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Bredemeier B.,Leibniz University of Hanover | von Haaren C.,Leibniz University of Hanover | Ruter S.,Leibniz University of Hanover | Reich M.,Leibniz University of Hanover | Meise T.,German Federal Agency for Nature Conservation
Ecological Modelling | Year: 2015

Agricultural practice is one of the most important factors leading to biodiversity loss. EU policies addressing this problem involve the provision of incentives for agri-environmental measures (AEM) and setting of targets for AEM on the national scale (e.g. for the amount of organic farming according to the German sustainability strategy), as well as monitoring their success. For AEM to most efficiently target, implement and monitor, they require comparable evaluation of results, describing their quantitative effects on biodiversity and nature conservation. However, there is a dearth of regional data about species and habitats, parts of biodiversity that are relevant for nature conservation. Thus, quantitative analyses are not typically feasible. Furthermore, impacts of agricultural practices on biodiversity cannot be analysed and evaluated merely from individual cases. Comparisons with average or maximum achievements on different spatial scales (benchmarking) are needed. However, meaningful state and pressure indicators are lacking for modelling the nature conservation value of agricultural fields and the consequences of changing pressures from agricultural practice.In this paper we present a model for evaluating the nature conservation value of field habitats based on projected field flora species richness. We propose a combination of an existing evaluation scale for habitat types, as the basis of the model setup, with field flora species richness. These are combined to obtain differentiated conservation values of field habitats as a measure of agricultural effects. We defined the field flora species richness as the total number of species on a homogenously managed field minus the cultivated crop. Indicators of the model are farming practices and site conditions. Based on an extensive literature review, these indicators were analysed regarding their influence on the flora species richness. Influences of the farming practices were reflected by the crop type, which was used as key indicator. As an outcome, the influence of conventional farming, organic farming and nature conservation oriented management on flora species richness was quantified. Additionally, we integrated the diversity of crop types and (semi-) natural habitats of the surrounding landscape into the model, in order to consider potential effects of landscape heterogeneity on field flora species richness.The model was applied in a case study at the NUTS 3-regional level (Nomenclature of territorial units for statistics), using the example of the AEM organic farming. In a scenario, we evaluated the possible effects of a complete conversion to organic farming on the assumed flora species richness. The results reveal that the modelling approach can be used to test for the effects of (i) conversion between organic and conventional farming, (ii) changes in crop rotations, and (iii) targeted positioning of organic farming or botanical management agreements in comparison to the spatially untargeted offering of payments. © 2014 Elsevier B.V. Source


Keith D.A.,University of New South Wales | Rodriguez J.P.,Venezuelan Institute for Scientific Research | Rodriguez-Clark K.M.,Venezuelan Institute for Scientific Research | Nicholson E.,University of Melbourne | And 31 more authors.
PLoS ONE | Year: 2013

An understanding of risks to biodiversity is needed for planning action to slow current rates of decline and secure ecosystem services for future human use. Although the IUCN Red List criteria provide an effective assessment protocol for species, a standard global assessment of risks to higher levels of biodiversity is currently limited. In 2008, IUCN initiated development of risk assessment criteria to support a global Red List of ecosystems. We present a new conceptual model for ecosystem risk assessment founded on a synthesis of relevant ecological theories. To support the model, we review key elements of ecosystem definition and introduce the concept of ecosystem collapse, an analogue of species extinction. The model identifies four distributional and functional symptoms of ecosystem risk as a basis for assessment criteria: A) rates of decline in ecosystem distribution; B) restricted distributions with continuing declines or threats; C) rates of environmental (abiotic) degradation; and D) rates of disruption to biotic processes. A fifth criterion, E) quantitative estimates of the risk of ecosystem collapse, enables integrated assessment of multiple processes and provides a conceptual anchor for the other criteria. We present the theoretical rationale for the construction and interpretation of each criterion. The assessment protocol and threat categories mirror those of the IUCN Red List of species. A trial of the protocol on terrestrial, subterranean, freshwater and marine ecosystems from around the world shows that its concepts are workable and its outcomes are robust, that required data are available, and that results are consistent with assessments carried out by local experts and authorities. The new protocol provides a consistent, practical and theoretically grounded framework for establishing a systematic Red List of the world's ecosystems. This will complement the Red List of species and strengthen global capacity to report on and monitor the status of biodiversity. Source


Heink U.,Helmholtz Center for Environmental Research | Hauck J.,Helmholtz Center for Environmental Research | Hauck J.,German Center for Integrative Biodiversity Research iDiv Halle Jena Leipzig | Jax K.,Helmholtz Center for Environmental Research | And 2 more authors.
Ecological Indicators | Year: 2015

Although the concept of ecosystem services (ES) has thrived over the last ten years, its operationalization is still in its infancy. A major challenge in operationalizing ES is the selection of scientifically defensible, policy relevant and widely accepted indicators. Here we examine how conceptualizations of ES influence indicator selection, and what criteria (such as validity and relevance to a policy issue) are applied in this process. We analyze how the ES concept is framed in the "Mapping and Assessment of Ecosystems and their Services" (MAES) working group and which indicator selection criteria are used in this project. Our findings indicate that there is still room for improvement in the selection of ES indicators, especially with regard to specific criteria (e.g. validity), and for linking indicators to policy issues. © 2015 Elsevier Ltd. Source


Rice J.,Northwest Atlantic Fisheries Center | Arvanitidis C.,Hellenic Center for Marine Research | Borja A.,Tecnalia | Frid C.,University of Liverpool | And 8 more authors.
Ecological Indicators | Year: 2012

The European Marine Strategy Framework Directive (MSFD) requires European states to maintain their marine waters in 'Good Environmental Status'. The MSFD includes 11 descriptors of "Good Environmental Status" (GES), including "Sea-floor Integrity". This descriptor is defined as: "Sea-floor integrity is at a level that ensures that the structure and functions of the ecosystems are safeguarded and benthic ecosystems, in particular, are not adversely affected." This contribution briefly summarizes the main conclusions of an international expert group established to review the scientific basis for making this concept operational. The experts concluded that consideration of 8 attributes of the seabed system would provide adequate information to meet requirements of the MSFD: (i) substratum, (ii) bioengineers, (iii) oxygen concentration, (iv) contaminants and hazardous substances, (v) species composition, (vi) size distribution, (vii) trophodynamics and (viii) energy flow and life history traits. The experts further concluded that "Good Environmental Status" cannot be defined exclusively as "pristine Environmental Status", but rather status when impacts of all uses were sustainable. Uses are sustainable if two conditions are met:the pressures associated with those uses do not hinder the ecosystem components to retain their natural diversity, productivity and dynamic ecological processesrecovery from perturbations such that the attributes lie within their range of historical natural variation must be rapid and secure. No single specific suite of indicators is proposed, both because no single set of indicators will meet the needs of all EU countries in all regional seas, and because according to the MSFD indicator selection is the prerogative of individual states. However, the need for conceptual consistency in assessing GES throughout European seas should be served if the selection of indicators and the integration of their information content in assessing GES follow the guidance in the report of the TG on Seafloor Integrity. This guidance is presented here in summary form. Informed by this report European Commission selected as indicators for the Sea-floor Integrity: (i) type, abundance, biomass and areal extent of relevant biogenic substrate; (ii) extent of the seabed significantly affected by human activities for the different substrate types; (iii) presence of particularly sensitive and/or tolerant species; (iv) multi-metric indices assessing benthic community condition and functionality, such as species diversity and richness, proportion of opportunistic to sensitive species; (v) proportion of biomass or number of individuals in the macrobenthos above some specified length/size; and (vi) parameters describing the characteristics (shape, slope and intercept) of the size spectrum of the benthic community. Source


Ranft S.,University of Vechta | Pesch R.,University of Vechta | Schroder W.,University of Vechta | Boedeker D.,German Federal Agency for Nature Conservation | And 2 more authors.
Marine Pollution Bulletin | Year: 2011

Concerning increased degradation of marine ecosystems, there is a great political and institutional demand for an array of different tools to restore a good environmental status. Thereby, eutrophication is acknowledged as one of the major human induced stressors which has to be monitored and reduced. The present study concentrates on an assessment of the eutrophication status of the Baltic Sea Protected Areas by use of available data and GIS technologies. Two geodata layers were used for analysis: (1) a map on the eutrophication status of the Baltic Sea generated by the Helsinki Commission applying the HELCOM Eutrophication Assessment Tool (HEAT), and (2) modelled data on atmospheric nitrogen deposition made available by the European Monitoring and Evaluation Programme (EMEP). The results yielded comprehensive and conclusive data indicating that most of the BSPAs may be classified as being 'affected by eutrophication' and underlining the need to decrease the overall emissions of nutrients. © 2011 Elsevier Ltd. Source

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