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Non-indigenous species tend to colonize aquaculture installations, especially when they are near international ports. In addition to the local environmental hazard that colonizing non-indigenous species pose, they can also take advantage of local transport opportunities to spread elsewhere. In this study, we examined the risk of the spread of eight invasive fouling species that are found in mussel farms in southern Brazil. We used ensemble niche models based on worldwide occurrences of these species, and environmental variables (ocean temperature and salinity) to predict suitable areas for each species with three algorithms (Maxent, Random Forest, and Support Vector Machine). As a proxy for propagule pressure, we used the tonnage transported by container ships from Santa Catarina (the main mariculture region) that travel to other Brazilian ports. We found that ports in the tropical states of Pernambuco, Ceará, and Bahia received the largest tonnage, although far from Santa Catarina and in a different ecoregion. The ascidians Aplidium accarense and Didemnum perlucidum are known from Bahia, with a high risk of invasion in the other states. The bryozoan Watersipora subtorquata also has a high risk of establishment in Pernambuco, while the ascidian Botrylloides giganteus has a medium risk in Bahia. Paraná, a state in the same ecoregion as Santa Catarina is likely to be invaded by all species. A second state in this region, Rio Grande do Sul, is vulnerable to A. accarense, the barnacle Megabalanus coccopoma, and the mussel Mytilus galloprovincialis. Climate change is changing species latitudinal distributions and most species will gain rather than lose area in near future (by 2050). As an ideal habitat for fouling organisms and invasive species, aquaculture farms can increase propagule pressure and thus the probability that species will expand their distributions, especially if they are close to ports. Therefore, an integrated approach of the risks of both aquaculture and nautical transport equipment present in a region is necessary to better inform decision-making procedures aiming at the expansion or establishment of new aquaculture farms. The risk maps provided will allow authorities and regional stakeholders to prioritize areas of concern for mitigating the present and future spread of fouling species.

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Although the utility of Ecological Niche Models (ENM) and Species Distribution Models (SDM) has been demonstrated in many ecological applications, their suitability for modelling epidemics or pandemics, such as SARS-Cov-2, has been questioned. In this paper, contrary to this viewpoint, we show that ENMs and SDMs can be created that can describe the evolution of pandemics, both in space and time. As an illustrative use case, we create models for predicting confirmed cases of COVID-19, viewed as our target "species", in Mexico through 2020 and 2021, showing that the models are predictive in both space and time. In order to achieve this, we extend a recently developed Bayesian framework for niche modelling, to include: (i) dynamic, non-equilibrium "species" distributions; (ii) a wider set of habitat variables, including behavioural, socio-economic and socio-demographic variables, as well as standard climatic variables; (iii) distinct models and associated niches for different species characteristics, showing how the niche, as deduced through presence-absence data, can differ from that deduced from abundance data. We show that the niche associated with those places with the highest abundance of cases has been highly conserved throughout the pandemic, while the inferred niche associated with presence of cases has been changing. Finally, we show how causal chains can be inferred and confounding identified by showing that behavioural and social factors are much more predictive than climate and that, further, the latter is confounded by the former.

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Different models are available to estimate species' niche and distribution. Mechanistic and correlative models have different underlying conceptual bases, thus generating different estimates of a species' niche and geographic extent. Hybrid models, which combining correlative and mechanistic approaches, are considered a promising strategy; however, no synthesis in the literature assessed their applicability for terrestrial vertebrates to allow best-choice model considering their strengths and trade-offs. Here, we provide a systematic review of studies that compared or integrated correlative and mechanistic models to estimate species' niche for terrestrial vertebrates under climate change. Our goal was to understand their conceptual, methodological, and performance differences, and the applicability of each approach. The studies we reviewed directly compared mechanistic and correlative predictions in terms of accuracy or estimated suitable area, however, without any quantitative analysis to support comparisons. Contrastingly, many studies suggest that instead of comparing approaches, mechanistic and correlative methods should be integrated (hybrid models). However, we stress that the best approach is highly context-dependent. Indeed, the quality and effectiveness of the prediction depends on the study's objective, methodological design, and which type of species' niche and geographic distribution estimated are more appropriate to answer the study's issue.

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Fagus mexicana Martínez (Mexican beech) is an endangered Arcto-Tertiary Geoflora tree species that inhabit isolated and fragmented tropical montane cloud forests in eastern Mexico. Exploring past, present, and future climate change effects on the distribution of Mexican beech involves the study of spatial ecology and temporal patterns to develop conservation plans. These are key to understanding the niche conservatism of other forest communities with similar environmental requirements. For this study, we used species distribution models by combining occurrence records, to assess the distribution patterns and changes of the past (Last Glacial Maximum), present (1981-2010), and future (2040-2070) periods under two climate scenarios (SSP 3-7.0 & SSP 5-8.5). Next, we determined the habitat suitability and priority conservation areas of Mexican beech as associated with topography, land cover use, distance to the nearest town, and environmental variables. By considering the distribution of Mexican beech during different periods and under different climate scenarios, our study estimated that high-impact areas of Mexican beech forests were restricted to specific areas of the Sierra Madre Oriental that constitute refugia from the Last Glacial Maximum. Regrettably, our results exhibited that Mexican beech distribution has decreased 71.3% since the Last Glacial Maximum and this trend will for the next 50 years, migrating to specific refugia at higher altitudes. This suggests that the states of Hidalgo, Veracruz, and Puebla will preserve the habitat suitability features as ecological refugia, related to high moisture and north-facing slopes. For isolated and difficult-to-access areas, the proposed methods are powerful tools for relict-tree species, which deserve further conservation.

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Species distribution models (SDMs) have become an essential tool for the management and conservation of imperiled species. However, many at-risk species are rare and characterized by limited data on their spatial distribution and habitat relationships. This has led to the development of SDMs that integrate multiple types and sources of data to leverage more information and provide improved predictions of habitat associations. We developed a novel integrated species distribution model to predict habitat suitability for jaguars (Panthera onca) in the border region between northern Mexico and the southwestern USA. Our model combined presence-only and occupancy data to identify key environmental correlates, and we used model results to develop a probability of use map. We adopted a logistic regression modeling framework, which we found to be more straightforward and less computationally intensive to fit than Poisson point process-based models. Model results suggested that high terrain ruggedness and the presence of riparian vegetation were most strongly related to habitat use by jaguars in our study region. Our best model, on average, predicted that there is currently 25,463 km2 of usable habitat in our study region. The United States portion of the study region, which makes up 38.6% of the total area, contained 40.6% of the total usable habitat. Even though there have been few detections of jaguars in the southwestern USA in recent decades, our results suggest that protection of currently suitable habitats, along with increased conservation efforts, could significantly contribute to the recovery of jaguars in the USA.

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Much has yet to be learned of the spatial patterning of pre-Columbian people across the Tropical Andes. Using compiled archaeological data and a suite of environmental variables, we generate an ensemble species distribution model (SDM) that incorporates general additive models, random forest models and Maxent models to reconstruct spatial patterns of pre-Columbian people that inhabited the Tropical Andes east of the continental divide, within the modern countries of Bolivia, Peru and Ecuador. Within this region, here referred to as the eastern Andean flank, elevation, mean annual cloud frequency, distance to rivers and precipitation of the driest quarter are the environmental variables most closely related to human occupancy. Our model indicates that 11.04% of our study area (65 368 km2) was likely occupied by pre-Columbian people. Our model shows that 30 of 351 forest inventory plots, which are used to generate ecological understanding of Andean ecosystems, were likely occupied in the pre-Columbian period. In previously occupied sites, successional trajectories may still be shaping forest dynamics, and those forests may still be recovering from the ecological legacy of pre-Columbian impacts. Our ensemble SDM links palaeo- and neo-ecology and can also be used to guide both future archaeological and ecological studies. This article is part of the theme issue 'Tropical forests in the deep human past'.

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The extreme north of Chile presents a subtropical climate permissive of the establishment of potential disease vectors. Anopheles (Ano.) pseudopunctipennis is distributed from the south of the United States to the north of Argentina and Chile, and is one of the main vectors of malaria in Latin America. Malaria was eradicated from Chile in 1945. Nevertheless, the vector persists in river ravines of the Arica and Tarapacá regions. The principal effect of climate change in the north of Chile is temperature increase. Precipitation prediction is not accurate for this region because records were erratic during the last century. The objective of this study was to estimate the current and the projected distribution pattern of this species in Chile, given the potential impact due to climate change. We compiled distributional data for An. (Ano.) pseudopunctipennis and constructed species distribution models to predict the spatial distribution of this species using the MaxEnt algorithm with current and RCP 4.5 and 8.5 scenarios, using environmental and topographic layers. Our models estimated that the current expected range of An. (Ano.) pseudopunctipennis extends continuously from Arica to the north of Antofagasta region. Furthermore, the RCP 4.5 and 8.5 projected scenarios suggested that the range of distribution of An. (Ano.) pseudopunctipennis may increase in longitude, latitude, and altitude limits, enhancing the local extension area by 38 and 101%, respectively, and local presence probability (>0.7), from the northern limit in Arica y Parinacota region (18°S) to the northern Antofagasta region (23°S). This study contributes to geographic and ecologic knowledge about this species in Chile, as it represents the first local study of An. (Ano.) pseudopunctipennis. The information generated in this study can be used to inform decision making regarding vector control and surveillance programs of Latin America. These kinds of studies are very relevant to generate human, animal, and environmental health knowledge contributing to the "One Health" concept.

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We tested two questions: (i) whether the climatic conditions of the Azorean Islands in Portugal may have restricted the invasion of Harmonia axyridis across this archipelago and (ii) determine what population of this species could have a higher probability of invading the islands. We used MaxEnt to project the climate requirements of different H. axyridis populations from three regions of the world, and the potential global niche of the species in the Azorean islands. Then we assessed the suitability of the islands for each of the three H. axyridis populations and global potential niche through histograms analysis, Principal Component Analysis (PCA) of climate variables, and a variable-by-variable assessment of the suitability response curves compared with the climatic conditions of the Azores. Climatic conditions of the Azores are less suitable for the U.S. and native Asian populations of H. axyridis, and more suitable for European populations and the global potential niche. The PCA showed that the climatic conditions of the islands differed from the climatic requirements of H. axyridis. This difference is mainly explained by precipitation of the wettest month, isothermality, and the minimum temperature of the coldest month. We concluded that the climatic conditions of the Azores could have influenced the establishment and spread of H. axyridis on these islands from Europe. Our results showed that abiotic resistance represented by the climate of the potentially colonizable zones could hinder the establishment of invasive insects, but it could vary depending of the origin of the colonizing population.

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The spectacled, or Andean, bear (Tremarctos ornatus) is classified as vulnerable by the IUCN due to climate change and human-induced habitat fragmentation. There is an urgent need for the conservation of spectacled bear at real time. However, the lack of knowledge about the distribution of this species is considered as one of the major limitations for decision-making and sustainable conservation. In this study, 92 geo-referenced records of the spectacled bear, 12 environmental variables and the MaxEnt entropy modelling have been used for predictive modelling for the current and future (2050 and 2070) potential distribution of the spectacled bear in Amazonas, northeastern Peru. The areas of "high", "moderate" and "low" potential habitat under current conditions cover 1.99% (836.22 km2), 14.46% (6081.88 km2) and 20.73% (8718.98 km2) of the Amazon, respectively. "High" potential habitat will increase under all climate change scenarios, while "moderate" and "low" potential habitat, as well as total habitat, will decrease over the time. The "moderate", "low" and total potential habitat are distributed mainly in Yunga montane forest, combined grasslands/rangelands and secondary vegetation and Yunga altimontane (rain) forest, while "high" potential habitat is also concentrated in the Jalca. The overall outcome showed that the most of the important habitats of the spectacled bear are not part of the protected natural areas of Amazonas, under current as well as under future scenarios.

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During the last century, the coyote (Canis latrans) has increased its distribution in Central America. Before the 1980s, it had not been recorded in Panama. New records show that coyotes have crossed the Panama Canal, indicating that continues to expand; therefore, there is a possibility that it will reach northern South America. Our objectives were to identify potential coyote colonization routes to South America, and the variables that favor its expansion. We hypothesized that habitat fragmentation benefits coyote expansion. We applied 7 algorithms to model the potential distribution of the coyote, using 196 presence records and 12 variables. The models with better performance were used to generate a consensus model. Using our consensus model and the areas with highest probability of presence, a potential colonization route was generated between Central America and northern South America. This route lies through southern Costa Rica, along the Pacific coast of Panama to the south, to the Andean mountains in northern Colombia. The variables that explained potential coyote distribution were human population density, altitude, and percentage of crops with positive influence, and tropical broadleaf forests with negative influence. These results indicate that human activities and deforestation are related to coyote distribution expansion. Actions can be implemented within the identified route to improve environmental management, in order to avoid the presence of the coyote in the ecosystems of northern South America.

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Introduction: The Black-headed Bushmaster (Lachesis melanocephala) is a large venomous snake that inhabits tropical moist forest, wet forest, montane and premontane wet forest in Southwestern Costa Rica and extreme Western Panama. Objective: We assign a neotype for the species due to the loss of the original holotype and update the information on its geographical distribution, natural history, and conservation status. Methods: To determine the conservation status of L. melanocephala, we modeled its potential distribution using the species` locality records and distribution modeling analysis implemented in MaxEnt. Based on the species' potential distribution, we evaluate the loss of its original habitat and estimate the percentage of its distribution area that is currently protected by the country's protected area system. Results: The potential distribution of the species was estimated at 10 139 km2, including areas where the species currently occurs and historical areas where the species has been registered but is nowadays considered locally extinct. About 29 % of that potential distribution overlaps with protected wild areas, so less than a third of the potential distribution of the species is under protection. Conclusions: During the last decade, accelerated habitat loss and growing evidence of declining natural populations indicate the need for urgent protective measures to prevent the extinction of this species in the foreseeable future.

Introducción: La serpiente Plato Negro (Lachesis melanocephala) es una especie venenosa de gran tamaño, endémica de los bosques lluviosos del Pacífico sur y suroeste de Costa Rica y el extremo oeste de Panamá. Objetivo: Se asigna un neotipo para la especie debido a la pérdida del holotipo original y se presentan datos actualizados de su distribución geográfica, historia natural y estado de conservación. Métodos: Para determinar el estado de conservación de L. melanocephala, reconstruimos su distribución potencial utilizando los registros de localidad de la especie y el análisis de modelado de distribución implementado en MaxEnt. En función de la distribución potencial de la especie, evaluamos la pérdida de su hábitat original y calculamos el porcentaje de su área de distribución que actualmente está protegida por el sistema de áreas protegidas del país. Resultados: La distribución potencial de la especie se estimó en 10 139 km2, incluyendo áreas donde la especie se encuentra actualmente y áreas históricas donde la especie se ha registrado, pero se considera localmente extinta. Cerca del 29 % de esa distribución potencial se traslapa con áreas silvestres protegidas, por lo que menos de una tercera parte de la distribución potencial de la especie está bajo protección. Conclusiones: La degradación acelerada de su hábitat y la disminución evidente de sus poblaciones durante la última década señalan la necesidad de tomar medidas urgentes de protección para evitar el riesgo de extinción a corto plazo o mediano plazo.

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Invasive species threaten global biodiversity, food security and ecosystem function. Such incursions present challenges to agriculture where invasive species cause significant crop damage and require major economic investment to control production losses. Pest risk analysis (PRA) is key to prioritize agricultural biosecurity efforts, but is hampered by incomplete knowledge of current crop pest and pathogen distributions. Here, we develop predictive models of current pest distributions and test these models using new observations at subnational resolution. We apply generalized linear models (GLM) to estimate presence probabilities for 1,739 crop pests in the CABI pest distribution database. We test model predictions for 100 unobserved pest occurrences in the People's Republic of China (PRC), against observations of these pests abstracted from the Chinese literature. This resource has hitherto been omitted from databases on global pest distributions. Finally, we predict occurrences of all unobserved pests globally. Presence probability increases with host presence, presence in neighbouring regions, per capita GDP and global prevalence. Presence probability decreases with mean distance from coast and known host number per pest. The models are good predictors of pest presence in provinces of the PRC, with area under the ROC curve (AUC) values of 0.75-0.76. Large numbers of currently unobserved, but probably present pests (defined here as unreported pests with a predicted presence probability >0.75), are predicted in China, India, southern Brazil and some countries of the former USSR. We show that GLMs can predict presences of pseudoabsent pests at subnational resolution. The Chinese literature has been largely inaccessible to Western academia but contains important information that can support PRA. Prior studies have often assumed that unreported pests in a global distribution database represent a true absence. Our analysis provides a method for quantifying pseudoabsences to enable improved PRA and species distribution modelling.

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Estimating α-diversity and species distributions provides baseline information to understand factors such as biodiversity loss and erosion of ecosystem services. Yet, species surveys typically cover a small portion of any country's landmass. Public, global databases could help, but contain biases. Thus, the magnitude of bias should be identified and ameliorated, the value of integration determined, and application to current policy issues illustrated. The ideal integrative approach should be powerful, flexible, efficient, and conceptually straightforward. We estimated distributions for >6,000 species, integrating species sightings (S) from the Global Biodiversity Information Facility (GBIF), systematic survey data (S2 ), and "bias-adjustment kernels" (BaK) using spatial and species trait databases (S2 BaK). We validated our approach using both locational and species holdout sets, and then applied our predictive model to Panama. Using sightings alone (the most common approach) discriminated relative probabilities of occurrences well (area under the curve [AUC] = 0.88), but underestimated actual probabilities by ~4,000%, while using survey data alone omitted over three-quarters of the >6,000 species. Comparatively, S2 BaK had no systematic underestimation, and substantially stronger discrimination (AUC = 0.96) and predictive power (deviance explained = 47%). Our model suggested high diversity (~200% countrywide mean) where urban development is projected to occur (the Panama Canal watershed) and also suggested this is not due to higher sampling intensity. However, portions of the Caribbean coast and eastern Panama (the Darién Gap) were even higher, both for total plant biodiversity (~250% countrywide mean), and CITES listed species. Finally, indigenous territories appeared half as diverse as other regions, based on survey observations. However, our model suggested this was largely due to site selection, and that richness in and out of indigenous territories was roughly equal. In brief, we provide arguably the best estimate of countrywide plant α-diversity and species distributions in the Neotropics, and make >6,000 species distributions available. We identify regions of overlap between development and high biodiversity, and improve interpretation of biodiversity patterns, including for policy-relevant CITES species, and locations with limited access (i.e., indigenous territories). We derive a powerful, flexible, efficient and simple estimation approach for biodiversity science.

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The tick genus Ripicephalus (Boophilus), particularly R. microplus, is one of the most important ectoparasites that affects livestock health and considered an epidemiological risk because it causes significant economic losses due, mainly, to restrictions in the export of infested animals to several countries. Its spatial distribution has been tied to environmental factors, mainly warm temperatures and high relative humidity. In this work, we integrated a dataset consisting of 5843 records of Rhipicephalus spp., in Mexico covering close to 50 years to know which environmental variables mostly influence this ticks' distribution. Occurrences were georeferenced using the software DIVA-GIS and the potential current distribution was modelled using the maximum entropy method (Maxent). The algorithm generated a map of high predictive capability (Area under the curve = 0.942), providing the various contribution and permutation importance of the tested variables. Precipitation seasonality, particularly in March, and isothermality were found to be the most significant climate variables in determining the probability of spatial distribution of Rhipicephalus spp. in Mexico (15.7%, 36.0% and 11.1%, respectively). Our findings demonstrate that Rhipicephalus has colonized Mexico widely, including areas characterized by different types of climate. We conclude that the Maxent distribution model using Rhipicephalus records and a set of environmental variables can predict the extent of the tick range in this country, information that should support the development of integrated control strategies.

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The American dog tick (Dermacentor variabilis) is medically and economically important in North America. This species is found across central and eastern North America from the Gulf Coast of Mexico through southern Canada. In parts of this region, D. variabilis is a vector for pathogens that cause diseases in humans and animals. Our aim was to determine whether climate change would affect the distribution of the climatically suitable area for D. variabilis in North America, to aid monitoring for potential future spread of tick-borne pathogens. We developed a species distribution model for D. variabilis to project where climate will likely be suitable for the tick in North America using a maximum entropy method, occurrence records from museum and laboratory archives, and 10 environmental variables relevant to climate requirements for the tick. We used four emissions scenarios from the Intergovernmental Panel on Climate Change's Fifth Assessment Report and 10 climate models from the Coupled Model Intercomparison Project (phase 5) to estimate potential future climate suitability and determine how the tick's distribution could change. Our consensus model projected that the area of suitable climate in North America could increase from present by approximately 50% by 2070. In areas beyond the current northern limit of D. variabilis, climate could become more suitable for the tick than at present, possibly resulting in a northward expansion in Canada, but the potential suitability of the southern range of D. variabilis could decrease, depending on the region and climate model. Due to the ability of D. variabilis to harbor and transmit pathogens, a change in the distribution of this species could also affect the risk of human and animal diseases throughout North America, particularly in the northern range of the tick.

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Malaria is an important health issue in French Guiana. Its principal mosquito vector in this region is Anopheles darlingi Root. Knowledge of the spatial distribution of this species is still very incomplete due to the extent of French Guiana and the difficulty to access most of the territory. Species distribution modeling based on the maximal entropy procedure was used to predict the spatial distribution of An. darlingi using 39 presence sites. The resulting model provided significantly high prediction performances (mean 10-fold cross-validated partial area under the curve and continuous Boyce index equal to, respectively, 1.11-with a level of omission error of 20%-and 0.42). The model also provided a habitat suitability map and environmental response curves in accordance with the known entomological situation. Several environmental characteristics that had a positive correlation with the presence of An. darlingi were highlighted: nonpermanent anthropogenic changes of the natural environment, the presence of roads and tracks, and opening of the forest. Some geomorphological landforms and high altitude landscapes appear to be unsuitable for An. darlingi. The species distribution modeling was able to reliably predict the distribution of suitable habitats for An. darlingi in French Guiana. Results allowed completion of the knowledge of the spatial distribution of the principal malaria vector in this Amazonian region, and identification of the main factors that favor its presence. They should contribute to the definition of a necessary targeted vector control strategy in a malaria pre-elimination stage, and allow extrapolation of the acquired knowledge to other Amazonian or malaria-endemic contexts.

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The study was conducted in the central region of Veracruz Mexico, in the metropolitan area of Xalapa. It is a mountainous area where Aedes aegypti (L.) is not currently endemic. An entomological survey was done along an elevation gradient using the Ae. aegypti occurrences at different life cycle stages. Seven sites were sampled and a total of 24 mosquito species were recorded: 9 species were found in urban areas, 18 in non-urban areas with remnant vegetation, and 3 occurred in both environments. Ae. aegypti was found only in the urban areas, usually below 1200m a.s.l., but in this study was recorded for the first time at 1420m a.s.l. These occurrences, together with additional distribution data in the state of Veracruz were used to developed species distribution models using Maxlike software in R to identify the current projected suitable areas for the establishment of this vector and the human populations that might be affected by dengue transmission at higher elevations. Its emergence in previously unsuitable places appears to be driven by both habitat destruction and biodiversity loss associated with biotic homogenization. A border study using data from the edges of the vector's distribution might allow sensitive monitoring to detect any changes in this mosquito's distribution pattern, and any changes in the anthropic drivers or climate that could increase transmission risk.

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The evolutionary history of invasive species within their native range may involve key processes that allow them to colonize new habitats. Therefore, phylogeographic studies of invasive species within their native ranges are useful to understand invasion biology in an evolutionary context. Here we integrated classical and Bayesian phylogeographic methods using mitochondrial and nuclear DNA markers with a palaeodistribution modelling approach, to infer the phylogeographic history of the invasive ant Wasmannia auropunctata across its native distribution in South America. We discuss our results in the context of the recent establishment of this mostly tropical species in the Mediterranean region. Our Bayesian phylogeographic analysis suggests that the common ancestor of the two main clades of W. auropunctata occurred in central Brazil during the Pliocene. Clade A would have differentiated northward and clade B southward, followed by a secondary contact beginning about 380,000 years ago in central South America. There were differences in the most suitable habitats among clades when considering three distinct climatic periods, suggesting that genetic differentiation was accompanied by changes in niche requirements, clade A being a tropical lineage and clade B a subtropical and temperate lineage. Only clade B reached more southern latitudes, with a colder climate than that of northern South America. This is concordant with the adaptation of this originally tropical ant species to temperate climates prior to its successful establishment in the Mediterranean region. This study highlights the usefulness of exploring the evolutionary history of invasive species within their native ranges to better understand biological invasions.

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Background. Just as for most other tortoise species, the once common Chaco tortoise, Chelonoidis chilensis (Testudinidae), is under constant threat across it distribution in Argentina, Bolivia and Paraguay. Despite initial qualitative description of the species distribution and further individual reports of new locations for the species, there is no description of the species distribution in probabilistic terms. With this work we aim to produce an updated predictive distribution map for C. chilensis to serve as a baseline management tool for directed strategic conservation planning. Methods. We fitted a spatially expanded logistic regression model within the Bayesian framework that accounts for uncertainty on presence-only and generated pseudo-absence data into the parameter estimates. We contrast the results with reported data for the national networks of protected areas to assess the inclusion of the species in area-based conservation strategies. Results. We obtained maps with predictions of the occurrence of the species and reported the model's uncertainty spatially. The model suggests that potential suitable habitats for the species are continuous across Argentina, West Paraguay and South Bolivia, considering the variables, the scale and the resolution used. The main limiting variables were temperature-related variables, and precipitation in the reproductive period. Discussion. Given the alarming low density and coverage of protected areas over the distribution area of C. chilensis, the map produced provides a baseline to identify areas where directed strategic conservation management actions would be more efficient for this and other associated species.

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

Resumo Recentemente, modelos de nicho têm sido empregados para investigar a distribuição geográfica potencial de espécies. Porém, é necessário analisar a vasta quantidade de publicações sobre o referido tema, a fim de compreender as tendências e vieses das pesquisas que usam modelos de nicho ecológico (MNEs). Portanto, esse trabalho tem por objetivo investigar as tendências da literatura científica de trabalhos sobre MNEs. Para a análise quantitativa das publicações sobre MNEs, foi realizada uma busca na base de dados Thomson ISI (Web of Science), entre o período de 1991 a 2013. A pesquisa agrupou 3042 documentos que continham nas palavras-chave, no título ou no resumo os termos selecionados para a busca. Os resultados mostraram que de forma geral o número de artigos tem aumentado ao longo dos anos (r=0,77, P<0,001), com um acentuado crescimento nos anos mais recentes, destacando o amplo uso de MNEs. Ao longo dos anos percebeu-se um aumento da diversidade de revistas que publicam sobre o assunto (r=0,97, P<0,001). As pesquisas têm sido desenvolvidas em diferentes países, com predomínio dos Estados Unidos (550 artigos) e o método mais utilizado foi o de Máxima Entropia (312 artigos). Quanto ao grupo taxonômico, a maioria dos estudos tem ocorrido com plantas (402 artigos ou 28,36% do total de artigos). Não houve relação entre método de modelagem e grupo taxonômico (χ2=4,8, P=0,15). Por fim, a ampla disponibilidade de dados biológicos, ambientais e recursos computacionais tem propiciado um amplo uso de MNEs. Apesar das discussões conceituais sobre MNEs, o método atualmente é o mais eficaz para conhecer a distribuição geográfica potencial das espécies e ainda projetar essa distribuição sob diferentes condições ambientais (i.e. cenários futuros, passado).

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