Spatiotemporal Dynamics of Hantavirus Cardiopulmonary Syndrome Transmission Risk in Brazil

Background: Hantavirus disease in humans is rare but frequently lethal in the Neotropics. Several abundant and widely distributed Sigmodontinae rodents are the primary hosts of Orthohantavirus and, in combination with other factors, these rodents can shape hantavirus disease. Here, we assessed the influence of host diversity, climate, social vulnerability and land use change on the risk of hantavirus disease in Brazil over 24 years. Methods: Landscape variables (native forest, forestry, sugarcane, maize and pasture), climate (temperature and precipitation), and host biodiversity (derived through niche models) were used in spatiotemporal models, using the 5570 Brazilian municipalities as units of analysis. Results: Amounts of native forest and sugarcane, combined with temperature, were the most important factors influencing the increase of disease risk. Population at risk (rural workers) and rodent host diversity also had a positive effect on disease risk. Conclusions: Land use change—especially the conversion of native areas to sugarcane fields—can have a significant impact on hantavirus disease risk, likely by promoting the interaction between the people and the infected rodents. Our results demonstrate the importance of understanding the interactions between landscape change, rodent diversity, and hantavirus disease incidence, and suggest that land use policy should consider disease risk. Meanwhile, our risk map can be used to help allocate preventive measures to avoid disease.publishedVersio

Effects of Land Cover on the Movement of Frugivorous Birds in a Heterogeneous Landscape

<div><p>Movement is a key spatiotemporal process that enables interactions between animals and other elements of nature. The understanding of animal trajectories and the mechanisms that influence them at the landscape level can yield insight into ecological processes and potential solutions to specific ecological problems. Based upon optimal foraging models and empirical evidence, we hypothesized that movement by thrushes is highly tortuous (low average movement speeds and homogeneous distribution of turning angles) inside forests, moderately tortuous in urban areas, which present intermediary levels of resources, and minimally tortuous (high movement speeds and turning angles next to 0 radians) in open matrix types (e.g., crops and pasture). We used data on the trajectories of two common thrush species (<i>Turdus rufiventris</i> and <i>Turdus leucomelas</i>) collected by radio telemetry in a fragmented region in Brazil. Using a maximum likelihood model selection approach we fit four probability distribution models to average speed data, considering short-tailed, long-tailed, and scale-free distributions (to represent different regimes of movement variation), and one distribution to relative angle data. Models included land cover type and distance from forest-matrix edges as explanatory variables. Speed was greater farther away from forest edges and increased faster inside forest habitat compared to urban and open matrices. However, turning angle was not influenced by land cover. Thrushes presented a very tortuous trajectory, with many displacements followed by turns near 180 degrees. Thrush trajectories resembled habitat and edge dependent, tortuous random walks, with a well-defined movement scale inside each land cover type. Although thrushes are habitat generalists, they showed a greater preference for forest edges, and thus may be considered edge specialists. Our results reinforce the importance of studying animal movement patterns in order to understand ecological processes such as seed dispersal in fragmented areas, where the percentage of remaining habitat is dwindling.</p></div

Average speeds of thrushes as a function of distances from edge, considering land cover classes.

<p>The dashed line represents the forest edges; green (forest), blue (open matrix—pastures and crops) and red (urban areas) lines represent the expected values for the mean speeds of individuals according to the exponential model M11, which considers the parameter settings being influenced by landscape variables (forest, open matrices and urban areas) and the forest edge distances. Speeds increase as individuals move away from forest edges.</p

Competing models using turning angles for the trajectories for <i>Turdus leucomelas</i> and <i>T</i>. <i>rufiventris</i>.

<p>Plausible model in italic. K is the number of estimated parameters and the <i>w</i> Akaike weights (relative likelihood of the model) and the <i>w</i> is the Akaike weights (relative likelihood of the model).</p

Predictions for average speed and turning angles of thrushes' trajectories in a fragmented landscape.

<p>Alternative hypotheses are explained and shown graphically considering the effects of land cover variables, land cover type, and distance to forest edges. In hypothesis H1 for average speed, zero values represent the contact area between two land cover classes (i.e. the edge).</p

Distribution of turning angles.

<p>Black points around the circle represent the relative angle observations. Note the high frequency of angle values of +180° or −180° (π or -π radians), which represents more abrupt turns and is characteristic of tortuous walks.</p

Study area encompasses the city limits of Itatiba, State of São Paulo, southeastern Brazil.

<p>The red points correspond to locations where <i>T</i>. <i>rufiventris</i> and <i>T</i>. <i>leucomelas</i> were captured. Land cover composition was: 51.0% pasture, 0.1% crops (mainly <i>Citrus</i> and corn fields), 14.9% urban areas, 1.1% water, 23.4% forest, 9.5% old plantations of <i>Eucalyptus</i> embedded in forested areas. Live fences are formed by lines of native trees, such as <i>Casearia sylvestris</i>, <i>Lithraea mollioides</i> and <i>Erythroxyllum deciduum</i>, located on different properties.</p

Competing models describing average speed for <i>Turdus leucomelas</i> and <i>T</i>. <i>rufiventris</i>.

<p>Plausible model in italic. K is the number of estimated parameters and the <i>w</i> is the Akaike weights (relative likelihood of the model).</p

Fragmented tropical forests lose mutualistic plant–animal interactions

Abstract Aim Forest fragmentation is among the principal causes of global biodiversity loss, yet how it affects mutualistic interactions between plants and animals at large spatial scale is poorly understood. In particular, tropical forest regeneration depends on animal-mediated seed dispersal, but the seed-dispersing animals face rapid decline due to forest fragmentation and defaunation. Here, we assess how fragmentation influences the pairwise interactions between 407 seed disperser and 1,424 tree species in a highly fragmented biodiversity hotspot. Location Atlantic Forest, South America. Methods We predicted interaction networks in 912 sites covering the entire biome by combining verified interaction data with co-occurrence probabilities obtained from a spatially explicit joint species distribution model. We identified keystone seed dispersers by computing a species-specific keystone index and by selecting those species belonging to the top 5% quantile. Results We show that forest fragmentation affects seed dispersal interactions negatively, and the decreased area of functionally connected forest, rather than increased edge effects, is the main driver behind the loss of interactions. Both the seed disperser availability for the local tree communities and in particular the proportion of interactions provided by keystone seed dispersers decline with increasing degree of fragmentation. Importantly, just 21 keystone species provided >40% of all interactions. The numbers of interactions provided by keystone and non-keystone species, however, were equally negatively affected by fragmentation, suggesting that seed dispersal interactions may not be rewired under strong fragmentation effects. Conclusions We highlight the importance of understanding the fragmentation-induced compositional shifts in seed disperser communities as they may lead to lagged and multiplicative effects on tree communities. Our results illustrate the utility of model-based prediction of interaction networks as well as model-based identification of keystone species as a tool for prioritizing conservation efforts. Similar modelling approaches could be applied to other threatened ecosystems and interaction types globally.Peer reviewe