Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation

Conservation gaps for Brazilian bats, limited protection across conservation units and the importance of the indigenous lands

In Brazil, there is 13% of the world's bat diversity, is the second most diverse group of mammals, playing a crucial role in providing ecosystem services that benefit humans. However, anthropogenic disturbances exacerbate processes of species extinction, shifts in geographic distributions, and phenological changes, despite efforts to safeguard biodiversity through the creation of Conservation Units and Indigenous Lands. Moreover, gaps in taxonomic knowledge and challenges related to species distribution hinder the effective implementation of conservation strategies in protected areas. This study assesses the contribution of Brazilian Conservation Units (both Full Protection and Sustainable Use) and Indigenous Lands to the conservation of bat species and their ecosystem services. It also presents maps illustrating species richness by trophic guilds and threat classification according to IUCN, including species listed as Data Deficient. The findings reveal low percentages of potential bat distribution areas within these protected regions, especially for insectivorous, nectarivorous, and frugivorous bats in the Cerrado biome, which are classified as Near Threatened. Additionally, the highest bat species richness was observed in the Amazon and Atlantic Forest biomes.

Climate-induced distribution dynamics and niche adaptation of South Korean endemic plants across the Korean Peninsula

As climate change intensifies, endemic plants native to South Korea, especially those in specialized ecological niches, confront heightened risks of distribution shifts and habitat degradation. To provide a comprehensive understanding of these impacts, this study evaluates the climate-induced distribution dynamics and niche adaptation of these endemic species across the entire Korean Peninsula. Utilizing species distribution models (SDMs) for 179 plant species and incorporating environmental variables under projected future climate scenarios, our analysis identified unique distribution and niche adaptation patterns. Findings demonstrate that specialized endemic species are likely to migrate to higher altitudes and latitudes, highlighting their distinct vulnerability due to limited ecological niches. Our comparative approach underscores the necessity for refined conservation strategies that address the specific requirements of these endemic species, as opposed to those with wider distributions. This research offers valuable insights into biodiversity conservation amid climate change, proposing targeted actions such as the establishment of protected areas, habitat restoration, and the implementation of assisted migration strategies to safeguard these vital endemic plant species throughout the Korean Peninsula.

Distribution patterns and potential suitable habitat prediction of Ceracris kiangsu (Orthoptera: Arcypteridae) under climate change- a case study of China and Southeast Asia

Ceracris kiangsu (Orthoptera: Arcypteridae), is greatly affected by climatic factors and exhibits strong adaptability, posing a serious threat to the ecological environment. Therefore, predicting its potential suitable habitat distribution provides a proactive theoretical basis for pest control. This study using the Biomod2 package of R simulated and predicted the current and future potential distribution, area changes, changes in the center points of suitable habitats, and niche shifts of C. kiangsu under two different greenhouse gas emission scenarios, SSP1-26 and SSP5-85. The results show that: (1) Currently, the high suitability areas for C. kiangsu are mainly distributed in Yunnan, Jiangxi, Hunan provinces in southern China and phongsaly province in northern Laos. In the future, the center of the suitable habitat distribution pattern of C. kiangsu will remain unchanged, primarily expanding outward from medium and high suitability areas. Additionally, significant suitable habitats for C. kiangsu were discovered in Southeast Asian countries without previous pest records. (2) Compared to the present, the overall suitable habitat area for C. kiangsu is expected to expand, particularly under the SSP5-85 climate change scenario. (3) In the SSP1-26 and SSP5-85 climate scenarios, the geometric center of the suitable habitat generally shows a trend of gradually shifting northeast. (4) Under different climate scenarios, the suitable habitat of C. kiangsu has highly overlapping, indicating that the suitable habitat of C. kiangsu in the invaded areas is broader than in its native regions. In conclusion, the research findings represent a breakthrough in identifying the potential distribution areas of C. kiangsu, which is of great practical significance for the monitoring and control of C. kiangsu pest infestation in China and Southeast Asian countries.

Precipitation and temperature timings underlying bioclimatic variables rearrange under climate change globally

Modeling how climate change may affect the potential distribution of species and communities typically utilizes bioclimatic variables. Distribution predictions rely on the values of the bioclimatic variable (e.g., precipitation of the wettest quarter). However, the ecological meaning of most of these variables depends strongly on the within-year position of a specific climate period (SCP), for example, the wettest quarter of the year, which is often overlooked. Our aim was to determine how the within-year position of the SCPs would shift (SCP shift) in reaction to climate change in a global context. We calculated the deviations of the future within-year position of the SCPs relative to the reference period. We used four future time periods, four scenarios, and four CMIP6 global climate models (GCMs) to provide an ensemble of expectations regarding SCP shifts and locate the spatial hotspots of the shifts. Also, the size and frequency of the SCP shifts were subjected to linear models to evaluate the importance of the impact modeler's decision on time period, scenario, and GCM. We found ample examples of SCP shifts exceeding 2 months, with 6-month shifts being predicted as well. Many areas in the tropics are expected to experience both temperature and precipitation-related shifts, but precipitation-related shifts are abundantly predicted for the temperate and arctic zones as well. The combined shifts at the Equator reinforce the likelihood of the emergence of no-analogue climates there. The shifts become more pronounced as time and scenario progress, while GCMs could not be ranked in a clear order in this respect. For most SCPs, the modeler's decision on the GCM was the least important, while the choice of time period was typically more important than the choice of scenario. Future predictive distribution models should account for SCP shifts and incorporate the phenomenon in the modeling efforts.

Pushing the boundaries: actual and potential distribution of thrushes expanding their ranges in South America

The distribution of a species reflects its ecological adaptability and evolutionary history, which is shaped by the environment and represents a dynamic area subject to anthropogenic environmental change. We used the MaxEnt algorithm to construct ecological niche models for four thrush species within the Turdus genus; T. amaurochalinus, T. chiguanco, T. falcklandii and T. rufiventris. These models were used to predict the potential geographic distributions of these species that are expanding their ranges in South America. Using occurrence records, we estimated currently occupied areas for each species. We also identified suitable habitats and projected possible areas to be colonized by the four species at continental scale. Temperature annual range had the highest influence for T. falcklandii, while human modification was the main variable explaining the distribution of the other three species. The potential distribution area ranged from 2.5 million km2 for T. falcklandii to nearly seven million km2 for T. amaurochalinus. Large proportions of suitable area remain unoccupied by all four species, being 50% for T. amaurochalinus and T. rufiventris, and about 70% for T. chiguanco and T. falcklandii. Anthropogenic disturbances, such as habitat loss and ecosystem transformation, lead to non-random species extinction and biotic homogenization, highlighting the importance of predictive models as valuable tools for informing mitigation policies and conservation strategies. Thrushes are progressively expanding their ranges, and the colonization of new habitats could bring new challenges.

Future trends of marine fish biomass distributions from the North Sea to the Barents Sea

Climate warming is one of the facets of anthropogenic global change predicted to increase in the future, its magnitude depending on present-day decisions. The north Atlantic and Arctic Oceans are already undergoing community changes, with warmer-water species expanding northwards, and colder-water species retracting. However, the future extent and implications of these shifts remain unclear. Here, we fitted a joint species distribution model to occurrence data of 107, and biomass data of 61 marine fish species from 16,345 fishery independent trawls sampled between 2004 and 2022 in the northeast Atlantic Ocean, including the Barents Sea. We project overall increases in richness and declines in relative dominance in the community, and generalised increases in species' ranges and biomass across three different future scenarios in 2050 and 2100. The projected decline of capelin and the practical extirpation of polar cod from the system, the two most abundant species in the Barents Sea, drove an overall reduction in fish biomass at Arctic latitudes that is not replaced by expanding species. Furthermore, our projections suggest that Arctic demersal fish will be at high risk of extinction by the end of the century if no climate refugia is available at eastern latitudes.

Forest Orchids under Future Climate Scenarios: Habitat Suitability Modelling to Inform Conservation Strategies

Orchidaceae is one of the largest and most diverse families of flowering plants in the world but also one of the most threatened. Climate change is a global driver of plant distribution and may be the cause of their disappearance in some regions. Forest orchids are associated with specific biotic and abiotic environmental factors, that influence their local presence/absence. Changes in these conditions can lead to significant differences in species distribution. We studied three forest orchids belonging to different genera (Cephalanthera, Epipactis and Limodorum) for their potential current and future distribution in a protected area (PA) of the Northern Apennines. A Habitat Suitability Model was constructed for each species based on presence-only data and the Maximum Entropy algorithm (MaxEnt) was used for the modelling. Climatic, edaphic, topographic, anthropogenic and land cover variables were used as environmental predictors and processed in the model. The aim is to identify the environmental factors that most influence the current species distribution and the areas that are likely to contain habitats suitable for providing refuge for forest orchids and ensuring their survival under future scenarios. This will allow PA authorities to decide whether to invest more resources in conserving areas that are potential refuges for threatened species.

An Assessment of the Climate Change Impacts on the Distribution of the Glacial Relict Woodpecker Three-Toed Woodpecker Picoides tridactylus

The Three-Toed Woodpecker Picoides tridactylus is a rare and endangered woodpecker on the Balkan Peninsula. Despite being widely distributed in Northern Europe, its distribution on the Balkan Peninsula is limited to high-altitude forest habitats, where it represents a glacial relict. Assessing the climate change impacts on its distribution can be crucial for improving the conservation and future survival of this specialist species on the Balkan Peninsula. We used species distribution modelling (SDM) to identify its potential distribution in the past (last interglacial and last glacial maximum), present, and future (2050 and 2070). Our results indicate that this species had the greatest distribution during the last glacial maximum, after which its distribution contracted to areas where suitable environment persisted (high altitudes). The largest territory of the Balkan Peninsula has an unsuitable environment for the species to inhabit, while highly suitable habitats have the smallest share in the total area of suitable habitats. All future models show a decrease in the area of suitable habitats compared with the current period, indicating that global warming has a negative effect on the distribution of the species. We recommend that conservation activities must be of greater extent to ensure the species' survival in the Balkans.

Some bats are here: Reducing the Wallacean shortfall of bats in the amazon

The Amazon rainforest has approximately 23% of its sampled area dedicated to bats, making it one of the least sampled and most diverse regions for bats in Brazil. The lack of sampling results in a lack of knowledge regarding the accurate geographical distribution of bat species. This lack is referred to as the Wallacean shortfall, which should be addressed with primary data obtained from in situ collections. However, the use of Species Distribution Models (SDMs) can help alleviate this gap. The states of Pará and Acre are located in the Brazilian Amazon. So, our objective is to decrease the Wallacean shortfall concerning Amazonian bat species. To achieve this, we provide (i) a list of bat species sampled in the states of Pará and Acre in the last 5 years (2017 to 2022); (ii) the potential distribution of species considered as new occurrences for the region; and (iii) the potential distribution of species classified as Data Deficient (DD) and Near Threatened (NT) according to the IUCN classification. With 96 nights of collection and 129,600 m2h of mist netting, we obtained 75 bat species, with an estimated total of 94.78 species. Additionally, 21 species were considered as range extensions. The Brazilian Amazon region has a vast geographic expanse and few established research centers, resulting in a limited sampling of bats and other biological groups. Furthermore, we draw attention to the significant number of bat species with expanded geographical distributions, with 21 out of the 75 sampled species. This should be a reminder that primary biogeographic data is still necessary for the neotropical region.

Current and future scenarios of suitability and expansion of cassava brown streak disease, Bemisia tabaci species complex, and cassava planting in Africa

Cassava (Manihot esculenta) is among the most important staple crops globally, with an imperative role in supporting the Sustainable Development Goal of 'Zero hunger'. In sub-Saharan Africa, it is cultivated mainly by millions of subsistence farmers who depend directly on it for their socio-economic welfare. However, its yield in some regions has been threatened by several diseases, especially the cassava brown streak disease (CBSD). Changes in climatic conditions enhance the risk of the disease spreading to other planting regions. Here, we characterise the current and future distribution of cassava, CBSD and whitefly Bemisia tabaci species complex in Africa, using an ensemble of four species distribution models (SDMs): boosted regression trees, maximum entropy, generalised additive model, and multivariate adaptive regression splines, together with 28 environmental covariates. We collected 1,422 and 1,169 occurrence records for cassava and Bemisia tabaci species complex from the Global Biodiversity Information Facility and 750 CBSD occurrence records from published literature and systematic surveys in East Africa. Our results identified isothermality as having the highest contribution to the current distribution of cassava, while elevation was the top predictor of the current distribution of Bemisia tabaci species complex. Cassava harvested area and precipitation of the driest month contributed the most to explain the current distribution of CBSD outbreaks. The geographic distributions of these target species are also expected to shift under climate projection scenarios for two mid-century periods (2041-2060 and 2061-2080). Our results indicate that major cassava producers, like Cameron, Ivory Coast, Ghana, and Nigeria, are at greater risk of invasion of CBSD. These results highlight the need for firmer agricultural management and climate-change mitigation actions in Africa to combat new outbreaks and to contain the spread of CBSD.

Conservation units alone are insufficient to protect Brazilian Amazonian chelonians

The creation of protected areas (PAs) is not always based on science; consequently, some aquatic species may not receive the same level of protection as terrestrial ones. The objective of this study was to identify priority areas for the conservation of chelonians in the Brazilian Amazon basin and assess the contribution of PAs, distinguishing between Full Protection Areas, Sustainable Use Areas, and Indigenous Lands for group protection. The entire species modeling procedure was carried out using Species Distribution Models. Location records were obtained from platforms such as SpeciesLink, GBIF, the Hydroatlas database, and WorldClim for bioclimatic variables adjusted with algorithms like Maximum Entropy, Random Forest, Support Vector Machine, and Gaussian-Bayesian. Indigenous lands cover more than 50% of the distribution areas of chelonian species in the Brazilian Amazon. Protected areas with higher conservation importance (Full Protection Areas and Sustainable Use Areas) hold less than 15% of the combined species distribution. Researchers face significant challenges when making decisions with models, especially in conservation efforts involving diverse taxa that differ significantly from one another within a group of individuals.

Ecological niche modeling of two Microtheca Stål, 1860 species (Coleoptera: Chrysomelidae: Chrysomelinae) in the Americas: insights from Brassicaceae occurrence

Biological invasions pose significant threats to biodiversity, with invasive species spread often facilitated by human activities. Consequently, this research utilized ecological niche modeling (ENM) to overcome this limitation and map the potential suitability of Microtheca ochroloma Stål, 1860 and Microtheca semilaevis Stål, 1860, which have been evaluated as potential insect pests in the Americas, zones for four genera of Brassicaceae, which include globally cultivated species such as Sinapis L., Raphanus L., Eruca Mill., and Brassica L. We utilized multiple methods to forecast the ecological habitat of Microtheca Stål, 1860 species based on distribution data and various environmental indicators. Our models, exhibiting high-performance metrics (TSS ranging from 0.84 to 0.96), revealed extensive environmental suitability for these species across the Americas, including previously unreported regions. The predicted zones overlapped significantly with areas where Brassicaceae crops were grown. Contrary to some previous assertions, our findings suggest that while these Microtheca species are recognized pests on these crops, their consistent widespread damage may be overstated. Nevertheless, their invasive potential could have broad ecological impacts, including biodiversity loss. Our research emphasizes the need for focused sampling in potential distribution zones and underlines the value of integrating ENM in predicting and managing invasive species spread.

Data-centric species distribution modeling: Impacts of modeler decisions in a case study of invasive European frog-bit

Premise

Species distribution models (SDMs) are widely utilized to guide conservation decisions. The complexity of available data and SDM methodologies necessitates considerations of how data are chosen and processed for modeling to enhance model accuracy and support biological interpretations and ecological applications.

Methods

We built SDMs for the invasive aquatic plant European frog-bit using aggregated and field data that span multiple scales, data sources, and data types. We tested how model results were affected by five modeler decision points: the exclusion of (1) missing and (2) correlated data and the (3) scale (large-scale aggregated data or systematic field data), (4) source (specimens or observations), and (5) type (presence-background or presence-absence) of occurrence data.

Results

Decisions about the exclusion of missing and correlated data, as well as the scale and type of occurrence data, significantly affected metrics of model performance. The source and type of occurrence data led to differences in the importance of specific explanatory variables as drivers of species distribution and predicted probability of suitable habitat.

Discussion

Our findings relative to European frog-bit illustrate how specific data selection and processing decisions can influence the outcomes and interpretation of SDMs. Data-centric protocols that incorporate data exploration into model building can help ensure models are reproducible and can be accurately interpreted in light of biological questions.

Future climatically suitable areas for bats in South Asia

Climate change majorly impacts biodiversity in diverse regions across the world, including South Asia, a megadiverse area with heterogeneous climatic and vegetation regions. However, climate impacts on bats in this region are not well-studied, and it is unclear whether climate effects will follow patterns predicted in other regions. We address this by assessing projected near-future changes in climatically suitable areas for 110 bat species from South Asia. We used ensemble ecological niche modelling with four algorithms (random forests, artificial neural networks, multivariate adaptive regression splines and maximum entropy) to define climatically suitable areas under current conditions (1970-2000). We then extrapolated near future (2041-2060) suitable areas under four projected scenarios (combining two global climate models and two shared socioeconomic pathways, SSP2: middle-of-the-road and SSP5: fossil-fuelled development). Projected future changes in suitable areas varied across species, with most species predicted to retain most of the current area or lose small amounts. When shifts occurred due to projected climate change, new areas were generally northward of current suitable areas. Suitability hotspots, defined as regions suitable for >30% of species, were generally predicted to become smaller and more fragmented. Overall, climate change in the near future may not lead to dramatic shifts in the distribution of bat species in South Asia, but local hotspots of biodiversity may be lost. Our results offer insight into climate change effects in less studied areas and can inform conservation planning, motivating reappraisals of conservation priorities and strategies for bats in South Asia.

White-nose syndrome, winter duration, and pre-hibernation climate impact abundance of reproductive female bats

White-nose syndrome (WNS) is an infectious disease that disrupts hibernation in bats, leading to premature exhaustion of fat stores. Though we know WNS does impact reproduction in hibernating female bats, we are unsure how these impacts are exacerbated by local climate factors. We compiled data from four southeastern U.S. states and used generalized linear mixed effects models to compare effects of WNS, pre-hibernation climate variables, and winter duration on the number of reproductive females in species across the range of WNS susceptibility. We predicted we would see a decline in the number of reproductive females in WNS-susceptible species, with the effect exaggerated by longer winter durations and pre-hibernation climate variables that lead to reductions in foraging. We found that the number of reproductive females in WNS-susceptible species was positively correlated with pre-hibernation local climate conditions conducive to foraging; however, WNS-susceptible species experienced an overall decline with the presence of WNS and as winter duration increased. Our long-term dataset provides evidence that pre-hibernation climate, specifically favorable summer weather conditions for foraging, greatly influences the reproduction, regardless of WNS status.

An ensemble model predicts an upward range shift of the endemic and endangered Yellow-throated Apalis (Apalis flavigularis) under future climate change in Malawi

Climate change poses a significant threat to endemic and endangered montane bird species with limited elevation and temperature ranges. Understanding their responses to changes in climate is essential for informing conservation actions. This study focused on the montane dwelling Yellow-throated Apalis (Apalis flavigularis) in Malawi, aiming to identify key factors affecting its distribution and predicting its potential distribution under different climate change scenarios. Using an ensemble species distribution modeling approach, we found that the mean temperature of the driest quarter (Bio9), mean temperature of the wettest quarter (Bio8), and precipitation seasonality (Bio15) were the most important variables that influenced the distribution of this species. Across future climate scenarios, the species' geographic range declined where range losses varied from 57.74% (2050 RCP 6.0) to 82.88% (2070 RCP 6.0). We estimate its current range size to be 549 km2 which is lower than some previous estimates of its spatial distribution. Moreover, our projections indicate that under future climate scenarios, the species will shift to higher elevations with a large proportion of suitable areas located outside forests, posing challenges for adaptation. Our results suggest that the species may be under greater threat than previously thought; hence, urgent conservation actions are required. We recommend reinforcing the protection of areas predicted to remain suitable under future climate scenarios and the development of a species conservation action plan.

Effects of climate on the distribution and conservation of commonly observed European earthworms

Belowground biodiversity distribution does not necessarily reflect aboveground biodiversity patterns, but maps of soil biodiversity remain scarce because of limited data availability. Earthworms belong to the most thoroughly studied soil organisms and-in their role as ecosystem engineers-have a significant impact on ecosystem functioning. We used species distribution modeling (SDMs) and available data sets to map the spatial distribution of commonly observed (i.e., frequently recorded) earthworm species (Annelida, Oligochaeta) across Europe under current and future climate conditions. First, we predicted potential species distributions with commonly used models (i.e., MaxEnt and Biomod) and estimated total species richness (i.e., number of species in a 5 × 5 km grid cell). Second, we determined how much the different types of protected areas covered predicted earthworm richness and species ranges (i.e., distributions) by estimating the respective proportion of the range area. Earthworm species richness was high in central western Europe and low in northeastern Europe. This pattern was mainly associated with annual mean temperature and precipitation seasonality, but the importance of predictor variables to species occurrences varied among species. The geographical ranges of the majority of the earthworm species were predicted to shift to eastern Europe and partly decrease under future climate scenarios. Predicted current and future ranges were only poorly covered by protected areas, such as national parks. More than 80% of future earthworm ranges were on average not protected at all (mean [SD] = 82.6% [0.04]). Overall, our results emphasize the urgency of considering especially vulnerable earthworm species, as well as other soil organisms, in the design of nature conservation measures.

Unravelling the impact of climate change on honey bees: An ensemble modelling approach to predict shifts in habitat suitability in Queensland, Australia

Honey bees play a vital role in providing essential ecosystem services and contributing to global agriculture. However, the potential effect of climate change on honey bee distribution is still not well understood. This study aims to identify the most influential bioclimatic and environmental variables, assess their impact on honey bee distribution, and predict future distribution. An ensemble modelling approach using the biomod2 package in R was employed to develop three models: a climate-only model, an environment-only model, and a combined climate and environment model. By utilising bioclimatic data (radiation of the wettest and driest quarters and temperature seasonality) from 1990 to 2009, combined with observed honey bee presence and pseudo absence data, this model predicted suitable locations for honey bee apiaries for two future time spans: 2020-2039 and 2060-2079. The climate-only model exhibited a true skill statistic (TSS) value of 0.85, underscoring the pivotal role of radiation and temperature seasonality in shaping honey bee distribution. The environment-only model, incorporating proximity to floral resources, foliage projective cover, and elevation, demonstrated strong predictive performance, with a TSS of 0.88, emphasising the significance of environmental variables in determining habitat suitability for honey bees. The combined model had a higher TSS of 0.96, indicating that the combination of climate and environmental variables enhances the model's performance. By the 2020-2039 period, approximately 88% of highly suitable habitats for honey bees are projected to transition from their current state to become moderate (14.84%) to marginally suitable (13.46%) areas. Predictions for the 2060-2079 period reveal a concerning trend: 100% of highly suitable land transitions into moderately (0.54%), marginally (17.56%), or not suitable areas (81.9%) for honey bees. These results emphasise the critical need for targeted conservation efforts and the implementation of policies aimed at safeguarding honey bees and the vital apiary industry.

Effects of Climate Change on the Distribution of Prosthechea mariae (Orchidaceae) and within Protected Areas in Mexico

The impact of climate change on the distribution of native species in the Neotropics remains uncertain for most species. Prosthechea mariae is an endemic epiphytic orchid in Mexico, categorized as threatened. The objective of this study was to assess the effect of climate change on the natural distribution of P. mariae and the capacity of protected areas (PAs) to safeguard optimal environmental conditions for the species in the future. Historical records were obtained from herbaria collections and through field surveys. We utilized climate variables from WorldClim for the baseline scenario and for the 2050 period, using the general circulation models CCSM4 and CNRM-CM5 (RCP 4.5). Three sets of climate data were created for the distribution models, and multiple models were evaluated using the kuenm package. We found that the species is restricted to the eastern region of the country. The projections of future scenarios predict not only a substantial reduction in habitat but also an increase in habitat fragmentation. Ten PAs were found within the current distribution area of the species; in the future, the species could lose between 36% and 48% of its available habitat within these PAs. The results allowed for the identification of locations where climate change will have the most severe effects, and proposals for long-term conservation are addressed.

The future of endemic and threatened birds of the Amazon in the face of global climate change

The anthropogenic impacts on the environment, including deforestation and the escalating emissions of greenhouse gases, have significantly contributed to global climate change that can lead to alterations in ecosystems. In this context, protected areas (PAs) are pillars for biodiversity conservation by being able, for example, to maintain the viability of populations of endangered species. On the other hand, the species range shifts do not follow the limits of PAs, jeopardizing the conservation of these species. Furthermore, the effectiveness of PAs is consistently undermined by impacts stemming from land use, hunting activities, and illegal exploitation, both within the designated areas and in their adjacent zones. The objectives of this study are to quantify the impacts of climate change on the distribution of threatened and endemic birds of the Amazon biome, evaluate the effectiveness of PAs in protecting the richness of threatened birds, and analyze the representativeness of species within PAs. We found with our results that climate suitability loss is above 80 for 65% of taxa in the optimistic scenario and above 93% in the pessimistic scenario. The results show that PAs are not effective in protecting the richness of Amazonian birds, just as they are ineffective in protecting most of the taxa studied when analyzed individually Although some taxa are presented as "Protected," in future scenarios these taxa may suffer major shrinkages in their distributions and consequently present population unviability. The loss of climatically suitable areas and the effectiveness of PAs can directly influence the loss of ecosystem services, fundamental to maintaining the balance of biodiversity. Therefore, our study paves the way for conservation actions aimed at these taxa so that they can mitigate current and future extinctions due to climate change.

An evaluation of the ecological niche of Orf virus (Poxviridae): Challenges of distinguishing broad niches from no niches

Contagious ecthyma is a skin disease, caused by Orf virus, creating great economic threats to livestock farming worldwide. Zoonotic potential of this disease has gained recent attention owing to the re-emergence of disease in several parts of the world. Increased public health concern emphasizes the need for a predictive understanding of the geographic distributional potential of Orf virus. Here, we mapped the current distribution using occurrence records, and estimated the ecological niche in both geographical and environmental spaces. Twenty modeling experiments, resulting from two- and three-partition models, were performed to choose the candidate models that best represent the geographic distributional potential of Orf virus. For all of our models, it was possible to reject the null hypothesis of predictive performance no better than random expectations. However, statistical significance must be accompanied by sufficiently good predictive performance if a model is to be useful. In our case, omission of known distribution of the virus was noticed in all Maxent models, indicating inferior quality of our models. This conclusion was further confirmed by the independent final evaluation, using occurrence records sourced from the Centre for Agriculture and Bioscience International. Minimum volume ellipsoid (MVE) models indicated the broad range of environmental conditions under which Orf virus infections are found. The excluded climatic conditions from MVEs could not be considered as unsuitable owing to the broad distribution of Orf virus. These results suggest two possibilities: that the niche models fail to identify niche limits that constrain the virus, or that the virus has no detectable niche, as it can be found throughout the geographic distributions of its hosts. This potential limitation of component-based pathogen-only ENMs is discussed in detail.

Climate change should drive mammal defaunation in tropical dry forests

Human-induced climate change has intensified negative impacts on socioeconomic factors, the environment, and biodiversity, including changes in rainfall patterns and an increase in global average temperatures. Drylands are particularly at risk, with projections suggesting they will become hotter, drier, and less suitable for a significant portion of their species, potentially leading to mammal defaunation. We use ecological niche modelling and community ecology biodiversity metrics to examine potential geographical range shifts of non-volant mammal species in the largest Neotropical dryland, the Caatinga, and evaluate impacts of climate change on mammal assemblages. According to projections, 85% of the mammal species will lose suitable habitats, with one quarter of species projected to completely lose suitable habitats by 2060. This will result in a decrease in species richness for more than 90% of assemblages and an increase in compositional similarity to nearby assemblages (i.e., reduction in spatial beta diversity) for 70% of the assemblages. Small-sized mammals will be the most impacted and lose most of their suitable habitats, especially in highlands. The scenario is even worse in the eastern half of Caatinga where habitat destruction already prevails, compounding the threats faced by species there. While species-specific responses can vary with respect to dispersal, behavior, and energy requirements, our findings indicate that climate change can drive mammal assemblages to biotic homogenization and species loss, with drastic changes in assemblage trophic structure. For successful long-term socioenvironmental policy and conservation planning, it is critical that findings from biodiversity forecasts are considered.

The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models

How to effectively obtain species-related low-dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high-dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

Climate change and carnivores: shifts in the distribution and effectiveness of protected areas in the Amazon

Background

Carnivore 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?

Methods

We 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.

Results

The 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.

Artificial intelligence algorithm comparison and ranking for weight prediction in sheep

In a rapidly transforming world, farm data is growing exponentially. Realizing the importance of this data, researchers are looking for new solutions to analyse this data and make farming predictions. Artificial Intelligence, with its capacity to handle big data is rapidly becoming popular. In addition, it can also handle non-linear, noisy data and is not limited by the conditions required for conventional data analysis. This study was therefore undertaken to compare the most popular machine learning (ML) algorithms and rank them as per their ability to make predictions on sheep farm data spanning 11 years. Data was cleaned and prepared was done before analysis. Winsorization was done for outlier removal. Principal component analysis (PCA) and feature selection (FS) were done and based on that, three datasets were created viz. PCA (wherein only PCA was used), PCA+ FS (both techniques used for dimensionality reduction), and FS (only feature selection used) bodyweight prediction. Among the 11 ML algorithms that were evaluated, the correlations between true and predicted values for MARS algorithm, Bayesian ridge regression, Ridge regression, Support Vector Machines, Gradient boosting algorithm, Random forests, XgBoost algorithm, Artificial neural networks, Classification and regression trees, Polynomial regression, K nearest neighbours and Genetic Algorithms were 0.993, 0.992, 0.991, 0.991, 0.991, 0.99, 0.99, 0.984, 0.984, 0.957, 0.949, 0.734 respectively for bodyweights. The top five algorithms for the prediction of bodyweights, were MARS, Bayesian ridge regression, Ridge regression, Support Vector Machines and Gradient boosting algorithm. A total of 12 machine learning models were developed for the prediction of bodyweights in sheep in the present study. It may be said that machine learning techniques can perform predictions with reasonable accuracies and can thus help in drawing inferences and making futuristic predictions on farms for their economic prosperity, performance improvement and subsequently food security.

Are threatened species special? An assessment of Dutch bees in relation to land use and climate

Red Lists are widely used as an indicator of the status and trends of biodiversity and are often used in directing conservation efforts. However, it is unclear whether species with a Least Concern status share a common relationship to environmental correlates compared to species that are on the Red List. To assess this, we focus here on the contribution and correlates of land use, climate, and soil to the occurrence of wild bees in the Netherlands. We used observation data and species distribution models to explain the relation between wild bees and the environment. Non-threatened bees had a relatively higher variable importance of the land use variables to their models, as opposed to the climate variables for the threatened bees. The threatened bees had a smaller extent of occurrence and occupied areas with more extreme climatic conditions. Bees with a Least Concern status showed more positive responses to urban green spaces and Red List species showed a different response to climatic variables, such as temperature and precipitation. Even though Red List bees were found in areas with a higher cover of natural areas, they showed a more selective response to natural land use types. Pastures and crops were the main contributing land use variables and showed almost exclusively a negative correlation with the distribution of all wild bees. This knowledge supports the implementation of appropriate, species-specific conservation measures, including the preservation of natural areas, and the improvement of land use practices in agricultural and urban areas, which may help mitigate the negative impacts of future global change on species' distributions.

Predicting the Potential Global Distribution of Scirtothrips dorsalis (Hood) (Thysanoptera: Thripidae) with Emphasis on the Americas Using an Ecological Niche Model

Scirtothrips dorsalis Hood (Thysanoptera: Thripidae) is an invasive pest that is popularly known as chilli thrips. This insect pest has a wide range of hosts distributed across 72 plant families, causing damage to numerous crops of great economic importance. In the Americas, it is present in the USA, Mexico, Suriname, Venezuela, Colombia, and some Caribbean Islands. Knowing the regions which have environmentally suitable conditions for the survival of this pest is important for phytosanitary monitoring and inspection. Thus, our objective was to forecast the distribution potential of S. dorsalis with a focus on the Americas. Models were produced to design this distribution, in which the environmental variables used were made available in Wordclim version 2.1. The algorithms used for the modeling were the generalized additive model (GAM), generalized linear model (GLM), maximum entropy (MAXENT), random forest (RF), and Bioclim, in addition to the ensemble, which consisted of the grouping of the algorithms used. The metrics used to evaluate the models were area over the curve (AUC), true ability statistics (TSS), and Sorensen score. All models had satisfactory results (> 0.8) for all metrics used. In North America, the model showed favorable regions on the west coast of the USA and east coast near New York. In South America, the potential distribution of the pest is significant, encompassing regions in all countries. It is concluded that S. dorsalis has suitable areas for the occurrence in the three American subcontinents and, in particular, a large part of South America.

Wild canids and the ecological traps facing the climate change and deforestation in the Amazon Forest

Ecological traps occur when species choose to settle in lower-quality habitats, even if this reduces their survival or productivity. This happens in situations of drastic environmental changes, resulting from anthropogenic pressures. In long term, this could mean the extinction of the species. We investigated the dynamics of occurrence and distribution of three canid species (Atelocynus microtis, Cerdocyon thous, and Spheotos venaticus) considering human threats to their habitats in the Amazon Rainforest. We analyzed the environmental thresholds for the occurrence of these species and related to the future projections of climatic niches for each one. All three species will be negatively affected by climate change in the future, with losses of up to 91% of the suitable area of occurrence in the Brazilian Amazon. A. microtis appear to be more forest-dependent and must rely on the goodwill of decision-makers to be maintained in the future. For C. thous and S. venaticus, climatic variables and those associated with anthropogenic disturbances that modulate their niches today may not act the same way in the future. Even though C. thous is least dependent on the Amazon Forest; this species may be affected in the future due to the ecological traps. S. venaticus, can also undergo the same process, but perhaps more drastically due to the lower ecological plasticity of this species compared to C. thous. Our results suggest that the ecological traps may put these two species at risk in the future. Using the canid species as a model, we had the opportunity to investigate these ecological effects that can affect a large part of the Amazonian fauna in the current scenario. Considering the high degree of environmental degradation and deforestation in the Amazon Rainforest, the theory of ecological traps must be discussed at the same level as the habitat loss, considering the strategies for preserving the Amazon biodiversity.

The value of private properties for the conservation of biodiversity in the Brazilian Cerrado

Areas set aside for conservation within private lands may be key to enhancing biodiversity-friendly landscapes. This conservation strategy should be especially effective in highly threatened regions that are poorly protected by public lands, such as the Brazilian Cerrado. Brazil's Native Vegetation Protection Law has included set-aside areas within private properties, but their relevance to conservation has not been evaluated. We assess whether private lands are contributing to biodiversity in the Cerrado, a global biodiversity conservation priority and major region for food production, where land use conflicts are often at odds with conservation objectives. We determined that private protected areas accommodate up to 14.5% of threatened vertebrate species ranges, which increases to 25% when considering the distribution of remaining native habitat. Moreover, the spatial spread of private protected areas benefits a large number of species. Ecological restoration of private protected lands would improve the benefits of this protection system, especially in the Southeastern Cerrado, where a large economic hub meets a threat hotspot.

Ecological niche modeling to find potential habitats of Vanda thwaitesii, a notified endangered orchid of Western Ghats, India

Conservation planning of a threatened species essentially requires information on its present population and extent of distribution. Ecological niche modeling (ENM) is a suitable machine learning technique to predict potential distribution of a species enabling to identify suitable habitat for conservation action. The present study undertook distribution modeling of Vanda thwaitesii, a notified endangered orchid species of the Indian Western Ghats and Sri Lanka using maxent software. Geographical coordinates of 54 occurrence points at 1 km resolutions gathered during the study were utilized for modeling. A total of 37 variables including bioclimatic, topographical, and seasonal climate subjected to principal component analysis extracted into three components based on temperature and precipitation. Four representative variables from each component in all possible combinations resulted consistent output showing distribution of the species extending from Gavi in Periyar Tiger Reserve of Kerala to Chikkamagalur of Karnataka. Habitat suitability was confined to the cooler regions receiving an average 3,400 mm annual mean precipitation, 22.70C annual mean temperature, and 290 mm summer precipitation. A total of 2,557 km2 in Kerala and Karnataka mostly outside protected forests demonstrated as the highly suitable habitats. Silent Valley National Park, Idukki Wildlife Sanctuary, Periyar Tiger Reserve, and Brahmagiri Wildlife Sanctuary in addition to a few reserve forests hold sufficient area for reinforcement of diversity of V. thwaitesii from vulnerable locations. The present study revealed niche modeling as a useful tool to find suitable habitats for V. thwaitesii in the Western Ghats.

Modeling present and future distribution of plankton populations in a coastal upwelling zone: the copepod Calanus chilensis as a study case

Predicting species distribution in the ocean has become a crucial task to assess marine ecosystem responses to ongoing climate change. In the Humboldt Current System (HCS), the endemic copepod Calanus chilensis is one of the key species bioindicator of productivity and water masses. Here we modeled the geographic distribution of Calanus chilensis for two bathymetric ranges, 0-200 and 200-400 m. For the 0-200 m layer, we used the Bayesian Additive Regression Trees (BART) method, whereas, for the 200-400 m layer, we used the Ensembles of Small Models (ESMs) method and then projected the models into two future scenarios to assess changes in geographic distribution patterns. The models were evaluated using the multi-metric approach. We identified that chlorophyll-a (0.34), Mixed Layer Depth (0.302) and salinity (0.36) explained the distribution of C. chilensis. The geographic prediction of the BART model revealed a continuous distribution from Ecuador to the southernmost area of South America for the 0-200 m depth range, whereas the ESM model indicated a discontinuous distribution with greater suitability for the coast of Chile for the 200-400 m depth range. A reduction of the distribution range of C. chilensis is projected in the future. Our study suggests that the distribution of C. chilensis is conditioned by productivity and mesoscale processes, with both processes closely related to upwelling intensity. These models serve as a tool for proposing indicators of changes in the ocean. We further propose that the species C. chilensis is a high productivity and low salinity indicator at the HCS. We recommend further examining multiple spatial and temporal scales for stronger inference.

Current and paleoclimate models for an Atlantic Forest kissing bug indicate broader distribution outside biome delimitations

Introduction

Rhodnius domesticus is a kissing bug with known occurrence around the Atlantic coast of South America and is considered to be the only endemic species of the Atlantic Forest for the Rhodniini tribe. In this study, we aimed to indicate the species trends in possible distribution in the current and paleoclimate scenarios from the last glacial maximum (LGM).

Methods

We revised R. domesticus distribution information and created ecological niche models (ENMs) between the current time and Pleistocene end scenarios for the study regions. Models were built and validated using Maxent, KUENM, and ENMeval packages in R and ArcMap. We considered the models' uncertainty when calculating the average model variance and using mobility-oriented parity (MOP) analyses to indicate extrapolation risk areas in transfer scenarios.

Results

We found 44 different geographical species records, and our current time models indicate suitable areas in coastal regions of the Atlantic and surrounding locations in higher and lower latitudes. Paleoclimate models indicate general suitability in coastal regions and change in suitability in the interior region through time.

Discussion

Our revision and ENMs indicate two main points: Despite the fact that R. domesticus records are spatial and time concentrated in some coastal regions of the Atlantic Forest, species could have a broader distribution area, including regions outside the biome delimitations in northeast and southwest areas of South America. Paleodistribution models indicate species broader distribution in Atlantic Forest-related areas in LGM and northern interior regions of South America from late Pleistocene to the current times. In glaciation scenarios, continental shelf distribution was relevant and species' different connectivity routes with other biomes may be developed after LGM.

Morphological and environmental differentiation as prezygotic reproductive barriers between parapatric and allopatric Campanula rotundifolia agg. cytotypes

BACKGROUND AND AIMS

Reproductive isolation and local establishment are necessary for plant speciation. Polyploidy, the possession of more than two complete chromosome sets, creates a strong postzygotic reproductive barrier between diploid and tetraploid cytotypes. However, this barrier weakens between polyploids (e.g. tetraploids and hexaploids). Reproductive isolation may be enhanced by cytotype morphological and environmental differentiation. Moreover, morphological adaptations to local conditions contribute to plant establishment. However, the relative contributions of ploidy level and the environment to morphology have generally been neglected. Thus, the extent of morphological variation driven by ploidy level and the environment was modelled for diploid, tetraploid and hexaploid cytotypes of Campanula rotundifolia agg. Cytotype distribution was updated, and morphological and environmental differentiation was tested in the presence and absence of natural contact zones.

METHODS

Cytotype distribution was assessed from 231 localities in Central Europe, including 48 localities with known chromosome counts, using flow cytometry. Differentiation in environmental niche and morphology was tested for cytotype pairs using discriminant analyses. A structural equation model was used to explore the synergies between cytotype, environment and morphology.

KEY RESULTS

Tremendous discrepancies were revealed between the reported and detected cytotype distribution. Neither mixed-ploidy populations nor interploidy hybrids were detected in the contact zones. Diploids had the broadest environmental niche, while hexaploids had the smallest and specialized niche. Hexaploids and spatially isolated cytotype pairs differed morphologically, including allopatric tetraploids. While leaf and shoot morphology were influenced by environmental conditions and polyploidy, flower morphology depended exclusively on the cytotype.

CONCLUSIONS

Reproductive isolation mechanisms vary between cytotypes. While diploids and polyploids are isolated postzygotically, the environmental niche shift is essential between higher polyploids. The impact of polyploidy and the environment on plant morphology implies the adaptive potential of polyploids, while the exclusive relationship between flower morphology and cytotype highlights the role of polyploidy in reproductive isolation.

A generalized framework for estimating snakebite underreporting using statistical models: A study in Colombia

BACKGROUND

Snakebite envenoming is a neglected tropical disease affecting deprived populations, and its burden is underestimated in some regions where patients prefer using traditional medicine, case reporting systems are deficient, or health systems are inaccessible to at-risk populations. Thus, the development of strategies to optimize disease management is a major challenge. We propose a framework that can be used to estimate total snakebite incidence at a fine political scale.

METHODOLOGY/PRINCIPAL FINDINGS

First, we generated fine-scale snakebite risk maps based on the distribution of venomous snakes in Colombia. We then used a generalized mixed-effect model that estimates total snakebite incidence based on risk maps, poverty, and travel time to the nearest medical center. Finally, we calibrated our model with snakebite data in Colombia from 2010 to 2019 using the Markov-chain-Monte-Carlo algorithm. Our results suggest that 10.19% of total snakebite cases (532.26 yearly envenomings) are not reported and these snakebite victims do not seek medical attention, and that populations in the Orinoco and Amazonian regions are the most at-risk and show the highest percentage of underreporting. We also found that variables such as precipitation of the driest month and mean temperature of the warmest quarter influences the suitability of environments for venomous snakes rather than absolute temperature or rainfall.

CONCLUSIONS/SIGNIFICANCE

Our framework permits snakebite underreporting to be estimated using data on snakebite incidence and surveillance, presence locations for the most medically significant venomous snake species, and openly available information on population size, poverty, climate, land cover, roads, and the locations of medical centers. Thus, our algorithm could be used in other countries to estimate total snakebite incidence and improve disease management strategies; however, this framework does not serve as a replacement for a surveillance system, which should be made a priority in countries facing similar public health challenges.

Low-elevation conifers in California's Sierra Nevada are out of equilibrium with climate

Since the 1930s, California's Sierra Nevada has warmed by an average of 1.2 ∘ C. Warming directly primes forests for easier wildfire ignition, but the change in climate also affects vegetation species composition. Different types of vegetation support unique fire regimes with distinct probabilities of catastrophic wildfire, and anticipating vegetation transitions is an important but undervalued component of long-term wildfire management and adaptation. Vegetation transitions are more likely where the climate has become unsuitable but the species composition remains static. This vegetation climate mismatch (VCM) can result in vegetation conversions, particularly after a disturbance like wildfire. Here we produce estimates of VCM within conifer-dominated forests in the Sierra Nevada. Observations from the 1930s Wieslander Survey provide a foundation for characterizing the historical relationship between Sierra Nevada vegetation and climate before the onset of recent, rapid climate change. Based on comparing the historical climatic niche to the modern distribution of conifers and climate, ∼19.5% of modern Sierra Nevada coniferous forests are experiencing VCM, 95% of which is below an elevation of 2356 m. We found that these VCM estimates carry empirical consequences: likelihood of type-conversion increased by 9.2% for every 10% decrease in habitat suitability. Maps of Sierra Nevada VCM can help guide long-term land management decisions by distinguishing areas likely to transition from those expected to remain stable in the near future. This can help direct limited resources to their most effective uses-whether it be protecting land or managing vegetation transitions-in the effort to maintain biodiversity, ecosystem services, and public health in the Sierra Nevada.

Possible Effects of Climate Change on the Occurrence and Distribution of the Rare Moss Buxbaumia viridis in Serbia (SE Europe)

The distribution range and occurrence of the rare and threatened epixylic moss Buxbaumia viridis have been reviewed in Serbia. Climatic conditions of its recent distribution in Serbia were involved in species distribution modeling and analyzed with the aim of obtaining a projection of unknown potential sites and future scenarios of its distribution dynamics. The results achieved suggest potential distribution range of the species will be significantly reduced. According to the climate change models, the habitat changes including the range loss of this species are predicted to be drastic, i.e., between 93% and 97% by the year 2050, and between 98% and 99.9% by the year 2070, affecting primarily lower elevations of its current range in Serbia. A major reason for the projected decline of the species is climate change combined with continued poor forest management.

Ecological-niche modeling reveals current opportunities for Agave dryland farming in Sonora, Mexico and Arizona, USA

For centuries, humans occupying arid regions of North America have maintained an intricate relationship with Agave (Agavoideae, Asparagaceae). Today Agave cultivation, primarily for beverage production, provides an economic engine for rural communities throughout Mexico. Among known dryland-farming methods, the use of rock piles and cattle-grazed areas stand out as promising approaches for Agave cultivation. Identifying new cultivation areas to apply these approaches in Arizona, USA and Sonora, Mexico warrants a geographic assessment of areas outside the known ranges of rock piles and grasslands. The objective of this study was to predict areas for dryland-farming of Agave and develop models to identify potential areas for Agave cultivation. We used maximum entropy (MaxEnt) ecological-niche-modeling algorithms to predict suitable areas for Agave dryland farming. The model was parameterized using occurrence records of Hohokam rock piles in Arizona and grassland fields cultivated with Agave in Sonora. Ten environmental-predictor variables were used in the model, downloaded from the WorldClim 2 climate database. The model identified potential locations for using rock piles as dryland-farming methods from south-central Arizona to northwestern Sonora. The Agave-grassland model indicated that regions from central to southern Sonora have the highest potential for cultivation of Agave, particularly for the species Agave angustifolia. Results suggest that there are many suitable areas where rock piles can be used to cultivate Agave in the Sonoran Desert, particularly in the border of southeastern Arizona and northwest Sonora. Likewise, cattle-grazing grasslands provide a viable environment for cultivating Agave in southern Sonora, where the expanding bacanora-beverage industry continues to grow and where different Agave products (e.g., syrups, fructans, saponins, and medicinal compounds) can potentially strengthen local economies.

Mapping the global distribution of invasive pest Drosophila suzukii and parasitoid Leptopilina japonica: implications for biological control

Insect pest invasions cause significant damage to crop yields, and the resultant economic losses are truly alarming. Climate change and trade liberalization have opened new ways of pest invasions. Given the consumer preference towards organic agricultural products and environment-friendly nature of natural pest control strategies, biological control is considered to be one of the potential options for managing invasive insect pests. Drosophila suzukii (Drosophilidae) is an extremely damaging fruit pest, demanding development of effective and sustainable biological control strategies. In this study, we assessed the potential of the parasitoid Leptopilina japonica (Figitidae) as a biocontrol agent for D. suzukii using ecological niche modeling approaches. We developed global-scale models for both pest and parasitoid to identify four components necessary to derive a niche based, target oriented prioritization approach to plan biological control programs for D. suzukii: (i) potential distribution of pest D. suzukii, (ii) potential distribution of parasitoid L. japonica, (iii) the degree of overlap in potential distributions of pest and parasitoid, and (iv) biocontrol potential of this system for each country. Overlapping suitable areas of pest and parasitoid were identified at two different thresholds and at the most desirable threshold (E = 5%), potential for L. japonica mediated biocontrol management existed in 125 countries covering 1.87 × 10⁷ km², and at the maximum permitted threshold (E = 10%), land coverage was reduced to 1.44 × 10⁷ km² in 121 countries. Fly pest distributional information as a predictor variable was not found to be improving parasitoid model performance, and globally, only in half of the countries, >50% biocontrol coverage was estimated. We therefore suggest that niche specificities of both pest and parasitoid must be included in site-specific release planning of L. japonica for effective biocontrol management aimed at D. suzukii. This study can be extended to design cost-effective pre-assessment strategies for implementing any biological control management program.

Multi-temporal ecological niche modeling for bird conservation in the face of climate change scenarios in Caatinga, Brazil

Background

Global shifts in climatic patterns have been recorded over the last decades. Such modifications mainly correspond to increased temperatures and rainfall regime changes, which are becoming more variable and extreme.

Methods

We aimed to evaluate the impact of future changes in climatic patterns on the distribution of 19 endemic or threatened bird taxa of the Caatinga. We assessed whether current protected areas (PAs) are adequate and whether they will maintain their effectiveness in the future. Also, we identified climatically stable areas that might work as refugia for an array of species.

Results

We observed that 84% and 87% of the bird species of Caatinga analyzed in this study will face high area losses in their predicted range distribution areas in future scenarios (RCP4.5 and RCP8.5, respectively). We also observed that the current PAs in Caatinga are ineffective in protecting these species in both present and future scenarios, even when considering all protection area categories. However, several suitable areas can still be allocated for conservation, where there are vegetation remnants and a high amount of species. Therefore, our study paves a path for conservation actions to mitigate current and future extinctions due to climate change by choosing more suitable protection areas.

Risk analysis of the spread of the quarantine pest mite Schizotetranychus hindustanicus in Brazil

Schizotetranychus hindustanicus Hirst (Acari: Tetranychidae) known as the Hindustan citrus mite, is a quarantine pest present in Roraima, Brazil. In 1924 this pest was described in India. It was reported in 2002 in Venezuela and in Roraima in 2008. In 2010, the Hindustan citrus mite was reported in Colombia. It is possible that it will be introduced in other areas of Brazil, resulting in a threat to Brazilian citrus industry. Our objective was to determine the most suitable regions of Brazil for S. hindustanicus using a maximum entropy (Maxent) algorithm, based on native and invasive updated occurrence records from published research, field surveys and online databases. To avoid overfitting and improving transferability, we chose parameter settings of Maxent to construct and validate models by searching for the best combination of feature classes and regularization multipliers. The model obtained showed excellent performance according to all evaluation metrics used. A high potential for the establishment of S. hindustanicus was identified in large areas of Roraima, the extreme west of Amazonas, the entire north of the State of Pará, also in northeast, south, east, and north of the State of Amapá, and in a small portion northwest of the State of Maranhão (all states belonging to the northern region of Brazil). Our results provide information for policy making and quarantine measures, especially where S. hindustanicus is still absent in Brazil.

Potential distributions of the parasite Trypanosoma cruzi and its vector Dipetalogaster maxima highlight areas at risk of Chagas disease transmission in Baja California Sur, Mexico, under climate change

Dipetalogaster maxima is a primary vector of Chagas disease in the Cape region of Baja California Sur, Mexico. The geographic distribution of D. maxima is limited to this small region of the Baja California Peninsula in Mexico. Our study aimed to construct the ecological niche models (ENMs) of this understudied vector species and the parasite responsible for Chagas disease (Trypanosoma cruzi). We modelled the ecological niches of both species under current and future climate change projections in 2050 using four Representative Concentration Pathways (RCPs): RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5. We also assessed the human population at risk of exposure to D. maxima bites, the hypothesis of ecological niche equivalency and similarity between D. maxima and T. cruzi, and finally the abundance centroid hypothesis. The ENM predicted a higher overlap between both species in the Western and Southern coastal regions of the Baja California Peninsula. The climate change scenarios predicted a Northern shift in the ecological niche of both species. Our findings suggested that the highly tourist destination of Los Cabos is a high-risk zone for Chagas disease circulation. Overall, the study provides valuable data to vector surveillance and control programs.

Prioritizing Areas for Primate Conservation in Argentina

Argentina lies within the southernmost distributional range of five neotropical primates, the brown howler monkey Alouatta guariba, the black-and-gold howler monkey Alouatta caraya, the black-horned capuchin Sapajus nigritus, the Azara’s capuchin Sapajus cay, and the Azara’s owl monkey Aotus azarae; the first three of which are globally threatened. These species occupy different ecoregions: the Alto Paraná Atlantic forest, the Araucaria moist forest, the humid Chaco, the Southern Cone Mesopotamian savanna, the Paraná Ffooded savanna, and the Southern Andean Yungas. The recently approved National Primate Conservation Plan of Argentina calls for identifying priority areas to focus conservation actions for these species. We used species distribution models to estimate species ranges and then used the Zonation software to perform a spatial conservation prioritization analysis based on primate habitat quality and connectivity to identify potential areas of importance at national and ecoregional levels. Only 7.2% (19,500 km2) of the area inhabited by primates in Argentina is under protection. Outside the current protected areas, the top-ranked 1% and 5% priority areas identified in our analysis covered 1894 and 7574 km2, respectively. The top 1% areas were in the Atlantic forest of Misiones province, where S. nigritus, A. guariba, and A. caraya are distributed, and in the humid portion of eastern Chaco and Formosa provinces, where A. azarae and A. caraya are present. The top 5% areas included portions of the Yungas, where S. cay is the only primate present. Priority areas in Chaco and Formosa provinces are particularly relevant because of the paucity of protected areas and the high deforestation rate. The endangered A. guariba population will benefit from the better protection of the priority areas of Misiones. The potential priority areas proposed herein, considered within a context of a broad participatory process involving relevant stakeholders and local people, will help guide new and innovative conservation policies and practices while supporting management objectives.

A two-stage latent factor regression method to model the common and unique effects of multiple highly correlated exposure variables

In many epidemiological and environmental health studies, developing an accurate exposure assessment of multiple exposures on a health outcome is often of interest. However, the problem is challenging in the presence of multicollinearity, which can lead to biased estimates of regression coefficients and inflated variance estimators. Selecting one exposure variable as a surrogate of multiple highly correlated exposure variables is often suggested in the literature as a solution to handle the multicollinearity problem. However, this may lead to loss of information, since the exposure variables that are highly correlated tend to have not only common but also additional effects on the outcome variable. In this study, a two-stage latent factor regression method is proposed. The key idea is to regress the dependent variable not only on the common latent factor(s) of the explanatory variables, but also on the residuals terms from the factor analysis as the explanatory variables. The proposed method is compared to the traditional latent factor regression and principal component regression for their performance of handling multicollinearity. Two case studies are presented. Simulation studies are performed to assess their performances in terms of the epidemiological interpretation and stability of parameter estimates.

Natural forest regeneration on anthropized landscapes could overcome climate change effects on the endangered maned sloth (Bradypus torquatus, Illiger 1811)

Climate change and habitat loss have been identified as the main causes of species extinction. Forest regeneration and protected areas are essential to buffer climate change impacts and to ensure quality habitats for threatened species. We assessed the current and future environmental suitability for the maned sloth, Bradypus torquatus, under both future climate and forest restoration scenarios, using ecological niche modeling. We compared environmental suitability for two Evolutionarily Significant Units (ESUnorth and ESUsouth) using two climate change scenarios for 2070, and three potential forest regeneration scenarios. Likewise, we evaluated the protection degree of the suitable areas resulting from the models, according to Brazilian law: PA—Protected Areas; PPA—Permanent Protection Areas (environmentally sensitive areas in private properties); and LR—Legal Reserves (natural vegetation areas in private properties). Finally, we calculated the deficit of PPA and LR in each ESU, considering the current forest cover. Forest regeneration might mitigate the deleterious effects of climate change by maintaining and increasing environmental suitability in future scenarios. The ESUnorth contains more suitable areas (21,570 km²) than the ESUsouth (12,386 km²), with an increase in all future scenarios (up to 45,648 km² of new suitable areas), while ESUsouth might have a significant decrease (up to 7,546 km² less). Suitable areas are mostly unprotected (ESUnorth—65.5% and ESUsouth—58.3%). Therefore, PPA and PA can maintain only a small portion of current and future suitable areas. Both ESUs present a high deficit of PPA and LR, highlighting the necessity to act in the recovery of these areas to accomplish a large-scale restoration, mitigate climate change effects, and achieve, at least, a minimum forested area to safeguard the species. Notwithstanding, a long-term conservation of B. torquatus will benefit from forest regeneration besides those minimum requirements, allied to the protection of forest areas.

Favourable climatic niche in low elevations outside the flood zone characterises the distribution pattern of venomous snakes in Bangladesh

Snakes are sensitive to both environmental and climate gradients. To design conservation plans, a scientific understanding of snake habitats in light of environmental and climatic variables is an essential prerequisite. For venomous snakes, denoting favourable habitats should also be relevant for snakebite management. We have considered 18 spatial variables to portray the range of terrestrial venomous snake distribution in Bangladesh. Our results indicate that the distribution of 29 studied venomous snakes in this country is primarily driven by climatic and environmental variables. We found that especially low elevation and flood risk constrain the distribution of those terrestrial snakes, i.e. regular floods in central Bangladesh push venomous snakes towards the edges of the country. Moreover, none of these species occupies the whole of its anticipated climatically favourable area. Projections into the future indicated that 11 studied species, Amphiesma platyceps, Boiga siamensis, Chrysopelea ornata, Pseudoxenodon macrops, Rhabdophis himalayanus, Rhabdophis subminiatus, Bungarus lividus, Ophiophagus hannah, Daboia russelii, Ovophis monticola and Trimeresurus popeiorum will lose their entire climatically suitable area within the country. Therefore, we suggest establishing more protected areas in the hilly ecosystems in the eastern part and in the mangrove forests in the south-western corner of Bangladesh to mitigate future extinction risks, such as climate change, sea-level rise and increase in flood severity. Conserving village forests and croplands, which are subject to rapid change, will also need to be addressed equally, as these are inhabited by almost one-third of the studied species. The occurrence of the cobras and kraits in village forests and cropland dominant habitats demands more attention to minimise snakebite related mortality and morbidity.