How much will it cost to save grassland diversity?

Peak Science and Environment, Station House, Leadmill Hathersage, Hope Valley S32 1BA, UK; Departamento Ecología Funcional y Biodiversidad, Instituto Pirenaico de Ecología (CSIC) Aptdo. 202, E-50080 Zaragoza, Spain; Institute of Grassland and Environmental Research, North Wyke Research Station, Okehampton, Devon EX20 2SB, UK; Unit of Comparative Plant Ecology, Department of Animal and Plant Sciences, The University, Sheffield S10 2TN, UK; Instituto Multidisciplinario de Biologia Vegetal and Cátedra de Biogeografı́a, FCEyN (CONICET- Universidad Nacional de Córdoba), Casilla de Correo 495 (5000), Córdoba, Argentina; Department of Archaeology, The University, Sheffield S1 4ET, UK; Departamento de Produción Animal, Facultad de Ciencias Agropecuarias, Universidad Nacional de Córdoba, Casilla de Correo 509, 5000 Córdoba, Argentina; Departamento de Desarrollo Rural, Facultad de Ciencias Agropecuarias, Universidad Nacional de Córdoba, Casilla de Correo 509, 5000 Córdoba, Argentina; Departamento de Agricultura y Economı́a Agraria, Universidad de Zaragoza, Miguel Servet 177, 50013 Zaragoza, Spain; Department of Systems Ecology, Faculty of Earth and Life Sciences, Free University, De Boelelaan 1087, 1081 HV Amsterdam, The Netherlands; Institut fũr Landwirtschaftliche Betriebslehre, Universität Hohenheim, Schloss Osthof-Sũd, 70599 Stuttgart, Germany; Faculty of Economics, University of Groningen, Postbus 800, 9700 AV Groningen, Netherlands; Faculty of Spatial Sciences, University of Groningen, Postbus 800, 9700 AV Groningen, Netherlands; Institut Botànic de Barcelona, Parc Montjuı¨c, Av. dels Muntanyans s/n 08038, Barcelona, Spain
Biological Conservation (Impact Factor: 4.04). 07/2004; 122(2):263-273. DOI: 10.1016/j.biocon.2004.07.016

ABSTRACT Conservation initiatives are failing to arrest the global loss of biodiversity. From our mechanistic studies of ecology and economics, we suggest that for grazing lands the root cause of this failure is a powerful economic deterrent to measures designed to protect diversity. We identify an exponential relationship between monetary returns and intensification of farming methods over an extremely wide range of grassland productivities and farm systems. At intermediate to high levels of fertility, however, this exponential increase in financial benefit from intensification is associated with a decline in biodiversity and an acceleration of the ecological processes driving species losses from grassland ecosystems.

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    ABSTRACT: The study aimed at the identification of favourable land use options for semi-natural grassland management and preservation. Economic assessments of energy recovery by the integrated generation of solid fuel and biogas from biomass (IFBB) in comparison with dry fermentation (DF) and hay combustion systems (HC), beef cattle production (BC) and non-refining landscape preservation measures, such as mulching (MU) and composting (CO), were carried out in this study. Energy recovery systems made profitable use of semi-natural grasslands with the highest economic returns attained by IFBB-AO (Return On Investment, ROI: 22.75%) and HC (ROI: 22.00%) systems, followed by the IFBB-SA (ROI: 7.71%) and the DF system (ROI: 6.22%). Animal husbandry (BC) and non-refining management systems (MU, CO) were not profitable considering the current framework conditions. Input parameters critical for profitability were modified in order to identify influences of changing framework conditions.
    Bioresource Technology 09/2012; 119:312–323. · 5.04 Impact Factor
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    Grassland Productivity and Ecosystem Services, Edited by Gilles Lemaire, John Hodgson, Abad Chabbi, 07/2011: chapter 14: pages 129-137; CAB International.
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    ABSTRACT: QuestionsWhat are the main drivers of variation in beta‐diversity for Bromus erectus semi‐natural dry grasslands of habitat 6210(*) at different scales? How should environmental variables and spatial patterns be taken into account to conserve the maximum possible beta‐diversity within the habitat? LocationCentral Italy. Methods We used 195 vegetation relevés distributed in three nested extents: a single mountain, a mountain chain and southern Lazio. Multiple regression on distance matrices was performed using dissimilarity matrices based on: (1) species abundances as response variables; (2) spatial coordinates and environmental parameters (altitude, slope, percentage of rock and stone coverage, aspect, annual rainfall) as explanatory variables. The two groups of explanatory variables were used separately to partition the variation, and jointly to assess the relative contribution of each individual variable. Those variables found to significantly affect beta‐diversity were used to: (1) compare beta‐diversity levels between a set of randomly selected and a set of stratified relevés; and (2) analyse the habitat distribution across environmental gradients. These analyses, together with the curves describing the relationships between spatial distances and composition dissimilarities, were used to inform management decisions for the habitat. ResultsMost of the variance was explained by environmental variables, whose share was higher in the smallest and intermediate extent than in the broadest extent. Community dissimilarity increased in proportion to differences in altitude and spatial distances at every extent. Accordingly, at all the extents, the selection of relevés stratified by altitude or selected taking into account a minimum spatial distance included significantly higher levels of within‐habitat beta‐diversity, than randomly selected relevés. The relation of beta‐diversity to the variation in aspect and annual rainfall varied at different extents. Conclusions Our results demonstrate that dry grassland management plans aimed at conserving the maximum within‐habitat beta‐diversity should take into account variation in environmental variables, among which altitude proved to be a critical factor at every extent. Also, spatial distances positively affect within‐habitat beta‐diversity levels, and scale‐dependent minimum distances among habitat patches should be taken into account when selecting patches of habitat 6210(*) to be conserved in the study area.
    Applied Vegetation Science 07/2013; 16(3). · 2.42 Impact Factor

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