Can species distribution modelling provide estimates of population densities? A case study with jaguars in the Neotropics

Effect of uneven tolerance to human disturbance on dominance interactions of top predators

Anthropogenic activities may alter felid assemblage structure, facilitating the persistence of tolerant species (commonly mesopredators), excluding ecologically demanding ones (top predators) and, consequently, changing coexistence rules. We aimed to determine how human activities influence intraguild relationships among top predators and their cascading effects on mesopredators, which remain poorly understood despite evidence of top carnivore decline. We used structural equation modeling at a continental scale to investigate how habitat quality and quantity, livestock density, and other human pressures modified the intraguild relations of the 3 species that are at the top of the food chain in the Neotropics: jaguars (Panthera onca), pumas (Puma concolor), and ocelots (Leopardus pardalis). We included presence-absence data derived from systematic studies compiled in Neocarnivores data set for these felid species at 0.0833° resolution. Human disturbance reduced the probability of jaguar occurrence by -0.35 standard deviations. Unexpectedly, the presence of sheep (Ovis aries) or goats (Capra aegagrus hircus) and jaguars was positively related to the presence of pumas, whereas puma presence was negatively related to the presence of ocelots. Extent of forest cover had more of an effect on jaguar (β = 0.23) and ocelot (β = 0.12) occurrences than the extent of protected area, which did not have a significant effect. The lack of effect of human activities on puma presence and the positive effect of small livestock supports the notion that pumas are more adaptable to habitat disturbance than jaguars. Our findings suggest that human disturbance has the potential to reverse the hierarchical competition dominance among large felids, leading to an unbalanced community structure. This shift disadvantages jaguars and elevates the position of pumas in the assemblage hierarchy, resulting in the exclusion of ocelots, despite their relatively lower susceptibility to anthropogenic disturbance. Our results suggest that conservation efforts should extend beyond protected areas to encompass the surrounding landscape, where complexities and potential conflicts are more pronounced.

A review of environmental and anthropogenic variables used to model jaguar occurrence

Jaguars (Panthera onca) are a landscape species of conservation importance and our understanding of environmental and anthropogenic drivers of jaguar occurrence is necessary to improve conservation strategies. We reviewed available literature to simply describe environmental and anthropogenic variables used and found to be significant in occurrence modeling. We reviewed 95 documents published from 1980 to 2021 that focused on jaguar occurrence and that used 39 variable types (21 anthropogenic, 18 environmental) among different techniques, scales, and approaches. In general, these variables included both anthropogenic (roads, land use, human activities, and population) and environmental (climate, vegetation, ecological interactions, topographic, water, and others) factors. Twelve variables were identified as affecting jaguar occurrence overall, eleven at local scale and seven at broad scales (regional and continental). Focusing more specifically on the variables that correlate with occurrence should help researchers to make better predictions in areas without quantitative jaguar data.

Climate Change Influences the Population Density and Suitable Area of Hippotiscus dorsalis (Hemiptera: Pentatomidae) in China

Hippotiscus dorsalis is the main pest of Phyllostachys edulis in South China. The relationship between climate change and outbreak of H. dorsalis, and the current and future distribution of H. dorsalis are unknown. This study aimed to confirm the effect of climate on population density and the attacked bamboo rate of H. dorsalis, using field survey data from 2005 to 2013 in Huzhou, Zhejiang Province, and to reveal the potential distribution of H. dorsalis under current and future climate conditions using the MaxEnt model. The damage investigation and distribution forecast revealed the following: (1) The mean monthly temperature and maximum temperatures were main factors affecting the population density and the attacked bamboo rate in April in the Anji county of Zhejiang Province; they are all significantly and positively correlated. (2) High suitable area will significantly expand in Anhui and Jiangxi Provinces under the future climate circumstances, and the total suitable area will present a decrease because of the precipitation restriction. The significant expansion of high suitable area in the Anhui and Jiangxi Provinces under future climate circumstances means that the affected provinces will face even greater challenges. These findings provide a theoretical basis for the early forecasting and monitoring of pest outbreaks.

Living under the risk of extinction: population status and conservation needs assessment of a micro–endemic tiger gecko in Vietnam

Human impact is considered the major threat to the global decline of biodiversity, especially for threatened endemic species in karst ecosystems. Studies assessing a species' demography based on temporal and spatial indicators of population size, density and structure are expected to evaluate the level of impact of threats and are therefore becoming increasingly important for species conservation efforts. Goniurosaurus huuliensis, an endemic species in Vietnam, is one of the most threatened reptiles in the world. This karst–adapted species is classified by the IUCN Red List as Critically Endangered and listed under CITES Appendix II due to habitat loss and over–exploitation for the international pet trade. Here we provide the first evaluation of the population status of G. huuliensis. We applied a 'capture mark–recapture' method to estimate the population size and identify the population density and structure. The total population size was estimated to comprise a maximum of 1,447 individuals in integrated suitable habitats, possibly reaching up to 2,855 individuals exclusively in karst habitats within the total extension of occurrence. This is exceedingly lower than the threshold for a minimum viable population. Furthermore, G. huuliensis is documented to occur in extremely small mean population densities of only 6.4 indiv./km and 2.5 indiv./km/day along the surveyed transects. Based on the demographic information, the ongoing severe human impact (e.g. wildlife exploitation and limestone quarrying) is driving G. huuliensis to the brink of extinction. In situ conservation measures are therefore urgently required. We recommend that in-situ actions should be increased, and a plan should be developed to establish a species and habitat conservation area for G. huuliensis.

Predicting Suitable Environments and Potential Occurrences for Cinnamomum camphora (Linn.) Presl

Global climate change has created a major threat to biodiversity. However, little is known about the habitat and distribution characteristics of Cinnamomum camphora (Linn.) Presl., an evergreen tree growing in tropical and subtropical Asia, as well as the factors influencing its distribution. The present study employed Maxent and a GARP to establish a potential distribution model for the target species based on 182 known occurrence sites and 17 environmental variables. The results indicate that Maxent performed better than GARP. The mean diurnal temperature range, annual precipitation, mean air temperature of driest quarter and sunshine duration in growing season were important environmental factors influencing the distribution of C. camphora and contributed 40.9%, 23.0%, 10.5%, and 7.2% to the variation in the model contribution, respectively. Based on the models, the subtropical and temperate regions of Eastern China, where the species has been recorded, had a high suitability for this species. Under each climate change scenario, the potential geographical distribution shifted farther north and toward a higher elevation. The predicted spatial and temporal distribution patterns of this species can provide guidance for the development strategies for forest management and species protection.

Geographic abundance patterns explained by niche centrality hypothesis in two Chagas disease vectors in Latin America

Ecoepidemiological scenarios for Chagas disease transmission are complex, so vector control measures to decrease human–vector contact and prevent infection transmission are difficult to implement in all geographic contexts. This study assessed the geographic abundance patterns of two vector species of Chagas disease: Triatoma maculata (Erichson, 1848) and Rhodnius pallescens (Barber, 1932) in Latin America. We modeled their potential distribution using the maximum entropy algorithm implemented in Maxent and calculated distances to their niche centroid by fitting a minimum-volume ellipsoid. In addition, to determine which method would accurately explain geographic abundance patterns, we compared the correlation between population abundance and the distance to the ecological niche centroid (DNC) and between population abundance and Maxent environmental suitability. The potential distribution estimated for T. maculata showed that environmental suitability covers a large area, from Panama to Northern Brazil. R. pallescens showed a more restricted potential distribution, with environmental suitability covering mostly the coastal zone of Costa Rica and some areas in Nicaragua, Honduras, Belize and the Yucatán Peninsula in Mexico, northern Colombia, Acre, and Rondônia states in Brazil, as well as a small region of the western Brazilian Amazon. We found a negative slope in the relationship between population abundance and the DNC in both species. R. pallecens has a more extensive potential latitudinal range than previously reported, and the distribution model for T. maculata corroborates previous studies. In addition, population abundance increases according to the niche centroid proximity, indicating that population abundance is limited by the set of scenopoetic variables at coarser scales (non-interactive variables) used to determine the ecological niche. These findings might be used by public health agencies in Latin America to implement actions and support programs for disease prevention and vector control, identifying areas in which to expand entomological surveillance and maintain chemical control, in order to decrease human–vector contact.

The differential genetic signatures related to climatic landscapes for jaguars and pumas on a continental scale

Modern and paleoclimate changes may have altered species dynamics by shifting species' niche suitability over space and time. We analyze whether the current genetic structure and isolation of the two large American felids, jaguar (Panthera onca) and puma (Puma concolor), are mediated by changes in climatic suitability and connection routes over modern and paleoclimatic landscapes. We estimate species distribution under 5 climatic landscapes (modern, Holocene, last maximum glaciations [LMG], average suitability, and climatic instability) and correlate them with individuals' genetic isolation through causal modeling on a resemblance matrix. Both species exhibit genetic isolation patterns correlated with LMG climatic suitability, suggesting that these areas may have worked as "allele refuges." However, the jaguar showed higher vulnerability to climate changes, responding to modern climatic suitability and connection routes, whereas the puma showed a continuous and gradual transition of genetic variation. Despite differential responsiveness to climate change, both species are subjected to the climatic effects on genetic configuration, which may make them susceptible to future climatic changes, since these are progressing faster and with higher intensity than changes in the paleoclimate. Thus, the effects of climatic changes should be considered in the design of conservation strategies to ensure evolutionary and demographic processes mediated by gene flow for both species.

Ecological niche models display nonlinear relationships with abundance and demographic performance across the latitudinal distribution of Astragalus utahensis (Fabaceae)

The potential for ecological niche models (ENMs) to accurately predict species' abundance and demographic performance throughout their geographic distributions remains a topic of substantial debate in ecology and biogeography. Few studies simultaneously examine the relationship between ENM predictions of environmental suitability and both a species' abundance and its demographic performance, particularly across its entire geographic distribution. Yet, studies of this type are essential for understanding the extent to which ENMs are a viable tool for identifying areas that may promote high abundance or performance of a species or how species might respond to future climate conditions. In this study, we used an ensemble ecological niche model to predict climatic suitability for the perennial forb Astragalus utahensis across its geographic distribution. We then examined relationships between projected climatic suitability and field-based measures of abundance, demographic performance, and forecasted stochastic population growth (λs). Predicted climatic suitability showed a J-shaped relationship with A. utahensis abundance, where low-abundance populations were associated with low-to-intermediate suitability scores and abundance increased sharply in areas of high predicted climatic suitability. A similar relationship existed between climatic suitability and λs from the center to the northern edge of the latitudinal distribution. Patterns such as these, where density or demographic performance only increases appreciably beyond some threshold of climatic suitability, support the contention that ENM-predicted climatic suitability does not necessarily represent a reliable predictor of abundance or performance across large geographic regions.

A Method for Heterogeneous Spatio-Temporal Data Integration in Support of Marine Aquaculture Site Selection

Aquaculture site selection, like most site suitability analyses, requires the assembly and combination of multiple variables. Geographic information systems GIS and multi-criteria evaluation (MCE) based approaches are commonly used for aquaculture site selection and demonstrate the integration of various information sources relevant for siting aquaculture. These analyses, however, tend to be one-time and result in a fixed site suitability plan. Within a dynamic marine environment experiencing potential regime shifts, a siting support tool that integrates new and evolving spatio-temporal data has benefits. This paper presents a flexible Voronoi cell-based GIS model for marine aquaculture siting. Rather than a one-time specification of suitable locations, the approach uses similarity measures on the characteristics of Voronoi cells to find cells with similar characteristics. We calculate a weighted aquaculture site tenure value for Voronoi cells that have been or are occupied by aquaculture farm sites. High scoring cells suggest suitable sites and serve as targets for similarity queries. We apply the approach to a case study on the coast of Maine using an R Shiny application to demonstrate the use of the framework for finding sites with similar characteristics.

Vulnerability of Phyllocycla Species (Odonata: Gomphidae) to Current and Planned Anthropic Activities by the Brazilian Government

Although most species distribution modeling (SDMs) are constructed at the species level, an appreciation of evolutionary processes has led to modeling above this level. In view of the difficulty in estimating the impacts of human actions on rare or deficient data species, we proposed a new approach to vulnerability assessment based on concepts already well established in the literature (ecological niche, niche conservatism, and extinction thresholds). We used distribution modeling to predict where species of the genus Phyllocycla (Calvert 1948) are most vulnerable to local extinctions and how the implementation of planned anthropic activities by the Brazilian government may modify the potential distribution of the genus in Brazil. We chose that genus because its conservation status is little known, especially due to the data gap about its geographical distribution. We proposed modeling the whole genus and used the niche conservatism theory to justify our methods. The anthropic activities considered in our analysis were agriculture and livestock, rural settlements, energy production installations, transportation, oil extraction, mining, and urbanization. We found that only 55.3% of the original potential distribution of Phyllocycla in Brazil remains available. The area compromised by anthropic activities comprises mainly the Cerrado and Atlantic Forest biomes, with less impact on the Amazon. However, with the implementation of activities planned by the Brazilian government, it is possible that an additional 13.6% of this area will be unavailable to species of Phyllocycla, especially in the Amazon, where interest in mining and the implementation of new hydroelectric production have increased.

Fragmentation and low density as major conservation challenges for the southernmost populations of the European wildcat

Knowledge of population dynamics of threatened species in the wild is key to effective conservation actions. However, at present, there are many examples of endangered animals for which their current situation is unknown, and not just in remote areas and less developed countries. We have explored this topic by studying the paradigmatic case of the European wildcat (Felis silvestris silvestris), an endangered small carnivore whose status has been subjectively established on the basis of non-systematic approaches and opportunistic records. Little is known about its demographic situation, prompting the need for information to improve conservation measures. However, the secretive behaviour of felines along with its low density in natural conditions have prevented the gathering of sufficient data. We developed a field sampling strategy for one of the largest populations (Andalusia, South Spain, 87,268 km2), based on a logistically viable systematic non-intrusive survey by camera-trapping. This study offers the first large-scale estimation for any European wildcat population, based on analytical approaches applied on Species Distribution Models. A hierarchical approach based on a Maxent model for distribution estimation was used, along with Generalised Linear Models for density estimation from explicit spatial capture-recapture data. Our results show that the distribution range is smaller and more highly fragmented than previously assumed. The overall estimated density was very low (0.069 ±0.0019 wildcats/km2) and the protected areas network seems to be insufficient to cover a significant part of the population or a viable nucleus in demographic terms. Indeed, the most important areas remain unprotected. Our main recommendations are to improve the protected area network and/or vigilance programs in hunting estates, in addition to studying and improving connectivity between the main population patches.

Two alternative evaluation metrics to replace the true skill statistic in the assessment of species distribution models

Model evaluation metrics play a critical role in the selection of adequate species distribution models for conservation and for any application of species distribution modelling (SDM) in general. The responses of these metrics to modelling conditions, however, are rarely taken into account. This leads to inadequate model selection, downstream analyses and uniformed decisions. To aid modellers in critically assessing modelling conditions when choosing and interpreting model evaluation metrics, we analysed the responses of the True Skill Statistic (TSS) under a variety of presence-background modelling conditions using purely theoretical scenarios. We then compared these responses with those of two evaluation metrics commonly applied in the field of meteorology which have potential for use in SDM: the Odds Ratio Skill Score (ORSS) and the Symmetric Extremal Dependence Index (SEDI). We demonstrate that (1) large cell number totals in the confusion matrix, which is strongly biased towards ‘true’ absences in presence-background SDM and (2) low prevalence both compromise model evaluation with TSS. This is since (1) TSS fails to differentiate useful from random models at extreme prevalence levels if the confusion matrix cell number total exceeds ~30,000 cells and (2) TSS converges to hit rate (sensitivity) when prevalence is lower than ~2.5%. We conclude that SEDI is optimal for most presence-background SDM initiatives. Further, ORSS may provide a better alternative if absence data are available or if equal error weighting is strictly required.

Species distribution modeling reveals strongholds and potential reintroduction areas for the world's largest eagle

The highly interactive nature of predator-prey relationship is essential for ecosystem conservation; predators have been extirpated, however, from entire ecosystems all over the Earth. Reintroductions comprise a management technique to reverse this trend. Species Distribution Models (SDM) are preemptive tools for release-site selection, and can define levels of habitat quality over the species distribution. The Atlantic Forest of South America has lost most of its apex predators, and Harpy Eagles Harpia harpyja—Earth’s largest eagle—are now limited to few forest pockets in this domain. Harpy Eagles are supposedly widespread in the Amazon Forest, however, where habitat loss and degradation is advancing at a rapid pace. We aim to describe the suitability of threatened Amazonian landscapes for this eagle. We also aim to assess the suitability of remaining Atlantic Forest sites for Harpy Eagle reintroductions. Here we show that that considerable eagle habitat has already been lost in Amazonia due to the expansion of the “Arc of Deforestation”, and that Amazonian forests currently represent 93% of the current distribution of the species. We also show that the Serra do Mar protected areas in southeastern Brazil is the most promising region for Harpy Eagle reintroductions in the Atlantic Forest. Reintroduction and captive breeding programs have been undertaken for Harpy Eagles, building the technical and biological basis for a successful restoration framework. Our distribution range for this species represents a 41% reduction of what is currently proposed by IUCN. Furthermore, habitat loss in Amazonia, combined with industrial logging and hunting suggest that the conservation status of this species should be reassessed. We suggest researchers and conservation practitioners can use this work to help expand efforts to conserve Harpy Eagles and their natural habitats.

Relationships between humans and ungulate prey shape Amur tiger occurrence in a core protected area along the Sino-Russian border

Large carnivore populations are globally threatened by human impacts. Better protection could benefit carnivores, co-occurring species, and the ecosystems they inhabit. The relationship between carnivores and humans, however, is not always consistent in areas of high human activities and is often mediated through the effects of humans on their ungulate prey. To test assumptions regarding how prey abundance and humans affect carnivore occurrence, density, and daily activity patterns, we assessed tiger-prey-human spatiotemporal patterns based on camera-trapping data in Hunchun Nature Reserve, a promising core area for tiger restoration in China. Our study area contained seasonally varying levels of human disturbance in summer and winter. We used N-mixture models to predict the relative abundance of ungulate prey considering human and environmental covariates. We estimated tiger spatial distribution using occupancy models and models of prey relative abundance from N-mixture models. Finally, we estimated temporal activity patterns of tigers and prey using kernel density estimates to test for temporal avoidance between tigers, prey, and humans. Our results show that human-related activities depressed the relative abundance of prey at different scales and in different ways, but across species, the relative abundance of prey directly increased tiger occupancy. Tiger occupancy was strongly positively associated with the relative abundance of sika deer in summer and winter. The crepuscular and nocturnal tigers also apparently synchronized their activity with that of wild boar and roe deer. However, tigers temporally avoided human activity without direct spatial avoidance. Our study supports the effects of humans on tigers through human impacts on prey populations. Conservation efforts may not only target human disturbance on predators, but also on prey to alleviate human-carnivore conflict.

Climate change likely to reduce orchid bee abundance even in climatic suitable sites

Studies have tested whether model predictions based on species' occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence-absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence-absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability-abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest.

Ecological niche modeling of Aedes mosquito vectors of chikungunya virus in southeastern Senegal

Background

Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent.

Methods

Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested.

Results

Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools.

Conclusions

Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2832-6) contains supplementary material, which is available to authorized users.

Geographical patterns in climate and agricultural technology drive soybean productivity in Brazil

The impacts of global climate change have been a worldwide concern for several research areas, including those dealing with resources essential to human well being, such as agriculture, which directly impact economic activities and food security. Here we evaluate the relative effect of climate (as indicated by the Ecological Niche Model-ENM) and agricultural technology on actual soybean productivity in Brazilian municipalities and estimate the future geographic distribution of soybeans using a novel statistical approach allowing the evaluation of partial coefficients in a non-stationary (Geographically Weighted Regression; GWR) model. We found that technology was more important than climate in explaining soybean productivity in Brazil. However, some municipalities are more dependent on environmental suitability (mainly in Southern Brazil). The future environmental suitability for soybean cultivation tends to decrease by up 50% in the central region of Brazil. Meanwhile, southern-most Brazil will have more favourable conditions, with an increase of ca. 25% in environmental suitability. Considering that opening new areas for cultivation can degrade environmental quality, we suggest that, in the face of climate change impacts on soybean cultivation, the Brazilian government and producers must invest in breeding programmes and more general ecosystem-based strategies for adaptation to climate change, including the development of varieties tolerant to climate stress, and strategies to increase productivity and reduce costs (social and environmental).

Mapping black panthers: Macroecological modeling of melanism in leopards (Panthera pardus)

The geographic distribution and habitat association of most mammalian polymorphic phenotypes are still poorly known, hampering assessments of their adaptive significance. Even in the case of the black panther, an iconic melanistic variant of the leopard (Panthera pardus), no map exists describing its distribution. We constructed a large database of verified records sampled across the species’ range, and used it to map the geographic occurrence of melanism. We then estimated the potential distribution of melanistic and non-melanistic leopards using niche-modeling algorithms. The overall frequency of melanism was ca. 11%, with a significantly non-random spatial distribution. Distinct habitat types presented significantly different frequencies of melanism, which increased in Asian moist forests and approached zero across most open/dry biomes. Niche modeling indicated that the potential distributions of the two phenotypes were distinct, with significant differences in habitat suitability and rejection of niche equivalency between them. We conclude that melanism in leopards is strongly affected by natural selection, likely driven by efficacy of camouflage and/or thermoregulation in different habitats, along with an effect of moisture that goes beyond its influence on vegetation type. Our results support classical hypotheses of adaptive coloration in animals (e.g. Gloger’s rule), and open up new avenues for in-depth evolutionary analyses of melanism in mammals.

Habitat suitability and demography, a time-dependent relationship

The habitat suitability index, which reflects spatial variability in species occurrence probability, has been shown to exhibit various contrasting relationships with local demographic performances (survival, productivity) in several species. One proposed explanation for these discrepancies is that the link between the habitat suitability index and demography is influenced by density-dependent, temporally variable processes. Based on the survival rates of more than 3,000 nests monitored over 12 years in the North African Houbara Bustard, we investigated whether the habitat suitability index computed over the species breeding range is related to nest survival throughout the breeding season, accounting for variation in meteorological conditions. We found that the relationship between the habitat suitability index and nest survival progressively changes along the breeding season and that this intra-annual variation is consistent between years. Our results support the hypothesis that variation in space use occurs intra-annually and that biotic interactions throughout the breeding season strongly influence the habitat suitability index-demography relationship.

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs.

Predators, Prey and Habitat Structure: Can Key Conservation Areas and Early Signs of Population Collapse Be Detected in Neotropical Forests?

Tropical forests with a low human population and absence of large-scale deforestation provide unique opportunities to study successful conservation strategies, which should be based on adequate monitoring tools. This study explored the conservation status of a large predator, the jaguar, considered an indicator of the maintenance of how well ecological processes are maintained. We implemented an original integrative approach, exploring successive ecosystem status proxies, from habitats and responses to threats of predators and their prey, to canopy structure and forest biomass. Niche modeling allowed identification of more suitable habitats, significantly related to canopy height and forest biomass. Capture/recapture methods showed that jaguar density was higher in habitats identified as more suitable by the niche model. Surveys of ungulates, large rodents and birds also showed higher density where jaguars were more abundant. Although jaguar density does not allow early detection of overall vertebrate community collapse, a decrease in the abundance of large terrestrial birds was noted as good first evidence of disturbance. The most promising tool comes from easily acquired LiDAR data and radar images: a decrease in canopy roughness was closely associated with the disturbance of forests and associated decreasing vertebrate biomass. This mixed approach, focusing on an apex predator, ecological modeling and remote-sensing information, not only helps detect early population declines in large mammals, but is also useful to discuss the relevance of large predators as indicators and the efficiency of conservation measures. It can also be easily extrapolated and adapted in a timely manner, since important open-source data are increasingly available and relevant for large-scale and real-time monitoring of biodiversity.

Habitat Heterogeneity Variably Influences Habitat Selection by Wild Herbivores in a Semi-Arid Tropical Savanna Ecosystem

An understanding of the habitat selection patterns by wild herbivores is critical for adaptive management, particularly towards ecosystem management and wildlife conservation in semi arid savanna ecosystems. We tested the following predictions: (i) surface water availability, habitat quality and human presence have a strong influence on the spatial distribution of wild herbivores in the dry season, (ii) habitat suitability for large herbivores would be higher compared to medium-sized herbivores in the dry season, and (iii) spatial extent of suitable habitats for wild herbivores will be different between years, i.e., 2006 and 2010, in Matetsi Safari Area, Zimbabwe. MaxEnt modeling was done to determine the habitat suitability of large herbivores and medium-sized herbivores. MaxEnt modeling of habitat suitability for large herbivores using the environmental variables was successful for the selected species in 2006 and 2010, except for elephant (Loxodonta africana) for the year 2010. Overall, large herbivores probability of occurrence was mostly influenced by distance from rivers. Distance from roads influenced much of the variability in the probability of occurrence of medium-sized herbivores. The overall predicted area for large and medium-sized herbivores was not different. Large herbivores may not necessarily utilize larger habitat patches over medium-sized herbivores due to the habitat homogenizing effect of water provisioning. Effect of surface water availability, proximity to riverine ecosystems and roads on habitat suitability of large and medium-sized herbivores in the dry season was highly variable thus could change from one year to another. We recommend adaptive management initiatives aimed at ensuring dynamic water supply in protected areas through temporal closure and or opening of water points to promote heterogeneity of wildlife habitats.

Patchiness of forest landscape can predict species distribution better than abundance: the case of a forest-dwelling passerine, the short-toed treecreeper, in central Italy

Environmental heterogeneity affects not only the distribution of a species but also its local abundance. High heterogeneity due to habitat alteration and fragmentation can influence the realized niche of a species, lowering habitat suitability as well as reducing local abundance. We investigate whether a relationship exists between habitat suitability and abundance and whether both are affected by fragmentation. Our aim was to assess the predictive power of such a relationship to derive advice for environmental management. As a model species we used a forest specialist, the short-toed treecreeper (Family: Certhiidae; Certhia brachydactyla Brehm, 1820), and sampled it in central Italy. Species distribution was modelled as a function of forest structure, productivity and fragmentation, while abundance was directly estimated in two central Italian forest stands. Different algorithms were implemented to model species distribution, employing 170 occurrence points provided mostly by the MITO2000 database: an artificial neural network, classification tree analysis, flexible discriminant analysis, generalized boosting models, generalized linear models, multivariate additive regression splines, maximum entropy and random forests. Abundance was estimated also considering detectability, through N-mixture models. Differences between forest stands in both abundance and habitat suitability were assessed as well as the existence of a relationship. Simpler algorithms resulted in higher goodness of fit than complex ones. Fragmentation was highly influential in determining potential distribution. Local abundance and habitat suitability differed significantly between the two forest stands, which were also significantly different in the degree of fragmentation. Regression showed that suitability has a weak significant effect in explaining increasing value of abundance. In particular, local abundances varied both at low and high suitability values. The study lends support to the concept that the degree of fragmentation can contribute to alter not only the suitability of an area for a species, but also its abundance. Even if the relationship between suitability and abundance can be used as an early warning of habitat deterioration, its weak predictive power needs further research. However, we define relationships between a species and some landscape features (i.e., fragmentation, extensive rejuvenation of forests and tree plantations) which could be easily controlled by appropriate forest management planning to enhance environmental suitability, at least in an area possessing high conservation and biodiversity values.

Realized niche shift associated with the Eurasian charophyte Nitellopsis obtusa becoming invasive in North America

Nitellopsis obtusa (starry stonewort) is a dioecious green alga native to Europe and Asia that has emerged as an aquatic invasive species in North America. Nitellopsis obtusa is rare across large portions of its native range, but has spread rapidly in northern-tier lakes in the United States, where it can interfere with recreation and may displace native species. Little is known about the invasion ecology of N. obtusa, making it difficult to forecast future expansion. Using ecological niche modeling we investigated environmental variables associated with invasion risk. We used species records, climate data, and remotely sensed environmental variables to characterize the species’ multidimensional distribution. We found that N. obtusa is exploiting novel ecological niche space in its introduced range, which may help explain its invasiveness. While the fundamental niche of N. obtusa may be stable, there appears to have been a shift in its realized niche associated with invasion in North America. Large portions of the United States are predicted to constitute highly suitable habitat for N. obtusa. Our results can inform early detection and rapid response efforts targeting N. obtusa and provide testable estimates of the physiological tolerances of this species as a baseline for future empirical research.

Assessing the umbrella value of a range-wide conservation network for jaguars (Panthera onca)

Umbrella species are employed as conservation short-cuts for the design of reserves or reserve networks. However, empirical data on the effectiveness of umbrellas is equivocal, which has prevented more widespread application of this conservation strategy. We perform a novel, large-scale evaluation of umbrella species by assessing the potential umbrella value of a jaguar (Panthera onca) conservation network (consisting of viable populations and corridors) that extends from Mexico to Argentina. Using species richness, habitat quality, and fragmentation indices of ~1500 co-occurring mammal species, we show that jaguar populations and corridors overlap a substantial amount and percentage of high-quality habitat for co-occurring mammals and that the jaguar network performs better than random networks in protecting high-quality, interior habitat. Significantly, the effectiveness of the jaguar network as an umbrella would not have been noticeable had we focused on species richness as our sole metric of umbrella utility. Substantial inter-order variability existed, indicating the need for complementary conservation strategies for certain groups of mammals. We offer several reasons for the positive result we document, including the large spatial scale of our analysis and our focus on multiple metrics of umbrella effectiveness. Taken together, our results demonstrate that a regional, single-species conservation strategy can serve as an effective umbrella for the larger community and should help conserve viable populations and connectivity for a suite of co-occurring mammals. Current and future range-wide planning exercises for other large predators may therefore have important umbrella benefits.

Potential Implications of Climate Change on Aegilops Species Distribution: Sympatry of These Crop Wild Relatives with the Major European Crop Triticum aestivum and Conservation Issues

Gene flow from crop to wild relatives is a common phenomenon which can lead to reduced adaptation of the wild relatives to natural ecosystems and/or increased adaptation to agrosystems (weediness). With global warming, wild relative distributions will likely change, thus modifying the width and/or location of co-occurrence zones where crop-wild hybridization events could occur (sympatry). This study investigates current and 2050 projected changes in sympatry levels between cultivated wheat and six of the most common Aegilops species in Europe. Projections were generated using MaxEnt on presence-only data, bioclimatic variables, and considering two migration hypotheses and two 2050 climate scenarios (RCP4.5 and RCP8.5). Overall, a general decline in suitable climatic conditions for Aegilops species outside the European zone and a parallel increase in Europe were predicted. If no migration could occur, the decline was predicted to be more acute outside than within the European zone. The potential sympatry level in Europe by 2050 was predicted to increase at a higher rate than species richness, and most expansions were predicted to occur in three countries, which are currently among the top four wheat producers in Europe: Russia, France and Ukraine. The results are also discussed with regard to conservation issues of these crop wild relatives.

The Impact of Global Climate Change on the Geographic Distribution and Sustainable Harvest of Hancornia speciosa Gomes (Apocynaceae) in Brazil

The global Climate change may affect biodiversity and the functioning of ecosystems by changing the appropriate locations for the development and establishment of the species. The Hancornia speciosa, popularly called Mangaba, is a plant species that has potential commercial value and contributes to rural economic activities in Brazil. The aim of this study was to evaluate the impact of global climate change on the potential geographic distribution, productivity, and value of production of H. speciosa in Brazil. We used MaxEnt to estimate the potential geographic distribution of the species in current and future (2050) climate scenarios. We obtained the productivity and value of production for 74 municipalities in Brazil. Moreover, to explain the variation the productivity and value of production, we constructed 15 models based on four variables: two ecological (ecological niche model and the presence of Unity of conservation) and two socio-economic (gross domestic product and human developed index). The models were selected using Akaike Information Criteria. Our results suggest that municipalities currently harvesting H. speciosa will have lower harvest rates in the future (mainly in northeastern Brazil). The best model to explain the productivity was ecological niche model; thus, municipalities with higher productivity are inserted in regions with higher environmental suitability (indicated by niche model). Thus, in the future, the municipalities harvesting H. speciosa will produce less because there will be less suitable habitat for H. speciosa, which in turn will affect the H. speciosa harvest and the local economy.

Trends and biases in global scientific literature about ecological niche models

Abstract Recently, ecological niche models have been employed to investigate the potential geographical distribution of species. However, it is necessary to analyze the vast number of publications on this topic to understand the trends and biases of research using ecological niche models (ENMs). Therefore, this study aims to investigate trends in the scientific literature regarding studies on ENMs. For the quantitative analysis of the literature on ENMs, we performed a search in the Thomson ISI (Web of Science) database between 1991 and 2013. The search identified 3042 papers containing preselected keywords in either the title or abstract. The results showed that the number of papers has increased over the years (r=0.77, P<0.001), with a sharp increase in recent years, highlighting the widespread use of the ENMs. There was an increase in the diversity of journals that published papers about ENMs (r=0.97, P<0.001). The research was conducted in different countries, predominantly the United States of America (550 papers), and the most commonly used method was the Maximum Entropy method (312 papers). Regarding the taxonomic group, most research has been conducted on plants (402 papers, or 28.36% of the total). There was no relationship between the modeling method used and the taxonomic group studied (χ2=4.8, P=0.15). Finally, the wide availability of biological, environmental and computational resources has elicited the broad use of tools for ENMs. Despite the conceptual discussions of the ENMs, this method is currently the most effective way to evaluate the potential geographical distribution of species, and to predict the distribution under different environmental conditions (i.e., future or past scenarios).

Using Range-Wide Abundance Modeling to Identify Key Conservation Areas for the Micro-Endemic Bolson Tortoise (Gopherus flavomarginatus)

A widespread biogeographic pattern in nature is that population abundance is not uniform across the geographic range of species: most occurrence sites have relatively low numbers, whereas a few places contain orders of magnitude more individuals. The Bolson tortoise Gopherus flavomarginatus is endemic to a small region of the Chihuahuan Desert in Mexico, where habitat deterioration threatens this species with extinction. In this study we combined field burrows counts and the approach for modeling species abundance based on calculating the distance to the niche centroid to obtain range-wide abundance estimates. For the Bolson tortoise, we found a robust, negative relationship between observed burrows abundance and distance to the niche centroid, with a predictive capacity of 71%. Based on these results we identified four priority areas for the conservation of this microendemic and threatened tortoise. We conclude that this approach may be a useful approximation for identifying key areas for sampling and conservation efforts in elusive and rare species.

Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account

The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.