Forecast increase in invasive rabbit spread into ecosystems of an oceanic island (Tenerife) under climate change.

The European rabbit (Oryctolagus cuniculus) is a pest and a conservation problem on many islands, where its heavy grazing pressure threatens many endemic plants with extinction. Previous studies in its native and introduced range have highlighted the high spatial variability of rabbit abundance at local and landscape scales, depending on many factors such as the existence of different habitats. Modeling of the species can be useful to better understand spatial patterns and to prioritize actions, especially in those regions in which rabbits have become invasive. Here, we investigate the distribution of the European rabbit in Tenerife (Canary Islands, Spain), where the species was introduced during the 15th century and has subsequently changed vegetation composition. Added to the direct effects of rabbits on vegetation, climate change could also have implications for rabbit populations, especially in the alpine ecosystem. To evaluate that, we estimated rabbit abundance in 216 plots randomly distributed on Tenerife island (61 in the alpine ecosystem), modeled the potential current spatial abundance of the species and considered how it might vary under different climate change scenarios. We associated rabbit abundance to a wide selection of abiotic, biotic, and human variables expected to influence rabbit abundance on the island. We found a positive correlation between rabbit abundance and temperature and a negative correlation in the case of precipitation. Hence, according to the models' projections, climate change is expected to enhance rabbit populations in the future. Current higher densities were related to land disturbance and open areas, and a remarkable increase is expected to occur in the alpine ecosystem. Overall, we consider that this study provides valuable information for land managers in the Canary archipelago as it reveals how global warming could indirectly exacerbate the conservation problems of the endemic flora in oceanic islands.

Ecological Requirements for Abundance and Dispersion of Brazilian Yellow Fever Vectors in Tropical Areas.

In the Americas, wild yellow fever (WYF) is an infectious disease that is highly lethal for some non-human primate species and non-vaccinated people. Specifically, in the Brazilian Atlantic Forest, Haemagogus leucocelaenus and Haemagogus janthinomys mosquitoes act as the major vectors. Despite transmission risk being related to vector densities, little is known about how landscape structure affects vector abundance and movement. To fill these gaps, we used vector abundance data and a model-selection approach to assess how landscape structure affects vector abundance, aiming to identify connecting elements for virus dispersion in the state of São Paulo, Brazil. Our findings show that Hg. leucocelaenus and Hg. janthinomys abundances, in highly degraded and fragmented landscapes, are mainly affected by increases in forest cover at scales of 2.0 and 2.5 km, respectively. Fragmented landscapes provide ecological corridors for vector dispersion, which, along with high vector abundance, promotes the creation of risk areas for WYF virus spread, especially along the border with Minas Gerais state, the upper edges of the Serra do Mar, in the Serra da Cantareira, and in areas of the metropolitan regions of São Paulo and Campinas.

The ecology of the banded civet (Hemigalus derbyanus) in Southeast Asia with implications for mesopredator release, zoonotic diseases, and conservation.

Habitat loss and degradation threaten forest specialist wildlife species, but some generalist mesopredators exploit disturbed areas and human-derived food, which brings them into closer contact with humans. Mesopredator release is also important for human health for known zoonotic disease reservoirs, such as Asian civets (Viverridae family), since this group includes the intermediator species for the SARS-CoV-1 outbreak. Here we use camera trapping to evaluate the habitat associations of the widespread banded civet (Hemigalus derbyanus) across its range in Southeast Asia. At the regional scale, banded civet detections among published studies were positively associated with forest cover and negatively associated with human population. At the local scale (within a landscape), hierarchical modeling of new camera trapping showed that abundance was negatively associated with forest loss and positively associated with distance to rivers. These results do not support mesopredator release and suggest a low likelihood overlap with humans in degraded habitats and, therefore, a low risk of zoonotic disease transmission from this species in the wild. We also estimate that banded civet distribution has contracted to under 21% of its currently recognized IUCN Red List range, only 12% of which falls within protected areas, and a precipitous recent decline in population size. Accordingly, we suggest the banded civet's Red List status should be re-evaluated in light of our findings.

Modeling Culicoides abundance in mainland France: implications for surveillance.

BACKGROUND: Biting midges of the genus Culicoides Latreille (Diptera: Ceratopogonidae) are involved in the transmission of several viruses affecting humans and livestock, particularly bluetongue (BTV). Over the last decade, Culicoides surveillance has been conducted discontinuously and at various temporal and spatial scales in mainland France following the BTV epizootics in 2008-2009 and its reemergence and continuous circulation since 2015. The ability to predict seasonal dynamics and spatial abundance of Culicoides spp. is a key element in identifying periods and areas at high risk of transmission in order to strengthen surveillance for early detection and to establish seasonally disease-free zones. The objective of this study was to model the abundance of Culicoides spp. using surveillance data. METHODS: A mixed-effect Poisson model, adjusted for overdispersion and taking into account temperature data at each trap location, was used to model the weekly relative abundance of Culicoides spp. over a year in 24 vector zones, based on surveillance data collected during 2009-2012. Vector zones are the spatial units used for Culicoides surveillance since 2016 in mainland France. RESULTS: The curves of the predicted annual abundance of Culicoides spp. in vector zones showed three different shapes: unimodal, bimodal or plateau, reflecting the temporal variability of the observed counts between zones. For each vector zone, the model enabled to identify periods of vector activity ranging from 25 to 51 weeks. CONCLUSIONS: Although the data were collected for surveillance purposes, our modeling approach integrating vector data with daily temperatures, which are known to be major drivers of Culicoides spp. activity, provided areas-specific predictions of Culicoides spp. abundance. Our findings provide decisions makers with essential information to identify risk periods in each vector zone and guide the allocation of resources for surveillance and control. Knowledge of Culicoides spp. dynamics is also of primary importance for modeling the risk of establishment and spread of midge-borne diseases in mainland France.

Spatial Distribution of Phlebotomus argentipes (Diptera: Psychodidae) in Eastern India, a Case Study Evaluating Multispatial Resolution Remotely Sensed Environmental Evidence and Microclimatic Data.

Remote sensing, a powerful tool for analyzing landscape factors, is being used to explore the spatial ecology of vectors of several diseases. This study aims to explore the role of buffer size in identification and quantification of geo-environmental factors from multispatial resolution satellite data and its application along with microclimatic data to kala-azar vector abundance modeling.Sand fly abundance and microclimatic data were collected from 210 sample sites during the premonsoon and postmonsoon season of 2014 from Muzaffarpur district of Bihar (India). Linear imaging self-scanning sensor (LISS-III; 23.5 m) and advanced wide field sensor (AWiFS; 56 m) imageries were used for generating environmental variables at 300- and 500-m buffer zones. Four analytical models of sand fly density were developed and evaluated for predictive accuracy.A total of 33 geo-environmental and four microclimatic variables were tested for the prediction of sand fly density, of which the best four were maximum temperature, relative humidity, Euclidean nearest-neighbor distance of settlement area to mixed bush-grass land, and surface water body. Predictive accuracy of the LISS-III models was found to be higher than AWiFS models at all buffer sizes.The results show that geo-environmental parameters and microclimatic data are the best predictors for sand fly density modeling. Buffer sizes play an important role in identifying the explanatory variables. Model parameters may be useful in identifying predisposing factors of sand fly habitat suitability at the micro level.

Unmanned Aircraft Systems complement biologging in spatial ecology studies.

The knowledge about the spatial ecology and distribution of organisms is important for both basic and applied science. Biologging is one of the most popular methods for obtaining information about spatial distribution of animals, but requires capturing the animals and is often limited by costs and data retrieval. Unmanned Aircraft Systems (UAS) have proven their efficacy for wildlife surveillance and habitat monitoring, but their potential contribution to the prediction of animal distribution patterns and abundance has not been thoroughly evaluated. In this study, we assess the usefulness of UAS overflights to (1) get data to model the distribution of free-ranging cattle for a comparison with results obtained from biologged (GPS-GSM collared) cattle and (2) predict species densities for a comparison with actual density in a protected area. UAS and biologging derived data models provided similar distribution patterns. Predictions from the UAS model overestimated cattle densities, which may be associated with higher aggregated distributions of this species. Overall, while the particular researcher interests and species characteristics will influence the method of choice for each study, we demonstrate here that UAS constitute a noninvasive methodology able to provide accurate spatial data useful for ecological research, wildlife management and rangeland planning.