Geographical Distribution of Ljungan Virus in Small Mammals in Europe

Ljungan virus (LV), which belongs to the Parechovirus genus in the Picornaviridae family, was first isolated from bank voles (Myodes glareolus) in Sweden in 1998 and proposed as a zoonotic agent. To improve knowledge of the host association and geographical distribution of LV, tissues from 1685 animals belonging to multiple rodent and insectivore species from 12 European countries were screened for LV-RNA using reverse transcriptase (RT)-PCR. In addition, we investigated how the prevalence of LV-RNA in bank voles is associated with various intrinsic and extrinsic factors. We show that LV is widespread geographically, having been detected in at least one host species in nine European countries. Twelve out of 21 species screened were LV-RNA PCR positive, including, for the first time, the red vole (Myodes rutilus) and the root or tundra vole (Alexandromys formerly Microtus oeconomus), as well as in insectivores, including the bicolored white-toothed shrew (Crocidura leucodon) and the Valais shrew (Sorex antinorii). Results indicated that bank voles are the main rodent host for this virus (overall RT-PCR prevalence: 15.2%). Linear modeling of intrinsic and extrinsic factors that could impact LV prevalence showed a concave-down relationship between body mass and LV occurrence, so that subadults had the highest LV positivity, but LV in older animals was less prevalent. Also, LV prevalence was higher in autumn and lower in spring, and the amount of precipitation recorded during the 6 months preceding the trapping date was negatively correlated with the presence of the virus. Phylogenetic analysis on the 185 base pair species-specific sequence of the 5' untranslated region identified high genetic diversity (46.5%) between 80 haplotypes, although no geographical or host-specific patterns of diversity were detected.

The effects of habitat loss and fragmentation on plant functional traits and functional diversity: what do we know so far?

Habitat loss and fragmentation result in significant landscape changes that ultimately affect plant diversity and add uncertainty to how natural areas will respond to future global change. This uncertainty is important given that the loss of biodiversity often includes losing key ecosystem functions. Few studies have explored the effects of landscape changes on plant functional diversity and evidence so far has shown far more pervasive effects than previously reported by species richness and composition studies. Here we present a review on the impact of habitat loss and fragmentation on (1) individual functional traits-related to persistence, dispersal and establishment-and (2) functional diversity. We also discuss current knowledge gaps and propose ways forward. From the literature review we found that studies have largely focused on dispersal traits, strongly impacted by habitat loss and fragmentation, while traits related to persistence were the least studied. Furthermore, most studies did not distinguish habitat loss from spatial fragmentation and were conducted at the plot or fragment-level, which taken together limits the ability to generalize the scale-dependency of landscape changes on plant functional diversity. For future work, we recommend (1) clearly distinguishing the effects of habitat loss from those of fragmentation, and (2) recognizing the scale-dependency of predicted responses when functional diversity varies in time and space. We conclude that a clear understanding of the effects of habitat loss and fragmentation on functional diversity will improve predictions of the resiliency and resistance of plant communities to varying scales of disturbance.

The DIARS toolbox: a spatially explicit approach to monitor alien plant invasions through remote sensing

The synergies between remote sensing technologies and ecological research have opened new avenues for the study of alien plant invasions worldwide. Such scientific advances have greatly improved our capacity to issue warnings, develop early-response systems and assess the impacts of alien plant invasions on biodiversity and ecosystem functioning. Hitherto, practical applications of remote sensing approaches to support nature conservation actions are lagging far behind scientific advances. Yet, for some of these technologies, knowledge transfer is difficult due to the complexity of the different data handling procedures and the huge amounts of data it involves per spatial unit.

In this context, the next logical step is to develop clear guidelines for the application of remote sensing data to monitor and assess the impacts of alien plant invasions, that enable scientists, landscape managers and policy makers to fully exploit the tools which are currently available. It is desirable to have such guidelines accompanied by freely available remote sensing data and generated in a free and open source environment that increases the availability and affordability of these new technologies.

Here we present a toolbox that provides an easy-to-use, flexible, transparent and open source set of tools to sample, map, model and assess the impact of alien plant invasions using two high-resolution remote sensing products (hyperspectral and LiDAR images). This online toolbox includes a real case dataset designed to facilitate testing and training in any computer system and processing capacity.

Anticipating species distributions: Handling sampling effort bias under a Bayesian framework

Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions.

Cartograms tool to represent spatial uncertainty in species distribution

Species distribution models have become an important tool for biodiversity monitoring. Like all statistical modelling techniques developed based on field data, they are prone to uncertainty due to bias in the sampling (e.g. identification, effort, detectability). In this study, we explicitly quantify and map the uncertainty derived from sampling effort bias. With that aim, we extracted data from the widely used GBIF dataset to map this semantic bias using cartograms.

A virtual species set for robust and reproducible species distribution modelling tests

Predicting species potential and future distribution has become a relevant tool in biodiversity monitoring and conservation. In this data article we present the suitability map of a virtual species generated based on two bioclimatic variables, and a dataset containing more than 700,000 random observations at the extent of Europe. The dataset includes spatial attributes such as: distance to roads, protected areas, country codes, and the habitat suitability of two spatially clustered species (grassland and forest species) and a wide-spread species.

Indirect interactions among tropical tree species through shared rodent seed predators: a novel mechanism of tree species coexistence

The coexistence of numerous tree species in tropical forests is commonly explained by negative dependence of recruitment on the conspecific seed and tree density due to specialist natural enemies that attack seeds and seedlings ('Janzen-Connell' effects). Less known is whether guilds of shared seed predators can induce a negative dependence of recruitment on the density of different species of the same plant functional group. We studied 54 plots in tropical forest on Barro Colorado Island, Panama, with contrasting mature tree densities of three coexisting large seeded tree species with shared seed predators. Levels of seed predation were far better explained by incorporating seed densities of all three focal species than by conspecific seed density alone. Both positive and negative density dependencies were observed for different species combinations. Thus, indirect interactions via shared seed predators can either promote or reduce the coexistence of different plant functional groups in tropical forest.

Modeling the spatial distribution and fruiting pattern of a key tree species in a neotropical forest: methodology and potential applications

Background

The movement patterns of wild animals depend crucially on the spatial and temporal availability of resources in their habitat. To date, most attempts to model this relationship were forced to rely on simplified assumptions about the spatiotemporal distribution of food resources. Here we demonstrate how advances in statistics permit the combination of sparse ground sampling with remote sensing imagery to generate biological relevant, spatially and temporally explicit distributions of food resources. We illustrate our procedure by creating a detailed simulation model of fruit production patterns for Dipteryx oleifera, a keystone tree species, on Barro Colorado Island (BCI), Panama.

Methodology and Principal Findings

Aerial photographs providing GPS positions for large, canopy trees, the complete census of a 50-ha and 25-ha area, diameter at breast height data from haphazardly sampled trees and long-term phenology data from six trees were used to fit 1) a point process model of tree spatial distribution and 2) a generalized linear mixed-effect model of temporal variation of fruit production. The fitted parameters from these models are then used to create a stochastic simulation model which incorporates spatio-temporal variations of D. oleifera fruit availability on BCI.

Conclusions and Significance

We present a framework that can provide a statistical characterization of the habitat that can be included in agent-based models of animal movements. When environmental heterogeneity cannot be exhaustively mapped, this approach can be a powerful alternative. The results of our model on the spatio-temporal variation in D. oleifera fruit availability will be used to understand behavioral and movement patterns of several species on BCI.