For predators, variation in distribution of primary prey owing to climate change will lead to mismatched distribution and local extinction, unless their diet is altered to more extensively include alternate prey. We assessed whether addition of prey information in climate projections restricted projected habitat of a specialist predator, Canada lynx (Lynx canadensis), and if switching from their primary prey (snowshoe hare; Lepus americanus) to an alternate prey (red squirrel; Tamiasciurus hudsonicus) mitigates range restriction along the southern range edge. Our models projected distributions of each species to 2050 and 2080 to then refine predictions for southern lynx on the basis of varying combinations of prey availability. We found that models that incorporated information on prey substantially reduced the total predicted southern range of lynx in both 2050 and 2080. However, models that emphasized red squirrel as the primary species had 7–24% lower southern range loss than the corresponding snowshoe hare model. These results illustrate that (i) persistence at the southern range may require species to exploit higher portions of alternate food; (ii) selection may act on marginal populations to accommodate phenotypic changes that will allow increased use of alternate resources; and (iii) climate projections based solely on abiotic data can underestimate the severity of future range restriction. In the case of Canada lynx, our results indicate that the southern range likely will be characterized by locally varying levels of mismatch with prey such that the extent of range recession or local adaptation may appear as a geographical mosaic.     

Fish introductions reveal the temperature dependence of species interactions

A major area of current research is to understand how climate change will impact species interactions and ultimately biodiversity. A variety of environmental conditions are rapidly changing owing to climate warming, and these conditions often affect both the strength and outcome of species interactions. We used fish distributions and replicated fish introductions to investigate environmental conditions influencing the coexistence of two fishes in Swedish lakes: brown trout (Salmo trutta) and pike (Esox lucius). A logistic regression model of brown trout and pike coexistence showed that these species coexist in large lakes (more than 4.5 km²), but not in small, warm lakes (annual air temperature more than 0.9–1.5°C). We then explored how climate change will alter coexistence by substituting climate scenarios for 2091–2100 into our model. The model predicts that brown trout will be extirpated from approximately half of the lakes where they presently coexist with pike and from nearly all 9100 lakes where pike are predicted to invade. Context dependency was critical for understanding pike–brown trout interactions, and, given the widespread occurrence of context-dependent species interactions, this aspect will probably be critical for accurately predicting climate impacts on biodiversity.     

Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks

Macroecological models for predicting species distributions usually only include abiotic environmental conditions as explanatory variables, despite knowledge from community ecology that all species are linked to other species through biotic interactions. This disconnect is largely due to the different spatial scales considered by the two sub‐disciplines: macroecologists study patterns at large extents and coarse resolutions, while community ecologists focus on small extents and fine resolutions. A general framework for including biotic interactions in macroecological models would help bridge this divide, as it would allow for rigorous testing of the role that biotic interactions play in determining species ranges. Here, we present an approach that combines species distribution models with Bayesian networks, which enables the direct and indirect effects of biotic interactions to be modelled as propagating conditional dependencies among species’ presences. We show that including biotic interactions in distribution models for species from a California grassland community results in better range predictions across the western USA. This new approach will be important for improving estimates of species distributions and their dynamics under environmental change.     

Developing biodiverse plantings suitable for changing climatic conditions 2: Using the Atlas of Living Australia

Summary There has been an increasing investment of taxpayer dollars in revegetation in Australia over the past 20 years, at both federal and state levels. The largest of these, the Australian Government’s Biodiversity Fund, will invest A$946 million to revegetate, rehabilitate and restore landscapes to store carbon, enhance biodiversity and build environmental resilience under climate change. The universal challenge for restoration practitioners working within these programmes is species selection for both current and future environmental conditions at a given site. For policy makers, the challenge is to provide guidelines and tools for this process. The first paper in this series of two papers looked at scientific methods that could provide underpinning knowledge to improve the assessment of species vulnerability to climatic and atmospheric change. In this paper, the publically accessible Atlas of Living Australia is used to demonstrate how revegetation project leaders can assess whether the species and provenances used in their revegetation projects are likely to be suitable for changing environmental conditions. While using the Atlas can assist current selections, ways in which more reliable selections for changing climatic conditions could be made are also outlined.     

No species is an island: testing the effects of biotic interactions on models of avian niche occupation

Traditionally, the niche of a species is described as a hypothetical 3D space, constituted by well‐known biotic interactions (e.g. predation, competition, trophic relationships, resource–consumer interactions, etc.) and various abiotic environmental factors. Species distribution models (SDMs), also called “niche models” and often used to predict wildlife distribution at landscape scale, are typically constructed using abiotic factors with biotic interactions generally been ignored. Here, we compared the goodness of fit of SDMs for red‐backed shrike Lanius collurio in farmlands of Western Poland, using both the classical approach (modeled only on environmental variables) and the approach which included also other potentially associated bird species. The potential associations among species were derived from the relevant ecological literature and by a correlation matrix of occurrences. Our findings highlight the importance of including heterospecific interactions in improving our understanding of niche occupation for bird species. We suggest that suite of measures currently used to quantify realized species niches could be improved by also considering the occurrence of certain associated species. Then, an hypothetical “species 1” can use the occurrence of a successfully established individual of “species 2” as indicator or “trace” of the location of available suitable habitat to breed. We hypothesize this kind of biotic interaction as the “heterospecific trace effect” (HTE): an interaction based on the availability and use of “public information” provided by individuals from different species. Finally, we discuss about the incomes of biotic interactions for enhancing the predictive capacities on species distribution models.     

The projected effects of climatic and vegetation changes on the distribution and diversity of Southeast Asian bats

Southeast‐Asia (SEA) constitutes a global biodiversity hotspot, but is exposed to extensive deforestation and faces numerous threats to its biodiversity. Climate change represents a major challenge to the survival and viability of species, and the potential consequences must be assessed to allow for mitigation. We project the effects of several climate change scenarios on bat diversity, and predict changes in range size for 171 bat species throughout SEA. We predict decreases in species richness in all areas with high species richness (>80 species) at 2050–2080, using bioclimatic IPCC scenarios A2 (a severe scenario, continuously increasing human population size, regional changes in economic growth) and B1 (the ‘greenest’ scenario, global population peaking mid‐century). We also predicted changes in species richness in scenarios that project vegetation changes in addition to climate change up to 2050. At 2050 and 2080, A2 and B1 scenarios incorporating changes in climatic factors predicted that 3–9% species would lose all currently suitable niche space. When considering total extents of species distribution in SEA (including possible range expansions), 2–6% of species may have no suitable niche space in 2050–2080. When potential vegetation and climate changes were combined only 1% of species showed no changes in their predicted ranges by 2050. Although some species are projected to expand ranges, this may be ecologically impossible due to potential barriers to dispersal, especially for species with poor dispersal ability. Only 1–13% of species showed no projected reductions in their current range under bioclimatic scenarios. An effective way to facilitate range shift for dispersal‐limited species is to improve landscape connectivity. If current trends in environmental change continue and species cannot expand their ranges into new areas, then the majority of bat species in SEA may show decreases in range size and increased extinction risk within the next century.     

Integrating demography and distribution modeling for the iconic Leontopodium alpinum Colm. in the Romanian Carpathians

1. Both climate change and human exploitation are major threats to plant life in mountain environments. One species that may be particularly sensitive to both of these stressors is the iconic alpine flower edelweiss (Leontopodium alpinum Colm.). Its populations have declined across Europe due to over‐collection for its highly prized flowers. Edelweiss is still subject to harvesting across the Romanian Carpathians, but no study has measured to what extent populations are vulnerable to anthropogenic change.
2. Here, we estimated the effects of climate and human disturbance on the fitness of edelweiss. We combined demographic measurements with predictions of future range distribution under climate change to assess the viability of populations across Romania.
3. We found that per capita and per‐area seed number and seed mass were similarly promoted by both favorable environmental conditions, represented by rugged landscapes with relatively cold winters and wet summers, and reduced exposure to harvesting, represented by the distance of plants from hiking trails. Modeling these responses under future climate scenarios suggested a slight increase in per‐area fitness. However, we found plant ranges contracted by between 14% and 35% by 2050, with plants pushed into high elevation sites.
4. Synthesis. Both total seed number and seed mass are expected to decline across Romania despite individual edelweiss fitness benefiting from a warmer and wetter climate. More generally, our approach of coupling species distribution models with demographic measurements may better inform conservation strategies of ways to protect alpine life in a changing world.

     

Biotic interactions influence the projected distribution of a specialist mammal under climate change

Aim

To measure the effects of including biotic interactions on climate‐based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.

Location

North‐east Queensland, Australia.

Methods

We developed separate climate‐based distribution models for the northern bettong, its two main resources and a competitor species. We then constructed models for the northern bettong by including climate suitability estimates for the resources and competitor as additional predictor variables to make climate + resource and climate + resource + competition models. We projected these models onto seven future climate scenarios and compared predictions of northern bettong distribution made by these differently structured models, using a ‘global’ metric, the I similarity statistic, to measure overlap in distribution and a ‘local’ metric to identify where predictions differed significantly.

Results

Inclusion of food resource biotic interactions improved model performance. Over moderate climate changes, up to 3.0 °C of warming, the climate‐only model for the northern bettong gave similar predictions of distribution to the more complex models including interactions, with differences only at the margins of predicted distributions. For climate changes beyond 3.0 °C, model predictions diverged significantly. The interactive model predicted less contraction of distribution than the simpler climate‐only model.

Main conclusions

Distribution models that account for interactions with other species, in particular direct resources, improve model predictions in the present‐day climate. For larger climate changes, shifts in distribution of interacting species cause predictions of interactive models to diverge from climate‐only models. Incorporating interactions with other species in SDMs may be needed for long‐term prediction of changes in distribution of species under climate change, particularly for specialized species strongly dependent on a small number of biotic interactions.     

Compositional similarity and the distribution of geographical range size for assemblages of native and non-native species in urban floras

There is evidence that, within a region, non-native species introduced from nearby sources (extralimital native) promote homogenization and non-native species introduced from distant sources (exotic) promote differentiation of species composition. A possible explanation for these associations is that they are related to differences in the distribution of geographical range size. We test this by examining geographical ranges, delineated within a defined region, for assemblages of vascular plants in eight urban floras in the USA. Across floras, native species had the largest, least variable ranges and the greatest proportion of shared species. Exotic species had the most variable ranges with concentrations of species with small and large ranges and the lowest proportion of shared species. Extralimital natives had concentrations of species with intermediate-sized ranges and intermediate proportions of shared species. These results suggest that patterns of compositional similarity were associated with the relative strength and equality of two opposing patterns within species range size distributions: species with small vs. large ranges. In general, concentrations of species with small ranges promoted low levels and concentrations of species with large ranges promoted high levels of compositional similarity. However, patterns documented for exotic species will likely continue to develop, possibly taking on new forms, depending on how geographical distributions and the rate of introductions of exotic species change over time. Our findings also suggest that processes underlying these patterns have operated at two spatiotemporal scales. The first scale reflects historical consequences of anthropogenic activities occurring within regional extents that have promoted the introduction of extralimital natives; the second scale reflects modern consequences of anthropogenic activities operating at an increasingly global extent that have promoted the introduction of exotic species.     

Occupancy models including local and landscape variables are useful to assess the distribution of a salamander species at risk

Numerous amphibian species are at risk of extinction worldwide. Therefore, reliable estimations of the distribution and abundance of these species are necessary for their conservation. Generally, amphibians are difficult to detect in the wild, which compromises the accuracy of long-term population monitoring and management. Occupancy models are useful tools to assess how environmental variables, at a local and at a landscape scale, affect the distribution and abundance of organisms taking into account species imperfect detectability. In this study, we evaluated with an environmental multiscale approach the seasonal variation of the occupation area of the threatened salamander, Ambystoma ordinarium along its distribution range. We obtained readings in 60 streams of physicochemical variables associated with habitat quality and landscape features. We found that detection and occupation probability of A. ordinarium are seasonally associated with different environmental variables. During the dry season, detectability was positively associated with temperature and stream depth, whereas occupancy was positively associated with the proportion of crops in the landscape and stream elevation. In the rainy season, the detection probability was not explained by any variable considered, and occupancy was negatively associated with stream's electrical conductivity and dissolved oxygen. Based on the estimation of occupied sites, we showed that A. ordinarium presents a more restricted distribution range than previously projected. Therefore, our results reveal the importance of evaluating the accuracy of distribution estimates for the conservation of threatened species as A. ordinarium.     

Type and spatial structure of distribution data and the perceived determinants of geographical gradients in ecology: the species richness of African birds

Aim Studies exploring the determinants of geographical gradients in the occurrence of species or their traits obtain data by: (1) overlaying species range maps; (2) mapping survey‐based species counts; or (3) superimposing models of individual species’ distributions. These data types have different spatial characteristics. We investigated whether these differences influence conclusions regarding postulated determinants of species richness patterns. Location Our study examined terrestrial bird diversity patterns in 13 nations of southern and eastern Africa, spanning temperate to tropical climates. Methods Four species richness maps were compiled based on range maps, field‐derived bird atlas data, logistic and autologistic distribution models. Ordinary and spatial regression models served to examine how well each of five hypotheses predicted patterns in each map. These hypotheses propose productivity, temperature, the heat–water balance, habitat heterogeneity and climatic stability as the predominant determinants of species richness. Results The four richness maps portrayed broadly similar geographical patterns but, due to the nature of underlying data types, exhibited marked differences in spatial autocorrelation structure. These differences in spatial structure emerged as important in determining which hypothesis appeared most capable of explaining each map's patterns. This was true even when regressions accounted for spurious effects of spatial autocorrelation. Each richness map, therefore, identified a different hypothesis as the most likely cause of broad‐scale gradients in species diversity. Main conclusions Because the ‘true’ spatial structure of species richness patterns remains elusive, firm conclusions regarding their underlying environmental drivers remain difficult. More broadly, our findings suggest that care should be taken to interpret putative determinants of large‐scale ecological gradients in light of the type and spatial characteristics of the underlying data. Indeed, closer scrutiny of these underlying data — here the distributions of individual species — and their environmental associations may offer important insights into the ultimate causes of observed broad‐scale patterns.     

Little evidence for morphological change in a resilient endemic species following the introduction of a novel predator

Human activities, such as species introductions, are dramatically and rapidly altering natural ecological processes and often result in novel selection regimes. To date, we still have a limited understanding of the extent to which such anthropogenic selection may be driving contemporary phenotypic change in natural populations. Here, we test whether the introduction of the piscivorous Nile perch, Lates niloticus, into East Africa's Lake Victoria and nearby lakes coincided with morphological change in one resilient native prey species, the cyprinid fish Rastrineobola argentea. Drawing on prior ecomorphological research, we predicted that this novel predator would select for increased allocation to the caudal region in R. argentea to enhance burst‐swimming performance and hence escape ability. To test this prediction, we compared body morphology of R. argentea across space (nine Ugandan lakes differing in Nile perch invasion history) and through time (before and after establishment of Nile perch in Lake Victoria). Spatial comparisons of contemporary populations only partially supported our predictions, with R. argentea from some invaded lakes having larger caudal regions and smaller heads compared to R. argentea from uninvaded lakes. There was no clear evidence of predator‐associated change in body shape over time in Lake Victoria. We conclude that R. argentea have not responded to the presence of Nile perch with consistent morphological changes and that other factors are driving observed patterns of body shape variation in R. argentea.     

样本量与研究范围变化对MaxEnt模型准确度的影响——以黑白仰鼻猴为例

MaxEnt模型是过去几年最为流行的物种分布预测模型之一。针对一些濒危物种、入侵种和模拟数据的研究表明,MaxEnt模型均能在小样本的分布数据下得到较准确的预测结果。此外,研究范围的变化也会影响MaxEnt模型的构建。 然而,基于动物的实际分布数据来评估MaxEnt模型的研究甚少。 我们以黑白仰鼻猴 (Rhinopithecus bieti)为例,以11个猴群的分布数据为训练数据（样本量从1到10个猴群）,在不同研究范围内构建MaxEnt模型,通过其它5个的猴群分布数据验证,分析样本量和研究范围变化对模型准确度产生的影响。 结果表明,随样本量和研究范围增大,MaxEnt模型准确度及稳定性都有增加。 此外,研究范围变化对模型准确度有一定影响。 应用Maxent进行物种分布预测时,训练数据应尽可能涵盖该物种可能出现的全部环境梯度。构建模型所需的背景数据点选择,应与建模使用的物种出现点形成有效对照。     

An attack on two fronts: predicting how changes in land use and climate affect the distribution of stream macroinvertebrates

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