Limitations to the Use of Species-Distribution Models for Environmental-Impact Assessments in the Amazon

Biogeography and environmental preferences of Butia yatay (Mart.) Becc

During the Quaternary, Chaco Phytogeographic Domain (Chaco) flora in subtropical South America experienced temperature and humidity fluctuations, primarily driven by wind dynamics, leading to significant shifts in species distribution. The palm Butia yatay is endemic to the Chaco and thrives in areas characterized by a warm-rainy climate and mostly restricted to sandy soils. To investigate the current geographic distribution of suitable habitat for B. yatay while assessing the significance of soil variables, we employed two distinct algorithms in species distribution modeling (SDM). We also determined whether the distribution of B. yatay has changed since the Pleistocene and whether these changes align with previously proposed Pleistocene refugia. In the present SDMs, we considered two separate sets of predictors, one set with bioclimatic variables only and the other set with bioclimatic topographic and soil variables. Additionally, we reconstructed the historical geographic distribution of suitable habitats using bioclimatic data. Our results suggested that the primary determinants of B. yatay's current distribution include precipitation and temperature of the driest month and soil cation exchange capacity. Incorporating soil variables affected the estimated size and range of suitable areas. Projections into the past indicated similar suitable habitat distributions during interglacial periods compared with the present. During the Last Glacial Maximum, climatically suitable habitat may have shifted northward, partially overlapping with previously suggested Pleistocene refugia located between the Paraná and Uruguay Rivers. These findings indicate the main factors driving the distribution and ecology of B. yatay and enhance understanding of subtropical flora shifts during the Quaternary. The approach also may prove valuable for other studies within the Chaco.

Hydropower Plants as Dispersal Barriers in Freshwater Species Distribution Models: Using Restrictions through Asymmetrical Dispersal Predictors

Hydropower plants represent one of the greatest threats for freshwater fish by fragmenting the habitat and avoiding the species dispersal. This type of dispersal barrier is often disregarded when predicting freshwater species distribution due to the complexity in inserting the species dispersal routes, and thus the barriers, into the models. Here, we evaluate the impact of including hydroelectric dams into species distribution models through asymmetrical dispersal predictors on the predicted geographic distribution of freshwater fish species. For this, we used asymmetrical dispersal (i.e., AEM) as predictors for modeling the distribution of 29 native fish species of Tocantins-Araguaia River basin. After that, we included the hydropower power plant (HPP) location into the asymmetrical binary matrix for the AEM construction by removing the connections where the HPP is located, representing the downstream disconnection a dam causes in the fish species dispersal route. Besides having higher predicted accuracy, the models using the HPP information generated more realistic predictions, avoiding overpredictions to areas suitable but limited to the species dispersal due to an anthropic barrier. Furthermore, the predictions including HPPs showed higher loss of species richness and nestedness (i.e., loss of species instead of replacement), especially for the southeastern area which concentrates most planned and built HPPs. Therefore, using dispersal constraints in species distribution models increases the reliability of the predictions by avoiding overpredictions based on premise of complete access by the species to any area that is climatically suitable regardless of dispersal barriers or capacity. In conclusion, in this study, we use a novel method of including dispersal constraints into distribution models through a priori insertion of their location within the asymmetrical dispersal predictors, avoiding a posteriori adjustment of the predicted distribution.

Past, present, and future predictions on the suitable habitat of the Slender racer (Orientocoluber spinalis) using species distribution models

Species distribution models (SDMs) across past, present, and future timelines provide insights into the current distribution of these species and their reaction to climate change. Specifically, if a species is threatened or not well-known, the information may be critical to understand that species. In this study, we computed SDMs for Orientocoluber spinalis, a monotypic snake genus found in central and northeast Asia, across the past (last interglacial, last glacial maximum, and mid-Holocene), present, and future (2070s). The goal of the study was to understand the shifts in distribution across time, and the climatic factors primarily affecting the distribution of the species. We found the suitable habitat of O. spinalis to be persistently located in cold-dry winter and hot summer climatic areas where annual mean temperature, isothermality, and annual mean precipitation were important for suitable habitat conditions. Since the last glacial maximum, the suitable habitat of the species has consistently shifted northward. Despite the increase in suitable habitat, the rapid alterations in weather regimes because of climate change in the near future are likely to greatly threaten the southern populations of O. spinalis, especially in South Korea and China. To cope with such potential future threats, understanding the ecological requirements of the species and developing conservation plans are urgently needed.

Delineating Functional Corridors Linking Leopard Habitat in the Eastern and Western Cape, South Africa

Natural landscapes are increasingly fragmented due to human activity. This contributes to isolation and inadequate gene flow among wildlife populations. These threats intensify where populations are already low, and gene flow is compromised. Ensuring habitat connectivity despite transformed landscapes can mitigate these risks. Leopards are associated with high levels of biodiversity and are the last widely occurring, free-roaming apex predator in South Africa. Although highly adaptable, leopard survival is reduced by human-caused mortality and habitat destruction. We aimed to assess the connectivity of leopard habitat in the Eastern Cape and Western Cape, South Africa. We predicted leopard habitat by correlating GPS data from 31 leopards to environmental features that included human-associated and natural landscapes. We used circuit theory to delineate corridors linking known leopard populations. Finally, using camera traps, we tested whether five predicted corridors were used by leopards. Leopard habitat was strongly correlated to moderate slopes and areas of natural land-cover and plantations, highlighting mountainous areas as important habitat with high connectivity probability. While most habitat patches showed some level of connectivity, leopards avoided highly transformed landscapes, potentially isolating some populations. Where corridors are not functional, active conservation measures for species connectivity becomes important.

Predicting the Potential Distribution of Non-Native Mammalian Species Sold in the South African Pet Trade

The pet trade is one of the main pathways of introduction of several mammals worldwide. In South Africa, non-native mammalian species are traded as pets, and so far, only four of these species are considered invasive. We used a list of 24 companion mammalian species compiled from a previous study. We selected a subset of 14 species for species distribution modeling (SDM) based on their trade popularity, invasion history and potential economic and socio-economic impacts. We aimed to estimate their potential distribution using their distribution records. Our SDM indicated that climate in South Africa was suitable for most traded species. However, commonly and easily available species had the broadest areas of suitable climates, such as house mice (Mus musculus) and Norwegian rats (Rattus norvegicus). In addition, the model with a human footprint suggested a high risk of invasion for Norwegian rats but less for house mice distribution. This assessment suggests the need of strict trade regulations and management strategies for pet mammals with broader suitability, which are already invasive, and most available for sale. In addition, our results provide a baseline approach that can be used to identify mammalian pet species with a potential risk of invasion so that urgent preventive measures can be implemented.

Modeling impacts of climate change on the potential distribution of six endemic baobab species in Madagascar

Madagascar, a globally renowned biodiversity hotspot characterized by high rates of endemism, is one of the few remaining refugia for many plants and animal species. However, global climate change has greatly affected the natural ecosystem and endemic species living in Madagascar, and will likely continue to influence species distribution in the future. Madagascar is home to six endemic baobab (Adansonia spp., Bombacoideae [Malvaceae]) species (Adansonia grandidieri, A. suarezensis, A. madagascariensis, A. perrieri, A. rubrostipa, A. za), which are remarkable and endangered plants. This study aimed to model the current distribution of suitable habitat for each baobab species endemic to Madagascar and determine the effect that climate change will have on suitable baobab habitat by the years 2050 and 2070. The distribution was modeled using MaxEnt based on locality information of 245 occurrence sites of six species from both online database and our own field work. A total of seven climatic variables were used for the modeling process. The present distribution of all six Madagascar's baobabs was largely influenced by temperature-related factors. Although both expansion and contraction of suitable habitat are predicted for all species, loss of original suitable habitat is predicted to be extensive. For the most widespread Madagascar baobab, A. za, more than 40% of its original habitat is predicted to be lost because of climate change. Based on these findings, we recommend that areas predicted to contract in response to climate change should be designated key protection regions for baobab conservation.

Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis

Understanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring programs and studies must deliver information on a range of variables and factors, from taxonomic/functional diversity and spatial distribution of habitats, to anthropogenic stress indicators such as land use, fisheries use, and pollution. Effective monitoring programs must therefore integrate observations from different sources and spatial scales to provide a comprehensive view to managers. Here we explore integrating aerial surveys from a low-cost Remotely Piloted Aircraft System (RPAS) with concurrent underwater surveys to deliver a novel approach to coastal monitoring. We: (i) map depth and substrate of shallow rocky habitats, and; (ii) classify the major biotopes associated with these environmental axes; and (iii) combine data from i and ii to assess the likely distribution of common sessile organismal assemblages over the survey area. Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce spatially-explicit biotope maps.

Spatial epidemiology of yellow fever: Identification of determinants of the 2016-2018 epidemics and at-risk areas in Brazil

Optimise control strategies of infectious diseases, identify factors that favour the circulation of pathogens, and propose risk maps are crucial challenges for global health. Ecological niche modelling, once relying on an adequate framework and environmental descriptors can be a helpful tool for such purposes. Despite the existence of a vaccine, yellow fever (YF) is still a public health issue. Brazil faced massive sylvatic YF outbreaks from the end of 2016 up to mid-2018, but cases in human and non-human primates have been recorded until the beginning of 2020. Here we used both human and monkey confirmed YF cases from two epidemic periods (2016/2017 and 2017/2018) to describe the spatial distribution of the cases and explore how biotic and abiotic factors drive their occurrence. The distribution of YF cases largely overlaps for humans and monkeys, and a contraction of the spatial extent associated with a southward displacement is observed during the second period of the epidemics. More contributive variables to the spatiotemporal heterogeneity of cases were related to biotic factors (mammal richness), abiotic factors (temperature and precipitation), and some human-related variables (population density, human footprint, and human vaccination coverage). Both projections of the most favourable conditions showed similar trends with a contraction of the more at-risk areas. Once extrapolated at a large scale, the Amazon basin remains at lower risk, although surrounding forest regions and notably the North-West region, would face a higher risk. Spatial projections of infectious diseases often relied on climatic variables only; here for both models, we instead highlighted the importance of considering local biotic conditions, hosts vulnerability, social and epidemiological factors to run the spatial risk analysis correctly: all YF cases occurring later on, in 2019 and 2020, were observed in the predicted at-risk areas.

The Potential Distribution of Tree Species in Three Periods of Time under a Climate Change Scenario

Species distribution models have become some of the most important tools for assessment of impact of climatic change, impact of human activity and for the detection of failure in silvicultural or conservation management plans. In this study, we modeled the potential distribution of 13 tree species of temperate forests distributed in the Mexican state Durango in the Sierra Madre Occidental, for three periods of time. Models were constructed for each period of time using 19 climate variables from the MaxEnt (Maximum Entropy algorithm) modelling algorithm. Those constructed for the future used a severe climate change scenario. When comparing the potential areas of the periods, some species such as Pinus durangensis (Martínez), Pinus teocote (Schiede ex Schltdl. & Cham.) and Quercus crassifolia (Bonpl.) showed no drastic changes. Rather, the models projected a slight reduction, displacement or fragmentation in the potential area of Pinus arizonica (Engelm.), P. cembroides (Zucc), P. engelmanni (Carr), P. leiophylla (Schl), Quercus arizonica (Sarg), Q. magnolifolia (Née) and Q. sideroxila (Humb. & Bonpl.) in the future period. Thus, establishing conservation and reforestation strategies in the medium and long term could guarantee a wide distribution of these species in the future.

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

Ecological Niche Models (ENMs) are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann-Whitney U tests, Principal Components Analysis and General Linear Models). Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude) were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species) and taxonomy (amphibians and reptiles). Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural parks.