MRI newsletter 8: Georeferenced biological databases - A tool for understanding mountain biodiversity

The Mountain Research Initiative invited Dr Eva Spehn, Director of the Global Mountain Biodiversity Assessment (GMBA), and Dr Antoine Guisan, head of the Spatial Ecology Group at the University of Lausanne, to introduce the reader to their coordinated efforts to advance understanding and prediction of mountain biodiversity. Antoine Guisan's EUROMONT project is one of the many scientific projects that may potentially provide data for the new GMBA initiative for a GIS mountain biodiversity database.

DNA banking for plant breeding, biotechnology and biodiversity evaluation.

The manipulation of DNA is routine practice in botanical research and has made a huge impact on plant breeding, biotechnology and biodiversity evaluation. DNA is easy to extract from most plant tissues and can be stored for long periods in DNA banks. Curation methods are well developed for other botanical resources such as herbaria, seed banks and botanic gardens, but procedures for the establishment and maintenance of DNA banks have not been well documented. This paper reviews the curation of DNA banks for the characterisation and utilisation of biodiversity and provides guidelines for DNA bank management. It surveys existing DNA banks and outlines their operation. It includes a review of plant DNA collection, preservation, isolation, storage, database management and exchange procedures. We stress that DNA banks require full integration with existing collections such as botanic gardens, herbaria and seed banks, and information retrieval systems that link such facilities, bioinformatic resources and other DNA banks. They also require efficient and well-regulated sample exchange procedures. Only with appropriate curation will maximum utilisation of DNA collections be achieved.

Conserving biodiversity in production landscapes.

Alternative land uses make different contributions to the conservation of biodiversity and have different implementation and management costs. Conservation planning analyses to date have generally assumed that land is either protected or unprotected, and that the unprotected portion does not contribute to conservation goals. We develop and apply a new planning approach that explicitly accounts for the contribution of a diverse range of land uses to achieving conservation goals. Using East Kalimantan (Indonesian Borneo) as a case study, we prioritize investments in alternative conservation strategies and account for the relative contribution of land uses ranging from production forest to well-managed protected areas. We employ data on the distribution of mammals and assign species-specific conservation targets to achieve equitable protection by accounting for life history characteristics and home range sizes. The relative sensitivity of each species to forest degradation determines the contribution of each land use to achieving targets. We compare the cost effectiveness of our approach to a plan that considers only the contribution of protected areas to biodiversity conservation, and to a plan that assumes that the cost of conservation is represented by only the opportunity costs of conservation to the timber industry. Our preliminary results will require further development and substantial stakeholder engagement prior to implementation; nonetheless we reveal that, by accounting for the contribution of unprotected land, we can obtain more refined estimates of the costs of conservation. Using traditional planning approaches would overestimate the cost of achieving the conservation targets by an order of magnitude. Our approach reveals not only where to invest, but which strategies to invest in, in order to effectively and efficiently conserve biodiversity.

Forecasting the effects of global warming on biodiversity

The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting have limitations. in this article, we compare and discuss the different uses of four forecasting methods: (1) models that consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean-atmosphere-biosphere models, and (4) specics-area curve models that consider all species or large aggregates of species. After outlining the different uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in the solution to the different problems.

Biodiversity study of arthropods collected on rat carrion in Yaounde, Cameroon: first study on forensic entomology in Central Africa

The first investigation of arthropods associated with carrion in Cameroon was carried out within the campus of the University of Yaounde I (Cameroon) from 17thJanuary to 3rd April 2008. Carcasses of rats (Rattus norvegicus Berkenhout, 1769 var WISTAR) were exposed to colonization by the local fauna of arthropods. The invading organisms were collected daily during the study period. 2287 individuals of arthropod belonging to 3 classes, 16 orders, 37 families and 7 subfamilies were identified. The insects assessed were mainly Diptera, Coleoptera and Acari. This study illustrates the high diversity of the necroentomofauna in Cameroon and provides an insight approximation into the succession pattern of invading insect and a weekly estimation of the time of death.

Biodiversity: predictive traits to the rescue

Climate change poses new challenges to the conservation of species, which at present requires data-hungry models to meaningfully anticipate future threats. Now a study suggests that species traits may offer a simpler way to help predict future extinction risks.

Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling.

Ecological-economic optimization of biodiversity conservation under climate change

Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity. The Intergovernmental Panel on Climate Change fourth assessment report(1) cites 28,586 studies demonstrating significant biological changes in terrestrial systems(2). Already high extinction rates, driven primarily by habitat loss, are predicted to increase under climate change(3-6). Yet there is little specific advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity within realistic economic constraints(7). Here we present a systematic ecological and economic analysis of a climate adaptation problem in one of the world's most species-rich and threatened ecosystems: the South African fynbos. We discover a counterintuitive optimal investment strategy that switches twice between options as the available adaptation budget increases. We demonstrate that optimal investment is nonlinearly dependent on available resources, making the choice of how much to invest as important as determining where to invest and what actions to take. Our study emphasizes the importance of a sound analytical framework for prioritizing adaptation investments(4). Integrating ecological predictions in an economic decision framework will help support complex choices between adaptation options under severe uncertainty. Our prioritization method can be applied at any scale to minimize species loss and to evaluate the robustness of decisions to uncertainty about key assumptions.

A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.

Biodiversity of amoebae and amoeba-associated bacteria in water treatment plants.

In this study, we enlarged our previous investigation focusing on the biodiversity of chlamydiae and amoebae in a drinking water treatment plant, by the inclusion of two additional plants and by searching also for the presence of legionellae and mycobacteria. Autochthonous amoebae were recovered onto non-nutritive agar, identified by 18S rRNA gene sequencing, and screened for the presence of bacterial endosymbionts. Bacteria were also searched for by Acanthamoeba co-culture. From a total of 125 samples, we recovered 38 amoebae, among which six harboured endosymbionts (three chlamydiae and three legionellae). In addition, we recovered by amoebal co-culture 11 chlamydiae, 36 legionellae (no L. pneumophila), and 24 mycobacteria (all rapid-growers). Two plants presented a similar percentage of samples positive for chlamydiae (11%), mycobacteria (20%) and amoebae (27%), whereas in the third plant the number of recovered bacteria was almost twice higher. Each plant exhibited a relatively high specific microbiota. Amoebae were mainly represented by various Naegleria species, Acanthamoeba species and Hartmannella vermiformis. Parachlamydiaceae were the most abundant chlamydiae (8 strains in total), and in this study we recovered a new genus-level strain, along with new chlamydiae previously reported. Similarly, about 66% of the recovered legionellae and 47% of the isolated mycobacteria could represent new species. Our work highlighted a high species diversity among legionellae and mycobacteria, dominated by putative new species, and it confirmed the presence of chlamydiae in these artificial water systems.

Impacts of climate change on Swiss biodiversity: An indicator taxa approach

We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of 'greenhouse' gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.