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In biogeography the competitive exclusion principle (CEP) has been confirmed in some cases but not in others. This has fueled an unresolved debate between those advocating niche theory or the neutral theory in biodiversity and biogeography. We suggest that this situation mainly arises from the use of crisp logic, where the CEP is defined as either completely true or false. We propose the application of the fuzzy concepts of favorability (the degree to which environmental conditions are propitious for the occurrence of individual species) and favorableness (the degree to which environmental conditions are simultaneously favorable for competing species) to operationalize a fuzzy version of the CEP. Favorability was obtained by performing species distribution models applying favorability functions, while favorableness was derived from the application of the fuzzy intersection between the favorability for competing species. Then we plotted individual favorability values along the gradient of favorableness. Two potentially competing species would coexist in high-favorableness locations, as the demands of both species would be well fulfilled. In locations of low favorableness, the result would be either autecological exclusion of both species or autecological segregation, as abiotic conditions are unfavorable for at least one of the species. Competitive exclusion would occur at the intermediate stretch of the favorableness gradient, as the conditions would be good enough for persistence of each species separately but not enough for permanent coexistence. According to this theoretical framework, the observed probability that a location belongs to the intermediate favorableness area given that the two species co-occur in this location should be lower than expected according to the environmental probability models for the two species. We tested this prediction on published data about the distribution of pairs of native and introduced deer species in Great Britain, using a Ba

1. A significant link between forest loss and fragmentation and human outbreaks of Ebola virus disease (EVD) has been documented. Deforestation may alter the natural circulation of viruses as well as change the composition, abundance, behaviour and possibly viral exposure of reservoir species. This in turn might increase contact between infected animals and humans. Fruit bats of the family Pteropodidae have been suspected as reservoirs of the Ebola virus. Though there is no solid proof that fruit bats cause human EVD outbreaks, this group of animals have been intermittently infected with the Ebola virus. 2. Our study investigates whether human activities positively affect African fruit bat species’ ranges and whether their ranges are linked to EVD outbreaks, in turn favoured by deforestation. 3. We use species observation records for the 20 fruit bat species found in Africa to determine factors affecting their distribution in two geographical scenarios: 1) the African continent; and 2) inside the predicted Ebola virus range. We do this by employing a hypothetico-deductive approach based on favourability modelling. 4. Our models point to clear associations between human activities and fruit bat distributions that may help scientists understand the anthropogenic settings that could cause the Ebola virus to jump from animals to humans. 5. We show that fruit bat distributions are linked to human activities throughout Africa and particularly within the region where the Ebola virus occurs. More specifically, the areas where human activities favour the presence of five fruit bat species (four of which had recorded seropositive individuals) overlap with EVD outbreak areas, themselves favoured by deforestation. 6. Our work is a useful first step to further investigate the networks and pathways that may lead to an EVD outbreak. The modelling framework we employ here can be employed for other emerging infectious diseases.

1. A significant link between forest loss and fragmentation and human outbreaks of Ebola virus disease (EVD) has been documented. Deforestation may alter the natural circulation of viruses as well as change the composition, abundance, behaviour and possibly viral exposure of reservoir species. This in turn might increase contact between infected animals and humans. Fruit bats of the family Pteropodidae have been suspected as reservoirs of the Ebola virus. Though there is no solid proof that fruit bats cause human EVD outbreaks, this group of animals have been intermittently infected with the Ebola virus. 2. Our study investigates whether human activities positively affect African fruit bat species’ ranges and whether their ranges are linked to EVD outbreaks, in turn favoured by deforestation. 3. We use species observation records for the 20 fruit bat species found in Africa to determine factors affecting their distribution in two geographical scenarios: 1) the African continent; and 2) inside the predicted Ebola virus range. We do this by employing a hypothetico-deductive approach based on favourability modelling. 4. Our models point to clear associations between human activities and fruit bat distributions that may help scientists understand the anthropogenic settings that could cause the Ebola virus to jump from animals to humans. 5. We show that fruit bat distributions are linked to human activities throughout Africa and particularly within the region where the Ebola virus occurs. More specifically, the areas where human activities favour the presence of five fruit bat species (four of which had recorded seropositive individuals) overlap with EVD outbreak areas, themselves favoured by deforestation. 6. Our work is a useful first step to further investigate the networks and pathways that may lead to an EVD outbreak. The modelling framework we employ here can be employed for other emerging infectious diseases.

BACKGROUND Currently, there is an increasing global interest for the study of how infectious diseases could be linked to climate and weather variability. The Chagas disease was described in 1909 by Carlos Chagas, and is caused by the flagellate protozoan Trypanosoma cruzi. The Chagas disease is considered one of the biggest concerns in public health in Latin America. In Chile, the main vectors involved in the transmission of T. cruzi are arthropods of the Triatominae subfamily. Moreover, another main transmission way is through of vectors by fecal-urine way, however, oral way also has been described among others transmission form. OBJECTIVES In order to get understand outbreaks of Chagas-disease, we search for possible relationships between the frequency of cases in the Chilean population and atmospheric oscillations. METHODS We explored the two most important atmospheric oscillations in the Southern Hemisphere: southern oscillation index (SOI) and Antarctic oscillation (AAO), during the available years with official data. Because the number of migrant people born outside from Chile increasing significantively between 2014 and 2018, we used for the analysis two different periods from data available official data: (i) 2001 to 2014, (ii) 2001 to 2017. FINDINGS For both periods we observed a significant and positive relation between AAO one year before. However, for the 2001 to 2014 period positive SOI one year before, which is related with La Niña phases, was the more important variable. MAIN CONCLUSIONS The Chagas disease frequency per year in Chile was found to depend mainly on SOI in previous year, whose values can be determined one year in advance. Therefore, it is possible to partially forecast annual frequency patterns. This could have important applications in public health strategies and for allocating resources for the management of the disease.

The international wildlife trade is a lucrative business. Although a huge variety of animal groups are trafficked, the Psittaciformes (parrots) are amongst the most traded avian groups. Deliberate or accidental releases of imported parrots have led to the establishment of feral populations in many countries. Far from their native habitats, parrots may cause economic and ecological damage, and may even favour the transmission of zoonotic diseases. Despite this, the links between numbers of imported individuals and the establishment of non-native populations is not well known. In this study, we analysed data on imports of two well-known invasive parrots, the Monk Parakeet Myiopsita monachus and the Ring-necked Parakeet Psittacula krameri, in Spain. We contrasted this information with the growth of known naturalised populations of these species from 1975 to 2015 and compared the success of these two species with other Psittaciformes imported in similar numbers into the country. We show that more than 190,000 Monk Parakeets were imported from Uruguay and Argentina, and almost 63,000 Ring-necked Parakeets were legally brought into the country from Pakistan and Senegal. For both species, wild populations grew exponentially following peak importation periods in 2015 (18,980–21,455 Monk Parakeets and 3,005–3,115 Ring-necked Parakeets). Even though imports of the two species were banned in Spain in 2005, wild populations are now self-sustaining. We argue that these parrot populations started from accidental and deliberate bird escapes, especially from birds originally captured in the wild. Although lack of more precise data makes it difficult for us to propose clear statistical associations between imports and established bird populations, we nonetheless suggest that the international trade is with some certainty the main cause for the origin of naturalised populations of invasive species in Spain. Our conclusions are useful to help manage similar animal groups that are nume

Ebola virus disease (EVD) is a contagious, severe and often lethal form of hemorrhagic fever in humans. The association of EVD outbreaks with forest clearance has been suggested previously but many aspects remained uncharacterized. We used remote sensing techniques to investigate the association between deforestation in time and space, with EVD outbreaks in Central and West Africa. Favorability modeling, centered on 27 EVD outbreak sites and 280 comparable control sites, revealed that outbreaks located along the limits of the rainforest biome were significantly associated with forest losses within the previous 2 years. This association was strongest for closed forests (>83%), both intact and disturbed, of a range of tree heights (5 - >19 m). Our results suggest that the increased probability of an EVD outbreak occurring in a site is linked to recent deforestation events, and that preventing the loss of forests could reduce the likelihood of future outbreaks.

BACKGROUND: Numerous small and medium-sized mammal pests cause widespread and economically significant damage to crops all over the globe. However, most research on pest species has focused on accounts of the level of damage. There are fewer studies concentrating on the description of crop damage caused by pests at large geographical scales, or on analysing the ecological and anthropogenic factors correlated with these observed patterns. We investigated the relationship between agricultural damage by the European rabbit (Oryctolagus cuniculus) and environmental and anthropogenic variables throughout Spain. RESULTS: Rabbit damage was mainly concentrated within the central-southern regions of Spain. We found that rabbit damage has increased significantly between the early 2000s and 2013. Greater losses were typical of those areas where farming dominated and natural vegetation was scarce, where main railways and highways were present, and where environmental conditions were generally favourable for rabbit populations to proliferate. CONCLUSIONS: From our analysis we suggest that roads and railway lines act as potential corridors along which rabbits can spread. The recent increase in Spain of such infrastructure may explain the rise in rabbit damage reported in this study. Our approach is valuable as a method for assessing drivers of wildlife pest damage at large spatial scales, and can be used to propose methods to reduce human-wildlife conflict.

The main goal of this article is to present a flexible statistical modelling framework to deal with multivariate count data along with longitudinal and repeated measures structures. The covariance structure for each response variable is defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. In order to specify the joint covariance matrix for the multivariate response vector, the generalized Kronecker product is employed. We take into account the count nature of the data by means of the power dispersion function associated with the Poisson–Tweedie distribution. Furthermore, the score information criterion is extended for selecting the components of the matrix linear predictor. We analyse a data set consisting of prey animals (the main hunted species, the blue duiker Philantomba monticola and other taxa) shot or snared for bushmeat by 52 commercial hunters over a 33-month period in Pico Basilé, Bioko Island, Equatorial Guinea. By taking into account the severely unbalanced repeated measures and longitudinal structures induced by the hunters and a set of potential covariates (which in turn affect the mean and covariance structures), our method can be used to indicate whether there was statistical evidence of a decline in blue duikers and other species hunted during the study period. Determining whether observed drops in the number of animals hunted are indeed true is crucial to assess whether species depletion effects are taking place in exploited areas anywhere in the world. We suggest that our method can be used to more accurately understand the trajectories of animals hunted for commercial or subsistence purposes and establish clear policies to ensure sustainable hunting practices.

Ebola virus is responsible for the fatal Ebola virus disease (EVD). Identifying the distribution area of the Ebola virus is crucial for understanding the risk factors conditioning the emergence of new EVD cases. Existing distribution models have underrepresented the potential contribution that reservoir species and vulnerable species make in sustaining the presence of the virus. In this paper, we map favourable areas for Ebola virus in Africa according to environmental and zoogeographical descriptors, independent of human-to-human transmissions. We combine two different biogeographical approaches: analysis of mammalian distribution types (chorotypes), and distribution modelling of the Ebola virus. We first obtain a model defining the distribution of environmentally favourable areas for the presence of Ebola virus. Based on a review of mammal taxa affected by or suspected of exposure to the Ebola virus, we model favourable areas again, this time according to mammalian chorotypes. We then build a combined model in which both the environment and mammalian distributions explain the favourable areas for Ebola virus in the wild. We demonstrate that mammalian biogeography contributes to explaining the distribution of Ebola virus in Africa, although vegetation may also underscore clear limits to the presence of the virus. Our model suggests that the Ebola virus may be even more widespread than previously suspected, given that additional favourable areas are found throughout the coastal areas of West and Central Africa, stretching from Cameroon to Guinea, and extend further East into the East African Lakes region. Our findings show that the most favourable area for the Ebola virus is significantly associated with the presence of the virus in non-human mammals. Core areas are surrounded by regions of intermediate favourability, in which human infections of unknown source were found. The difference in association between humans and other mammals and the virus may offer further

Observations by the Cloud Imaging and Particle Size (CIPS) instrument on the Aeronomy of Ice in the Mesosphere (AIM) satellite have demonstrated the existence of Polar Mesospheric Cloud (PMC) regions populated by particles whose mean sizes range between 60 and 100 nm (radii of equivalent volume spheres). It is known from numerous satellite experiments that typical mean PMC particle sizes are of the order of 40-50 nm. Determination of particle size by CIPS is accomplished by measuring the scattering of solar radiation at various scattering angles at a spatial resolution of 25 km(2). In this size range we find a robust anti-correlation between mean particle size and albedo. These very-large particle-low-ice (VLP-LI) clouds occur over spatially coherent areas. The surprising result is that VLP-LI are frequently present either in the troughs of gravity wave-like features or at the edges of PMC voids. We postulate that an association with gravity waves exists in the low-temperature summertime mesopause region, and illustrate the mechanism by a gravity wave simulation through use of the 2D Community Aerosol and Radiation Model for Atmospheres (CARMA). The model results are consistent with a VLP-LI population in the cold troughs of monochromatic gravity waves. In addition, we find such events in Whole Earth Community Climate Model/CARMA simulations, suggesting the possible importance of sporadic downward winds in heating the upper cloud regions. This newly-discovered association enhances our understanding of the interaction of ice microphysics with dynamical processes in the upper mesosphere. Published by Elsevier Ltd.

Ebola virus is responsible for the fatal Ebola-virus disease (EVD). Links between EVD outbreaks in Africa and 3 chiropteran species, presumed to be reservoirs for the Ebola virus, have been suggested, but discussions are still on-going. There is also evidence of significant virus spillover among mammal species not suspected to be natural hosts (e.g. chimpanzees, gorillas and duikers). We mapped the potential distribution of the Ebola virus in Africa based on both environmental and zoogeographic descriptors. We employed distribution modelling using the Favourability Function, alongside a complement of biogeographic approaches including chorotype analysis. We obtained a significantly well-calibrated model defining the distribution of environmentally favourable areas for the presence of Ebola virus, which was outperformed by a model determining favourable areas according to mammalian biogeography. Finally, we built a model in which the combined landscape and mammalian distribution types better explained the distribution of Ebola virus independent of human-to-human transmissions. Our findings show that the core area for the virus is associated with infections of known animal origin, but surrounded by areas where human infections of unknown source were found. This difference in the association between human and animals and the virus may offer further insights to better understand how EVD can spread, as well as providing the basis for an early warning system based on where human contact with multiple animal species may occur. We propose a biogeographically-justified list of at least 64 mammal species whose link with Ebola virus is worth investigating.

Pygmy populations occupy a vast territory extending west-to-east along the central African belt from the Congo Basin to Lake Victoria. However, their numbers and actual distribution is not known precisely. Here, we undertake this task by using locational data and population sizes for an unprecedented number of known Pygmy camps and settlements (n = 654) in five of the nine countries where currently distributed. With these data we develop spatial distribution models based on the favourability function, which distinguish areas with favourable environmental conditions from those less suitable for Pygmy presence. Highly favourable areas were significantly explained by presence of tropical forests, and by lower human pressure variables. For documented Pygmy settlements, we use the relationship between observed population sizes and predicted favourability values to estimate the total Pygmy population throughout Central Africa. We estimate that around 920,000 Pygmies (over 60% in DRC) is possible within favourable forest areas in Central Africa. We argue that fragmentation of the existing Pygmy populations, alongside pressure from extractive industries and sometimes conflict with conservation areas, endanger their future. There is an urgent need to inform policies that can mitigate against future external threats to these indigenous peoples’ culture and lifestyles.

Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250-m-resolution land-cover map of the western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1,300-km, 8-day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. Several classes were significantly connected with agriculture, fishing, overall hunting, and more specifically the hunting of primates, red brocket deer, black agouti, and white-lipped peccary. We then characterized land classes using greenness and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Our results show that TEK-based approaches can serve as a basis for validating the livelihood relevance of landscapes in high-value conservation areas, which can form the basis for furthering the management of natural resources in these regions.

We use data on game harvest from 60 Pygmy and non-Pygmy settlements in the Congo Basin forests to examine whether hunting patterns and prey profiles differ between the two hunter groups. For each group, we calculate hunted animal numbers and biomass available per inhabitant, P, per year (harvest rates) and killed per hunter, H, per year (extraction rates). We assess the impact of hunting of both hunter groups from estimates of numbers and biomass of prey species killed per square kilometre, and by examining the proportion of hunted taxa of low, medium and high population growth rates as a measure of their vulnerability to overhunting. We then map harvested biomass (kg-1P-1Yr-1) of bushmeat by Pygmies and non-Pygmies throughout the Congo Basin. Hunting patterns differ between Pygmies and non-Pygmies; Pygmies take larger and different prey and non-Pygmies sell more for profit. We show that non-Pygmies have a potentially more severe impact on prey populations than Pygmies. This is because non-Pygmies hunt a wider range of species, and twice as many animals are taken per square kilometre. Moreover, in non-Pygmy settlements there was a larger proportion of game taken of low population growth rate. Our harvest map shows that the non-Pygmy population may be responsible for 27 times more animals harvested than the Pygmy population. Such differences indicate that the intense competition that may arise from the more widespread commercial hunting by non-Pygmies is a far more important constraint and source of conflict than are protected areas.

We studied links between human malnutrition and wild meat availability within the Rainforest Biotic Zone in central Africa. We distinguished two distinct hunted mammalian diversity distributions, one in the rainforest areas (Deep Rainforest Diversity, DRD) containing taxa of lower hunting sustainability, the other in the northern rainforest-savanna mosaic, with species of greater hunting potential (Marginal Rainforest Diversity, MRD). Wild meat availability, assessed by standing crop mammalian biomass, was greater in MRD than in DRD areas. Predicted bushmeat extraction was also higher in MRD areas. Despite this, stunting of children, a measure of human malnutrition, was greater in MRD areas. Structural equation modeling identified that, in MRD areas, mammal diversity fell away from urban areas, but proximity to these positively influenced higher stunting incidence. In DRD areas, remoteness and distance from dense human settlements and infrastructures explained lower stunting levels. Moreover, stunting was higher away from protected areas. Our results suggest that in MRD areas, forest wildlife rational use for better human nutrition is possible. By contrast, the relatively low human populations in DRD areas currently offer abundant opportunities for the continued protection of more vulnerable mammals and allow dietary needs of local populations to be met.