European environmental stratifications and typologies: An overview

Hazeu, G.W.; Metzger, Marc J.; Mücher, C.A.; Pérez‐Soba, Marta; Renetzeder, Ch.; Andersen, Erling B.

doi:10.1016/j.agee.2010.01.009

Cited by 58 publications

(41 citation statements)

References 34 publications

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“…Hazeu et al (2011) in order to know the state and trends of the European environments exposed five new European typologies using the spatial environmental datasets. Different methods have been used in each typology: multivariate statistical clustering, multi-scale segmentation (that recognizes objects based on spatial characteristics, the most often used technique in the interpretation of satellite imagery) and f inally, methods based on geographical coherence and on expert knowledge.…”

Section: Techniques Of Typology Classification Analysismentioning

confidence: 99%

An overview of farming system typology methodologies and its use in the study of pasture-based farming system: a review

Mądry

Guerrero²,

Roszkowska-Mądra

et al. 2013

Span. j. agric. res.

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The main objective of the paper is to do a critic study of the use of typology methodologies within pasture-based farming systems (PBFS), especially those situated in less favoured areas, showing in each case the more relevant variables or indicators determining the farming system classification. Another objective is to do an overview of the most used farming system typology methodologies in general. First some considerations about the concept of farming system and approaches to its study have been done. Next, the farming system typology methodologies have been showed in general to different farming systems, but addressed preferably to PBFS. The different tools integrated in these methodologies have been considered: sampling methods, sources of data, variables or indicators obtained from available data and techniques of analysis (statistical or not). Methods for farming system classification have been presented (expert methods, analytical methods or a combination of both types). Among the statistical methods, the multivariate analysis has been overall treated, including the principal component analysis and the cluster analysis. Finally, the use of farming system typology methodologies on different pasture-based farming systems has been presented. The most important aspects considered are following: the main objective of the typology, the main animal species, the employed methods of classification and the main variables involved in this classification.

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Section: Techniques Of Typology Classification Analysismentioning

confidence: 99%

An overview of farming system typology methodologies and its use in the study of pasture-based farming system: a review

Mądry

Guerrero²,

Roszkowska-Mądra

et al. 2013

Span. j. agric. res.

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“…It provides a generic classification that can be adapted for a specific objective, whilst providing suitable zones for environmental reporting (Hazeu et al, 2011). The EnS was created using tried-and-tested statistical clustering procedures on 20 primary physical environmental variables.…”

Section: Test Regions and Sitesmentioning

confidence: 99%

“…In general, the EnS was found to be comparable with regional stratifications and to resolve border effects where divergent environmental conditions are combined into dominant strata (Ortega et al, 2012). The test of a Europe-wide sampling strategy based on the EnS and of a survey protocol for habitats and species based on life forms and general habitat categories (GHCs) has been achieved in EBONE (Bunce et al, 2008;Hazeu et al, 2011). This protocol has been tested in the field in contrasting environments, from boreal conifer forests to hot deserts, but a formal test on its effectiveness in the assessment of species and habitat diversity patterns across a major environmental gradient has not yet been carried out.…”

Section: Introductionmentioning

confidence: 99%

Surveillance of habitats and plant diversity indicators across a regional gradient in the Iberian Peninsula

Ortega

Guerra

Honrado

et al. 2013

Ecological Indicators

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a b s t r a c tLocated in the west of the Mediterranean and with high environmental heterogeneity, the Iberian Peninsula represents a challenging region for designing and implementing observation systems for landscape, habitat and species diversity indicators. Within the framework of a project designed to set up a European Biodiversity Observation Network (EBONE), a standardized protocol for field survey was used in pilot sites located across a major gradient in Portugal and Spain. Results are presented and compared to assess the efficiency of the method in detecting patterns along this gradient. These sites represent different types of Iberian landscapes selected using a stratified random procedure implemented in the Madrid province (Spain) and in the north of Portugal. Species and habitat richness and diversity (as well as their components) are compared in their relation to environmental gradients and survey area. Results from spatial analyses of landscape heterogeneity are also presented and discussed in relation to appropriate indicators. The implications for setting up cost-efficient observation schemes that capture the key indicators effectively are discussed. Perspectives for integration with complementary monitoring schemes targeted at key species, habitat and landscape indicators are also discussed in order to optimize the power and efficiency of these observation networks.

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“…Spatial classification of information and geographical data is essential for their analysis and communication (Metzger et al 2005). Increased availability of spatial environmental data and advances in spatial data processing has led to a range of new European classifications and typologies of biophysical regions (Hazeu et al 2011;EEA 2011). However, few attempts have been made to develop useful classifications and/or typologies focussing on environmental impacts of agricultural innovations.…”

Section: Baseline Conditions Of European Agro-ecosystems (Tc2)mentioning

confidence: 99%

“…This should build on or be co-developed with existing stratifications, typologies and classifications (Andersen et al 2007;Petit et al 2008;Hazeu et al 2011;EEA 2011) with biophysical data relevant for discriminating potential environmental GM crop effects on the previously identified indicators (TC1) from the continuously changing agro-environment. Ecological information on habitats, species, sites with local biological diversity importance, and protected areas should also be integrated.…”

Section: Baseline Conditions Of European Agro-ecosystems (Tc2)mentioning

confidence: 99%

A framework for a European network for a systematic environmental impact assessment of genetically modified organisms (GMO)

Graef¹,

Römbke²,

Binimelis³

et al. 2012

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A peer-reviewed open-access journalFrieder Graef et al. / BioRisk 7: 73-97 (2012) AbstractThe assessment of the impacts of growing genetically modified (GM) crops remains a major political and scientific challenge in Europe. Concerns have been raised by the evidence of adverse and unexpected environmental effects and differing opinions on the outcomes of environmental risk assessments (ERA). The current regulatory system is hampered by insufficiently developed methods for GM crop safety testing and introduction studies. Improvement to the regulatory system needs to address the lack of well designed GM crop monitoring frameworks, professional and financial conflicts of interest within the ERA research and testing community, weaknesses in consideration of stakeholder interests and specific regional conditions, and the lack of comprehensive assessments that address the environmental and socio-economic risk assessment interface. To address these challenges, we propose a European Network for systematic GMO impact assessment (ENSyGMO) with the aim directly to enhance ERA and post-market environmental monitoring (PMEM) of GM crops, to harmonize and ultimately secure the long-term socio-political impact of the ERA process and the PMEM in the EU. These goals would be achieved with a multi-dimensional and multi-sector approach to GM crop impact assessment, targeting the variability and complexity of the EU agro-environment and the relationship with relevant socio-economic factors. Specifically, we propose to develop and apply methodologies for both indicator and field site selection for GM crop ERA and PMEM, embedded in an EU-wide typology of agro-environments. These methodologies should be applied in a pan-European field testing network using GM crops. The design of the field experiments and the sampling methodology at these field sites should follow specific hypotheses on GM crop effects and use state-of-the art sampling, statistics and modelling approaches. To address public concerns and create confidence in the ENSyGMO results, actors with relevant specialist knowledge from various sectors should be involved.

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European environmental stratifications and typologies: An overview

Cited by 58 publications

References 34 publications

An overview of farming system typology methodologies and its use in the study of pasture-based farming system: a review

An overview of farming system typology methodologies and its use in the study of pasture-based farming system: a review

Surveillance of habitats and plant diversity indicators across a regional gradient in the Iberian Peninsula

A framework for a European network for a systematic environmental impact assessment of genetically modified organisms (GMO)

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