Predicting Species Distribution and Conserving Rosewood Tree Under Global Climate Change Scenarios

Dengue and chikungunya are increasing global public health concerns due to their rapid geographical spread and increasing disease burden. Knowledge of the contemporary distribution of their shared vectors, Aedes aegypti and Aedes albopictus remains incomplete and is complicated by an ongoing range expansion fuelled by increased global trade and travel. Mapping the global distribution of these vectors and the geographical determinants of their ranges is essential for public health planning. Here we compile the largest contemporary database for both species and pair it with relevant environmental variables predicting their global distribution. We show Aedes distributions to be the widest ever recorded; now extensive in all continents, including North America and Europe. These maps will help define the spatial limits of current autochthonous transmission of dengue and chikungunya viruses. It is only with this kind of rigorous entomological baseline that we can hope to project future health impacts of these viruses.DOI: http://dx.doi.org/10.7554/eLife.08347.001

The negative effects of land-use changes on biodiversity significantly contribute to climate change. Primates are among the animals most affected by these changes, because of their high dependence on forest cover where a lack of forest connectivity can limit their dispersal and segregate their populations. In this sense, protected areas (PAs) are crucial for conserving endangered primates, especially endemic species. Using species distribution models, we assessed the impact of climate change and deforestation on the geographic distribution of 35 endangered Brazilian primates. We also evaluated the potential of PAs to retain suitable habitats for primate species under current conditions (baseline) and four future climate scenarios (optimistic and pessimistic, both for the periods 2041–2060 and 2061–2080), as well as the capacity of PAs to preserve species’ geographic representation both now and in the future. Our findings indicate that most primate taxa would experience a significant loss of suitable area (> 90%) in both pessimistic and optimistic scenarios. For future scenarios, the loss could exceed 98% for 10 taxa, particularly Amazonian species. Regarding PAs potential to retain suitable areas for maintaining the richness of threatened primates, only 8.6% harbor more species than expected by chance (1–6 taxa) in the baseline conditions, with a decrease in future scenarios. Results suggest that taxa already threatened with extinction are inadequately protected by PAs in the baseline conditions and even less so in future scenarios. Given the restricted geographic distribution and current population decline for most taxa, we emphasize the need to increase the number of PAs to ensure population viability and prevent future extinction.

Data shortfalls on species distribution affect species differently, but it is frequent among insects. Species distribution models (SDMs) are important tools to fill biogeographic deficits and provide support for practical conservation actions, particularly for cryptic or hard to survey species. We employed SDMs to evaluate one such species, the long-horned beetle (Macrodontia cervicornis), listed as ‘vulnerable’ in the IUCN’s Red List of Threatened Species. Given new distributional data for this species, we applied three different SDMs to: (1) provide the first assessment of this species’ distribution and potential dispersal routes; (2) evaluate the effectiveness of the current South American protected areas system for its conservation; and (3) discuss its potential distribution, as well as historical, biogeographical, and taxonomic issues related to it. Our models reached fair True Skilled Statistics values (TSS > 0.5), with the core area for M. cervicornis located in the Amazon forest, although suitable areas were also predicted along the Atlantic forest. Areas in the dry diagonal South American corridor (dry biomes of Cerrado, Caatinga, and Pampas) in South America were not predicted as suitable. The preference of M. cervicornis for humid areas with high temperatures may guarantee a better physiological control for dehydration, considering that large insects are more affected by water loss. In general, approximately 15 % of the distribution of M. cervicornis is in humid protected areas. The disconnected distribution of the long-horned beetle may be an indication of the existence of cryptic species under the same classification. We suggest that similar studies with other insect groups (e.g. butterflies, bees) should be conducted to properly assess their distributions, conservation status, and responses to hot-humid gradients throughout South America.

It has been hypothesised that rivers serve as biogeographic barriers and Pleistocene forest refuges may explain the rich species diversity observed within Neotropical rainforests. The lack of correspondence between Amazonian and Atlantic forest species in South America is a good model for testing such hypotheses. We used molecular, ancestral area reconstruction, and potential paleodistribution analyses of Chiroxiphia pareola to test above hypotheses and examine the diversification and/or geographical expansion of populations. Six genes, two mitochondrial and four nuclear, were analysed. All population splits were estimated to have occurred in the Pliocene–Pleistocene period, and the occurrence of an Amazon population split was supported by historical river dynamics. Amazonian populations were not monophyletic, and the eastern Amazonian cluster was a sister of the Atlantic Forest population. Molecular divergence occurring between the Amazonian and Atlantic forest populations was low when compared to splits between the lineages separated by Amazonian rivers. During the early to middle Pleistocene era, regions associated with mountain slopes and riverbanks connected the Amazonian and Atlantic Forest populations near the interior of the Brazilian Northeast semiarid region, which might have facilitated species dispersal from Amazonia into the Atlantic Forest. After this point, the populations were separated, and the Atlantic Forest population remained stable until the end of the Pleistocene and Holocene eras when short-range expansion and demographic growth occurred. Our results provide evidence that highlights the role of rivers and historical climate change in the diversification of Amazonian and Atlantic Forest bird species through the Plio-Pleistocene era.

Summary Remote sensing techniques offer an opportunity to improve biodiversity modelling and prediction world‐wide. Yet, to date, the weather station‐based WorldClim data set has been the primary source of temperature and precipitation information used in correlative species distribution models. WorldClim consists of grids interpolated from in situ station data recorded primarily from 1960 to 1990. Those data sets suffer from uneven geographic coverage, with many areas of Earth poorly represented. Here, we compare two remote sensing data sources for the purposes of biodiversity prediction: MERRA climate reanalysis data and AMSR‐E, a pure remote sensing data source. We use these data to generate novel temperature‐based bioclimatic information and to model the distributions of 20 species of vertebrates endemic to four regions of South America: Amazonia, the Atlantic Forest, the Cerrado and Patagonia. We compare the bioclimatic data sets derived from MERRA and AMSR‐E information with in situ station data and contrast species distribution models based on these two products to models built with WorldClim. Surface temperature estimates provided by MERRA and AMSR‐E showed warm temperature biases relative to the in situ data fields, but the reliability of these data sets varied in geographic space. Species distribution models derived from the MERRA data performed equally well (in Cerrado, Amazonia and Patagonia) or better (Atlantic Forest) than models built with the WorldClim data. In contrast, the performance of models constructed with the AMSR‐E data was similar to (Amazonia, Atlantic Forest, Cerrado) or worse than (Patagonia) that of models built with WorldClim data. Whereas this initial comparison assessed only temperature fields, efforts to estimate precipitation from remote sensing information hold great promise; furthermore, other environmental data sets with higher spatial and temporal fidelity may improve upon these results.

BackgroundCarnivore mammals are animals vulnerable to human interference, such as climate change and deforestation. Their distribution and persistence are affected by such impacts, mainly in tropical regions such as the Amazon. Due to the importance of carnivores in the maintenance and functioning of the ecosystem, they are extremely important animals for conservation. We evaluated the impact of climate change on the geographic distribution of carnivores in the Amazon using Species Distribution Models (SDMs). Do we seek to answer the following questions: (1) What is the effect of climate change on the distribution of carnivores in the Amazon? (2) Will carnivore species lose or gain representation within the Protected Areas (PAs) of the Amazon in the future?MethodsWe evaluated the distribution area of 16 species of carnivores mammals in the Amazon, based on two future climate scenarios (RCP 4.5 and RCP 8.5) for the year 2070. For the construction of the SDMs we used bioclimatic and vegetation cover variables (land type). Based on these models, we calculated the area loss and climate suitability of the species, as well as the effectiveness of the protected areas inserted in the Amazon. We estimated the effectiveness of PAs on the individual persistence of carnivores in the future, for this, we used the SDMs to perform the gap analysis. Finally, we analyze the effectiveness of PAs in protecting taxonomic richness in future scenarios.ResultsThe SDMs showed satisfactory predictive performance, with Jaccard values above 0.85 and AUC above 0.91 for all species. In the present and for the future climate scenarios, we observe a reduction of potencial distribution in both future scenarios (RCP4.5 and RCP8.5), where five species will be negatively affected by climate change in the RCP 4.5 future scenario and eight in the RCP 8.5 scenario. The remaining species stay stable in terms of total area. All species in the study showed a loss of climatic suitability. Some species lost almost all climatic suitability in the RCP 8.5 scenario. According to the GAP analysis, all species are protected within the PAs both in the current scenario and in both future climate scenarios. From the null models, we found that in all climate scenarios, the PAs are not efficient in protecting species richness.

Climate change is threatening several montane species across the world, including a large number of endemics, needing the development of forward-looking conservation strategies to foster their future survival. In this context, Species Distribution Models (SDMs) represent a useful method to forecast changes in species’ habitat suitability under different scenarios of global warming, often advising conservation frameworks with credible, defensible and repeatable information. In this paper, we estimate the environmental and bioclimatic suitability for an endemic mountain amphibian (Salamandra lanzai) in the western European Alps through an SDM approach, considering both current and future scenarios, to address short- and long-term management and conservation actions, and to update the current IUCN extinction risk assessment. The ensemble model forecasts predict a dramatic decline of the climatically suitable area for the Lanza’s alpine salamander in the next 20–40 years, even considering an optimistic CO2 emissions scenario, leading to a theoretical extinction of this species in 2100 in case the worst global warming prediction will be actualised. This underlines the urgent need for up-to-date conservation and management strategies to ensure the successful mitigation of climate change effects on S. lanzai, especially by adapting and improving the network of protected areas, immediately removing additional threats and identifying possible management actions able to increase fine-scale habitat suitability and connectivity among populations. In addition, a significant range contraction in the future has to be considered when assessing the extinction risk for this species, possibly exacerbating the effect of other threatening factors, such as the spread of lethal pathogens. Keywords: Salamandra lanzai, ensemble models, environmental suitability, bioclimatic suitability, future projections

The emergence of the diagonal of open/dry vegetations, including Chaco, Cerrado and Caatinga, is suggested to have acted as a dispersal barrier for terrestrial organisms by fragmenting a single large forest that existed in South America into the present Atlantic and Amazon forests. Here we tested the hypothesis that the expansion of the South American diagonal of open/dry landscapes acted as a vicariant process for forest lanceheads of the genus Bothrops, by analyzing the temporal range dynamics of those snakes. We estimated ancestral geographic ranges of the focal lancehead clade and its sister clade using a Bayesian dated phylogeny and the BioGeoBEARS package. We compared nine Maximum Likelihood models to infer ancestral range probabilities and their related biogeographic processes. The best fitting models (DECTS and DIVALIKETS) recovered the ancestor of our focal clade in the Amazon biogeographic region of northwestern South America. Vicariant processes in two different subclades resulted in disjunct geographic distributions in the Amazon and the Atlantic Forest. Dispersal processes must have occurred mostly within the Amazon and the Atlantic Forest and not between them. Our results suggest the fragmentation of a single ancient large forest into the Atlantic and Amazon forests acting as a driver of vicariant processes for the snake lineage studied, highlighting the importance of the diagonal of open/dry landscapes in shaping distribution patterns of terrestrial biota in South America.

The emergence of the diagonal of open/dry vegetations, including Chaco, Cerrado and Caatinga, is suggested to have acted as a dispersal barrier for terrestrial organisms by fragmenting a single large forest that existed in South America into the present Atlantic and Amazon forests. Here we tested the hypothesis that the expansion of the South American diagonal of open/dry landscapes acted as a vicariant process for forest lanceheads of the genus Bothrops, by analyzing the temporal range dynamics of those snakes. We estimated ancestral geographic ranges of the focal lancehead clade and its sister clade using a Bayesian dated phylogeny and the BioGeoBEARS package. We compared nine Maximum Likelihood models to infer ancestral range probabilities and their related biogeographic processes. The best fitting models (DECTS and DIVALIKETS) recovered the ancestor of our focal clade in the Amazon biogeographic region of northwestern South America. Vicariant processes in two different subclades resulted in disjunct geographic distributions in the Amazon and the Atlantic Forest. Dispersal processes must have occurred mostly within the Amazon and the Atlantic Forest and not between them. Our results suggest the fragmentation of a single ancient large forest into the Atlantic and Amazon forests acting as a driver of vicariant processes for the snake lineage studied, highlighting the importance of the diagonal of open/dry landscapes in shaping distribution patterns of terrestrial biota in South America.

The use of species distribution models (SDMs) to predict local abundance has been often proposed and contested. We tested whether SDMs at different spatiotemporal resolutions may predict the local density of 14 bird species of open/semi-open habitats. SDMs were built at 1 ha and 1 km, and with long-term versus a mix of current and long-term climatic variables. The estimated environmental suitability was used to predict local abundance obtained by means of 275 linear transects. We tested SDM ability to predict abundance for all sampled sites versus occurrence sites, using N-mixture models to account for imperfect detection. Then, we related the R2 of N-mixture models to SDM traits. Fine-grain SDMs appeared generally more robust than large-grain ones. Considering the all-transects models, for all species environmental suitability displayed a positive and highly significant effect at all the four combinations of spatial and temporal grains. When focusing only on occurrence transects, at the 1 km grain only one species showed a significant and positive effect. At the 1 ha grain, 62% of species models showed (over both climatic sets) a significant or nearly significant positive effect of environmental suitability on abundance. Grain was the only factor significantly affecting the model's explanatory power: 1 km grain led to lower amounts of variation explained by models. Our work re-opens the debate about predicting abundance using SDM-derived suitability, emphasizing the importance of grains and of spatiotemporal resolution more in general. The incorporation of local variables into SDMs at fine grains is key to predict local abundance. SDMs worked out at really fine grains, approaching the average size of territory or home range of target species, are needed to predict local abundance effectively. This may result from the fact that each single cell may represent a potential territory/home range, and hence a higher suitability over a given area means that more potential territories occur there.

Climate change is suggested to be one of the possible drivers of decline in pollinators. In this paper, we applied an ecological niche model to modeling distributional responses in face of climate changes for the subspecies of Melipona quadrifasciata Lepeletier. This species is divided into two subspecies based on difference in the yellow tergal stripes, which are continuous in M. q. quadrifasciata and interrupted in M. q. anthidioides. The geographic distribution of each subspecies is also distinct. M. q. quadrifasciata is found in colder regions in the Southern states of Brazil, whereas M. q. anthidioides is found in habitats with higher temperatures, suggesting that ecological features, such as adaption to distinct climatic conditions may take place. Thus, the possibility of having diff erent responses in geographic range shifts to future climate scenario would be expected. This study aimed to investigate the eff ects of climate changes on the distribution of the two M. quadrifasciata subspecies in Brazil, using an ecological niche model by the MaxEnt algorithm. Our results indicate that the subspecies showed clear diff erences in geographic shift patterns and increased climate niche overlap in the future scenarios. M. q. anthidioides will have the potential for an increase of suitable climatic conditinos in the Atlantic Forest, and towards the Pampa biome, while M. q. quadrifasciata will suffer a reduction of adequate habitats in almost all of its current geographic distribution. Given the potential adverse eff ects of climate changes for this subspecies, conservation actions are urgently needed to avoid that it goes extinct.

The most common approach to predicting how species ranges and ecological functions will shift with climate change is to construct correlative species distribution models (SDMs). These models use a species’ climatic distribution to determine currently suitable areas for the species and project its potential distribution under future climate scenarios. A core, rarely tested, assumption of SDMs is that all populations will respond equivalently to climate. Few studies have examined this assumption, and those that have rarely dissect the reasons for intraspecific differences. Focusing on the arctic‐alpine cushion plant Silene acaulis, we compared predictive accuracy from SDMs constructed using the species’ full global distribution with composite predictions from separate SDMs constructed using subpopulations defined either by genetic or habitat differences. This is one of the first studies to compare multiple ways of constructing intraspecific‐level SDMs with a species‐level SDM. We also examine the contested relationship between relative probability of occurrence and species performance or ecological function, testing if SDM output can predict individual performance (plant size) and biotic interactions (facilitation). We found that both genetic‐ and habitat‐informed SDMs are considerably more accurate than a species‐level SDM, and that the genetic model substantially differs from and outperforms the habitat model. While SDMs have been used to infer population performance and possibly even biotic interactions, in our system these relationships were extremely weak. Our results indicate that individual subpopulations may respond differently to climate, although we discuss and explore several alternative explanations for the superior performance of intraspecific‐level SDMs. We emphasize the need to carefully examine how to best define intraspecific‐level SDMs as well as how potential genetic, environmental, or sampling variation within species ranges can critically affect SDM predictions. We urge caution in inferring population performance or biotic interactions from SDM predictions, as these often‐assumed relationships are not supported in our study.

ABSTRACTAimClimate change represents one of the main threats to global biodiversity, and such alterations are expected to induce shifts in distribution ranges and diversity patterns. We evaluate if protected areas and forest remnants in the Atlantic Forest in South America (AF) are projected to ensure the taxonomic diversity (TD) and phylogenetic diversity (PD) of non‐volant small mammals under scenarios of future climate change.LocationAtlantic Forest (AF), South America.MethodsWe used Species Distribution Modelling (SDMs) through an ensemble approach to assess the potential distribution of 101 species of small mammals using present (1979–2013) and future (2050 and 2070) climate scenarios. We consider optimistic and pessimistic greenhouse gas concentration scenarios (SSP370 and SSP585). We accessed TD through the sum of the suitable areas vs. areas of low or unknown suitability distribution maps for each species and PD using the sum of the branch lengths of a phylogenetic tree spatialised.ResultsOur models suggest that climate change is likely to reduce the suitable climatic areas for small mammals in the AF. The shrinkage in the potential distribution is projected to lead to high loss of TD and PD. The southeastern region of the Atlantic Forest is likely to experience the most pronounced decline in PD, while some small areas in the southern Atlantic Forest are projected to increase PD in the future.Main ConclusionsOur models suggest a strong decline in TD and in PD from biodiversity hotspot regions in the AF under climate change scenarios. Since small mammals have low dispersal ability, and because most of the AF is highly fragmented, it is unlikely that this biome will sustain small mammal biodiversity in the future.

Assessing the vulnerability of Thailand's forest birds to global change

The threatened thin-spined porcupine (Chaetomys subspinosus), a forest-specialist endemic to the Brazilian Atlantic forest, was rarely detected in the wild during the 20th century. Previous geographic distribution assessments were carried out nearly three decades ago and were based on interview data. We performed extensive field surveys (based on active search and interviews), a literature review, and species distribution modeling to predict and validate a more reliable picture of its geographic distribution and environmental suitability gradient. We identified the main predictors of species’ incidence, its conservation status, and pinpointed key areas for species conservation. Our results indicated that C. subspinosus is distributed continuously in the Atlantic forest from southeastern Espirito Santo to central-eastern Sergipe state, totaling 104,326 km2 of occurrence area, although only 3,299 km2 (13.3%) is currently represented by native forests (species habitat). C. subspinosus was absent or at least so rare that it was not detected in more than half of the locations sampled by interviews (53.5%). Our results suggest that populations are sensitive to climatic conditions and habitat loss, becoming abruptly rarer when the remaining forest cover reaches less than 10% area within a region (~ 5,000 km2 scale). This result indicates that the high deforestation level of the Atlantic forest is already close to the limit of regional species resistance. Bahia state still harbors the bulk of the remaining forest with high climatic suitability, and generally under low levels of legal protection. Herein we highlight priority areas and research gaps that could guide decision makers to promote conservation strategies for this threatened species.