Spatial variation of trace metals within intertidal beds of native mussels (Mytilus edulis) and non-native Pacific oysters (Crassostrea gigas): implications for the food web?

Abstract Pollution is of increasing concern within coastal regions and the prevalence of invasive species is also rising. Yet the impact of invasive species on the distribution and potential trophic transfer of metals has rarely been examined. Within European intertidal areas, the non-native Pacific oyster (Crassostrea gigas) is becoming established, forming reefs and displacing beds of the native blue mussel (Mytilus edulis). The main hypothesis tested is that the spatial pattern of metal accumulation within intertidal habitats will change should the abundance and distribution of C. gigas continue to increase. A comparative analysis of trace metal content (cadmium, lead, copper and zinc) in both species was carried out at four shores in south-east England. Metal concentrations in bivalve and sediment samples were determined after acid digestion by inductively coupled plasma-optical emission spectrometry. Although results showed variation in the quantities of zinc, copper and lead (mg m-2) in the two bivalve species, differences in shell thickness are also likely to influence the feeding behaviour of predators and intake of metals. The availability and potential for trophic transfer of metals within the coastal food web, should Pacific oysters transform intertidal habitats, is discussed

Assessing differences in connectivity based on habitat versus movement models for brown bears in the Carpathians

Context. Connectivity assessments typically rely on resistance surfaces derived from habitat models, assuming that higher-quality habitat facilitates movement. This assumption remains largely untested though, and it is unlikely that the same environmental factors determine both animal movements and habitat selection, potentially biasing connectivity assessments. Objectives. We evaluated how much connectivity assessments differ when based on resistance surfaces from habitat versus movement models. In addition, we tested how sensitive connectivity assessments are with respect to the parameterization of the movement models. Methods. We parameterized maximum entropy models to predict habitat suitability, and step selection functions to derive movement models for brown bear (Ursus arctos) in the northeastern Carpathians. We compared spatial patterns and distributions of resistance values derived from those models, and locations and characteristics of potential movement corridors. Results. Brown bears preferred areas with high forest cover, close to forest edges, high topographic complexity, and with low human pressure in both habitat and movement models. However, resistance surfaces derived from the habitat models based on predictors measured at broad and medium scales tended to underestimate connectivity, as they predicted substantially higher resistance values for most of the study area, including corridors. Conclusions. Our findings highlighted that connectivity assessments should be based on movement information if available, rather than generic habitat models. However, the parameterization of movement models is important, because the type of movement events considered, and the sampling method of environmental covariates can greatly affect connectivity assessments, and hence the predicted corridors

La Red Internacional de Inventarios Forestales (BIOTREE-NET) en Mesoamérica: avances, retos y perspectivas futuras

Conservation efforts in Neotropical regions are often hindered by lack of data, since for many species there is a vacuum of information, and many species have not even been described yet. The International Network of Forest Inventory Plots (BIOTREE-NET) gathers and facilitates access to tree data from forest inventory plots in Mesoamerica, while encouraging data exchange between researchers, managers and conservationists. The information is organised and standardised into a single database that includes spatially explicit data. This article describes the scope and objectives of the network, its progress, and the challenges and future perspectives. The database includes above 50000 tree records of over 5000 species from more than 2000 plots distributed from southern Mexico through to Panama. Information is heterogeneous, both in nature and shape, as well as in the geographical coverage of inventory plots. The database has a relational structure, with 12 inter-connected tables that include information about plots, species names, dbh, and functional attributes of trees. A new system that corrects typographical errors and achieves taxonomic and nomenclatural standardization was developed using The Plant List (http://theplantlist.org/) as reference. Species distribution models have been computed for around 1700 species using different methods, and they will be publicly accessible through the web site in the future (http://portal.biotreenet.com). Although BIOTREE-NET has contributed to the development of improved species distribution models, its main potential lies, in our opinion, in studies at the community level. Finally, we emphasise the need to expand the network and encourage researchers willing to share data and to join the network and contribute to the generation of further knowledge about forest biodiversity in Neotropical regions

Use of a Bayesian Belief Network to predict the impacts of commercializing non-timber forest products on livelihoods

Commercialization of non-timber forest products (NTFPs) has been widely promoted as a means of sustainably developing tropical forest resources, in a way that promotes forest conservation while supporting rural livelihoods. However, in practice, NTFP commercialization has often failed to deliver the expected benefits. Progress in analyzing the causes of such failure has been hindered by the lack of a suitable framework for the analysis of NTFP case studies, and by the lack of predictive theory. We address these needs by developing a probabilistic model based on a livelihood framework, enabling the impact of NTFP commercialization on livelihoods to be predicted. The framework considers five types of capital asset needed to support livelihoods: natural, human, social, physical, and financial. Commercialization of NTFPs is represented in the model as the conversion of one form of capital asset into another, which is influenced by a variety of socio-economic, environmental, and political factors. Impacts on livelihoods are determined by the availability of the five types of assets following commercialization. The model, implemented as a Bayesian Belief Network, was tested using data from participatory research into 19 NTFP case studies undertaken in Mexico and Bolivia. The model provides a novel tool for diagnosing the causes of success and failure in NTFP commercialization, and can be used to explore the potential impacts of policy options and other interventions on livelihoods. The potential value of this approach for the development of NTFP theory is discussed. <br/

Species Distribution Modeling in the Tropics: Problems, Potentialities, and the Role of Biological Data for Effective Species Conservation

In this paper we aim to investigate the problems and potentialities of species distribution modeling (SDM) as a tool for conservation planning and policy development and implementation in tropical regions. We reviewed 123 studies published between 1995 and 2007 in five of the leading journals in ecology and conservation, and examined two tropical case studies in which distribution modeling is currently being applied to support conservation planning. We also analyzed the characteristics of data typically used for fitting models within the specific context of modeling tree species distribution in Central America. The results showed that methodological papers outnumbered reports of SDMs being used in an applied context for setting conservation priorities, particularly in the tropics. Most applications of SDMs were in temperate regions and biased towards certain organisms such as mammals and birds. Studies from tropical regions were less likely to be validated than those from temperate regions. Unpublished data from two major tropical case studies showed that those species that are most in need of conservation actions, namely those that are the rarest or most threatened, are those for which SDM is least likely to be useful. We found that only 15% of the tree species of conservation concern in Central America could be reliably modelled using data from a substantial source (Missouri Botanical Garden VAST database). Lack of data limits model validation in tropical areas, further restricting the value of SDMs. We concluded that SDMs have a great potential to support biodiversity conservation in the tropics, by supporting the development of conservation strategies and plans, identifying knowledge gaps, and providing a tool to examine the potential impacts of environmental change. However, for this potential to be fully realized, problems of data quality and availability need to be overcome. Weaknesses in current biological datasets need to be systematically addressed, by increasing collection of field survey data, improving data sharing and increasing structural integration of data sources. This should include use of distributed databases with common standards, referential integrity, and rigorous quality control. Integration of data management with SDMs could significantly add value to existing data resources by improving data quality control and enabling knowledge gaps to be identified. </jats:p