A framework for habitat monitoring and climate change modelling: construction and validation of the Environmental Stratification of Estonia

Environmental stratifications provide the framework for efficient surveillance and monitoring of biodiversity and ecological resources, as well as modelling exercises. An obstacle for agricultural landscape monitoring in Estonia has been the lack of a framework for the objective selection of monitoring sites. This paper describes the construction and testing of the Environmental Stratification of Estonia (ESE). Principal components analysis was used to select the variables that capture the most amount of variation. Seven climate variables and topography were selected and subsequently subjected to the ISODATA clustering routine in order to produce relatively homogeneous environmental strata. The ESE contains eight strata, which have been described in terms of soil, land cover and climatic parameters. In order to assess the reliability of the stratification procedure for the selection of monitoring sites, the ESE was compared with the previous map of Landscape Regions of Estonia and correlated with five environmental data sets. All correlations were significant. The stratification has therefore already been used to extend the current series of samples in agricultural landscapes into a more statistically robust series of monitoring sites. The potential for applying climate change scenarios to assess the shifts in the strata and associated ecological impacts is also examined.</p

The Earth Observation Data for Habitat Monitoring (EODHaM) system

To support decisions relating to the use and conservation of protected areas and surrounds, the EU-funded BIOdiversity multi-SOurce monitoring System: from Space TO Species (BIO_SOS) project has developed the Earth Observation Data for HAbitat Monitoring (EODHaM) system for consistent mapping and monitoring of biodiversity. The EODHaM approach has adopted the Food and Agriculture Organization Land Cover Classification System (LCCS) taxonomy and translates mapped classes to General Habitat Categories (GHCs) from which Annex I habitats (EU Habitats Directive) can be defined. The EODHaM system uses a combination of pixel and object-based procedures. The 1st and 2nd stages use earth observation (EO) data alone with expert knowledge to generate classes according to the LCCS taxonomy (Levels 1 to 3 and beyond). The 3rd stage translates the final LCCS classes into GHCs from which Annex I habitat type maps are derived. An additional module quantifies changes in the LCCS classes and their components, indices derived from earth observation, object sizes and dimensions and the translated habitat maps (i.e., GHCs or Annex I). Examples are provided of the application of EODHaM system elements to protected sites and their surrounds in Italy, Wales (UK), the Netherlands, Greece, Portugal and India

Indicateurs de biodiversité dans les exploitations agricoles biologiques et conventionnelles des Vallées et Coteaux de Gascogne, cas d’étude français du projet européen BIOBIO

Dans le cadre du projet européen BIOBIO, nous avons comparé entre pays les richesses en habitats et richesses spécifiques cumulées de quatre groupes taxonomiques (plantes, abeilles sauvages, araignées, vers de terre), de 169 exploitations biologiques ou conventionnelles appartenant à 10 pays. Pour le cas d’étude français, Vallées et Coteaux de Gascogne, les corrélations entre indicateurs directs (richesses spécifiques des taxons et habitats) et indirects (pratiques agricoles) de biodiversité, relevés dans 8 exploitations conventionnelles et 8 biologiques, ont été recherchées. Les résultats montrent que le nombre d’habitats cultivés et surtout semi-naturels par exploitation est le principal facteur déterminant le niveau de biodiversité à cette échelle, pour le cas d’étude français comme pour les autres cas d’étude. Ce facteur explique en partie le plus haut niveau de biodiversité observé pour le cas d’étude français. Néanmoins, les pratiques, spécifiques ou non des modes de production biologique et conventionnelle, gouvernent généralement les paramètres de biodiversité à l’échelle de l’habitat. In fine, le projet propose la méthode BIOBIO de suivi de la biodiversité dans les exploitations agricoles

Farmland biodiversity and agricultural management on 237 farms in 13 European and two African regions

Farmland is a major land cover type in Europe and Africa and provides habitat for numerous species. The severe decline in farmland biodiversity of the last decades has been attributed to changes in farming practices, and organic and low-input farming are assumed to mitigate detrimental effects of agricultural intensification on biodiversity. Since the farm enterprise is the primary unit of agricultural decision making, management-related effects at the field scale need to be assessed at the farm level. Therefore, in this study, data were collected on habitat characteristics, vascular plant, earthworm, spider, and bee communities and on the corresponding agricultural management in 237 farms in 13 European and two African regions. In 15 environmental and agricultural homogeneous regions, 6–20 farms with the same farm type (e.g., arable crops, grassland, or specific permanent crops) were selected. If available, an equal number of organic and non-organic farms were randomly selected. Alternatively, farms were sampled along a gradient of management intensity. For all selected farms, the entire farmed area was mapped, which resulted in total in the mapping of 11 338 units attributed to 194 standardized habitat types, provided together with additional descriptors. On each farm, one site per available habitat type was randomly selected for species diversity investigations. Species were sampled on 2115 sites and identified to the species level by expert taxonomists. Species lists and abundance estimates are provided for each site and sampling date (one date for plants and earthworms, three dates for spiders and bees). In addition, farmers provided information about their management practices in face-to-face interviews following a standardized questionnaire. Farm management indicators for each farm are available (e.g., nitrogen input, pesticide applications, or energy input). Analyses revealed a positive effect of unproductive areas and a negative effect of intensive management on biodiversity. Communities of the four taxonomic groups strongly differed in their response to habitat characteristics, agricultural management, and regional circumstances. The data has potential for further insights into interactions of farmland biodiversity and agricultural management at site, farm, and regional scale

A High-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring

Aim To develop a novel global spatial framework for the integration and analysis of ecological and environmental data. Location The global land surface excluding Antarctica. Methods A broad set of climate-related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis (PCA). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature. Results The global environmental stratification (GEnS) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the Kappa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS. Main conclusions The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research

Ecological networks as a new approach for nature conservation in Turkey: A case study of Izmir Province (vol 90, pg 143, 2009)

WOS: 00027922810000

Identifying and prioritising services in European terrestrial and freshwater ecosystems

Ecosystems are multifunctional and provide humanity with a broad array of vital services. Effective management of services requires an improved evidence base, identifying the role of ecosystems in delivering multiple services, which can assist policy-makers in maintaining them. Here, information from the literature and scientific experts was used to systematically document the importance of services and identify trends in their use and status over time for the main terrestrial and freshwater ecosystems in Europe. The results from this review show that intensively managed ecosystems contribute mostly to vital provisioning services (e.g. agro-ecosystems provide food via crops and livestock, and forests provide wood), while semi-natural ecosystems (e.g. grasslands and mountains) are key contributors of genetic resources and cultural services (e.g. aesthetic values and sense of place). The most recent European trends in human use of services show increases in demand for crops from agro-ecosystems, timber from forests, water flow regulation from rivers, wetlands and mountains, and recreation and ecotourism in most ecosystems, but decreases in livestock production, freshwater capture fisheries, wild foods and virtually all services associated with ecosystems which have considerably decreased in area (e.g. semi-natural grasslands). The condition of the majority of services show either a degraded or mixed status across Europe with the exception of recent enhancements in timber production in forests and mountains, freshwater provision, water/erosion/natural hazard regulation and recreation/ecotourism in mountains, and climate regulation in forests. Key gaps in knowledge were evident for certain services across all ecosystems, including the provision of biochemicals and natural medicines, genetic resources and the regulating services of seed dispersal, pest/disease regulation and invasion resistance