The Influence of Agroforestry and Other Land-Use Types on the Persistence of a Sumatran Tiger (<Emphasis Type="Italic">Panthera tigris sumatrae</Emphasis>) Population: An Individual-Based Model Approach

The importance of preserving both protected areas and their surrounding landscapes as one of the major conservation strategies for tigers has received attention over recent decades. However, the mechanism of how land-use surrounding protected areas affects the dynamics of tiger populations is poorly understood. We developed Panthera Population Persistence (PPP)—an individual-based model—to investigate the potential mechanism of the Sumatran tiger population dynamics in a protected area and under different land-use scenarios surrounding the reserve. We tested three main landscape compositions (single, combined and real land-uses of Tesso-Nilo National Park and its surrounding area) on the probability of and time to extinction of the Sumatran tiger over 20 years in Central Sumatra. The model successfully explains the mechanisms behind the population response of tigers under different habitat landscape compositions. Feeding and mating behaviours of tigers are key factors, which determined population persistence in a heterogeneous landscape. All single land-use scenarios resulted in tiger extinction but had a different probability of extinction within 20 years. If tropical forest was combined with other land-use types, the probability of extinction was smaller. The presence of agroforesty and logging concessions adjacent to protected areas encouraged the survival of tiger populations. However, with the real land-use scenario of Tesso-Nilo National Park, tigers could not survive for more than 10 years. Promoting the practice of agroforestry systems surrounding the park is probably the most reasonable way to steer land-use surrounding the Tesso-Nilo National Park to support tiger conservation.     

Congruence of epicuticular hydrocarbons and tarsal secretions as a principle in beetles

Within beetles, those species that are adapted to life on plants have developed widened tarsi with specialised hairy attachment structures. The capability to adhere to smooth surfaces is based on a liquid film on the surface of these structures, the composition of which is similar to the cuticular lipids. By means of a cluster analysis based on chemical similarities between samples obtained from tarsi or elytra of 35 species using solid phase microextraction, the present study strongly suggests that this chemical congruence is a principle in beetles. This supports the idea of tarsal liquids being part of the cuticular lipid layer and contributes to the understanding of liquid-mediated attachment systems.     

Predicting the distributions of marine organisms at the global scale

We present and evaluate AquaMaps, a presence-only species distribution modelling system that allows the incorporation of expert knowledge about habitat usage and was designed for maximum output of standardized species range maps at the global scale. In the marine environment there is a significant challenge to the production of range maps due to large biases in the amount and location of occurrence data for most species. AquaMaps is compared with traditional presence-only species distribution modelling methods to determine the quality of outputs under equivalently automated conditions. The effect of the inclusion of expert knowledge to AquaMaps is also investigated. Model outputs were tested internally, through data partitioning, and externally against independent survey data to determine the ability of models to predict presence versus absence. Models were also tested externally by assessing correlation with independent survey estimates of relative species abundance. AquaMaps outputs compare well to the existing methods tested, and inclusion of expert knowledge results in a general improvement in model outputs. The transparency, speed and adaptability of the AquaMaps system, as well as the existing online framework which allows expert review to compensate for sampling biases and thus improve model predictions are proposed as additional benefits for public and research use alike.     

Using Data From Seed-Dispersal Modelling to Manage Invasive Tree Species: The Example of Fraxinus pennsylvanica Marshall in Europe

Management strategies to control invasive species need information about dispersal distances to predict establishment potential. Fraxinus pennsylvanica is a North American anemochorous tree species that is invasive in many Central European floodplain forests. To predict seed-dispersal potential, the stochastic model WaldStat was used, which enables different options for directionality (isotropic and anisotropic) to be simulated. In this article, we (1) show empirical results of fructification and seed dispersal for this tree species. The model predicts approximately 250,000 seeds for one F. pennsylvanica tree. These results were used to (2) calculate species-specific dispersal distances and effects of wind direction. To consider the influence of wind on dispersal potential of the tree species, long-distance dispersal (LDD [95th percentile dispersal distance]) was calculated. Mean dispersal distances varied between 47 and 66 m. LDD values modelled along the main wind direction ranged from 60 to 150 m. Seed production, dispersal distance, and direction data were (3) incorporated into theoretical management scenarios for forest ecosystems. Finally (4), we discuss management options and the practical relevance of model scenarios in relation to the accuracy of spatial dispersal predictions. Further analyses should be focused on possible, well-adapted management concepts at stand level that could restrict the potential spread of invasive species.     

Capability and limitations of first-order and diffusion approaches to describe long-term sorption of chlortoluron in soil

This paper compares the capability of a first-order and a spherical diffusion model to describe and predict long-term sorption and desorption processes of chlortoluron in two soils. Chlortoluron sorption was investigated at different time scales utilizing one rate experiment (120 days) and two sorption/desorption experiments. Experimental periods for sorption and desorption were set to 1 day (five desorption steps) and 30 days (three desorption steps), respectively. Upon fitting, the two models satisfactorily described the whole set of data. The spherical diffusion model performed better than the first-order model. We then tested the predictive capability of the models by predicting 30-day sorption/desorption data using kinetic parameters fitted on 1-day sorption/desorption data only. While the spherical diffusion model was able to predict the 30-day data set, the first-order model failed completely. Fitting both models to subsets of the data corresponding to different experimental time scales revealed that the rate parameter as well as the Freundlich coefficient of the first-order model are strongly time-dependent--a property that is not shared by parameters of the spherical diffusion model. The apparent stability of the spherical diffusion model with regard to time dependency of its parameters indicates that sorptive uptake may be diffusion-controlled. This also explains the models greater predictive power across different time scales compared to the first-order model. Finally, we investigate the suitability of solute class specific log-linear relationships between the first-order rate parameter and the Freundlich coefficient presented by earlier researchers in the light of the time dependency observed for the parameters of the first-order model.