Environmental stratifications as the basis for national, European and global ecological monitoring

Metzger, M.J.; Brus, D.J.; Bunce, R. G. H.; Carey, Peter; Gonçalves, João; Honrado, João P.; Jongman, R.H.G.; Trabucco, Antonio; Zomer, Robert J.

doi:10.1016/j.ecolind.2012.11.009

Cited by 71 publications

(75 citation statements)

References 52 publications

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“…This successful method of the consistent classification of land into relatively homogenous strata has been proven to provide a valuable spatial framework as the basis for monitoring ecological indicators across large areas. There are now several examples of where the British methods have been emulated effectively, including Northern Ireland (Cooper, 2000), Spain (Elena-Rosselló, 1997), Norway (Bakkestuen et al, 2008), Sweden (Ståhl et al, 2011), Estonia (Villoslada et al, 2016) and Europe (and the whole world) (Metzger et al, 2013).…”

Section: Survey Design: Site Selection and Stratificationmentioning

confidence: 99%

Ecological landscape elements: long-term monitoring in Great Britain, the Countryside Survey 1978–2007 and beyond

Wood

Bunce

Norton

et al. 2018

Earth Syst. Sci. Data

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Abstract. The Countryside Survey (CS) of Great Britain (GB) provides a unique and statistically robust series of datasets, consisting of an extensive set of repeated ecological measurements at a national scale, covering a time span of 29 years. CS was first undertaken in 1978 to provide a baseline for ecological and land use change monitoring in the rural environment of GB, following a stratified random design, based on 1 km squares. Originally, eight random 1 km squares were drawn from each of 32 environmental classes, thus comprising 256 sample squares in the 1978 survey. The number of these sites increased to 382 in 1984, 506 in 1990, 569 in 1998 and 591 in 2007. Detailed information regarding vegetation types and land use was mapped in all five surveys, allowing reporting by defined standard habitat classifications. Additionally, point and linear landscape features (such as trees and hedgerows) are available from all surveys after 1978. From these stratified, randomly located sample squares, information can be converted into national estimates, with associated error terms.Other data, relating to soils, freshwater and vegetation, were also sampled on analogous dates. However, the present paper describes only the surveys of landscape features and habitats. The resulting datasets provide a unique, comprehensive, quantitative ecological coverage of extent and change in these features in GB. Basic results are presented and their implications discussed. However, much opportunity for further analyses remains.Data from each of the survey years are available via the following DOIs: Landscape area data 1978: https://doi.org/10.5285/86c017ba-dc62-46f0-ad13-c862bf31740e, 1984: https://doi.org/10.5285/b656bb43-448d-4b2c-aade-7993aa243ea3, 1990: https://doi.org/10.5285/94f664e5-10f2-4655-bfe6-44d745f5dca7, 1998: https://doi.org/10.5285/1e050028-5c55-42f4-a0ea-c895d827b824, and 2007: https://doi.org/10.5285/bf189c57-61eb-4339-a7b3-d2e81fdde28d; Landscape linear feature data 1984: https://doi.org/10.5285/a3f5665c-94b2-4c46-909e-a98be97857e5, 1990: https://doi.org/10.5285/311daad4-bc8c-485a-bc8a-e0d054889219, 1998: https://doi.org/10.5285/8aaf6f8c-c245-46bb-8a2a-f0db012b2643 and 2007: https://doi.org/10.5285/e1d31245-4c0a-4dee-b36c-b23f1a697f88, Landscape point feature data 1984: https://doi.org/10.5285/124b872e-036e-4dd3-8316-476b5f42c16e, 1990: https://doi.org/10.5285/1481bc63-80d7-4d18-bcba-8804aa0a9e1b, 1998: https://doi.org/10.5285/ed10944f-40c8-4913-b3f5-13c8e844e153 and 2007: https://doi.org/10.5285/55dc5fd7-d3f7-4440-b8a7-7187f8b0550b.

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Section: Survey Design: Site Selection and Stratificationmentioning

confidence: 99%

Ecological landscape elements: long-term monitoring in Great Britain, the Countryside Survey 1978–2007 and beyond

Wood

Bunce

Norton

et al. 2018

Earth Syst. Sci. Data

View full text Add to dashboard Cite

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“…Similarly, inventory data on development activities such as power generation, infrastructure, and water withdrawals could improve consistency in life-cycle assessments and other strategic business-risk evaluations (65,74). Several global efforts are working to increase the accessibility of environmental-change information, often based on cutting-edge satellite and remotely sensed data (75,76). If these environmental intelligence platforms succeed, they could lower the cost of acquiring environmental data throughout the supply chain and make individualized and spatially explicit sustainability reporting routine.…”

Section: Avenues For Ecosystem Science To Engage With Corporate Envirmentioning

confidence: 99%

Improving global environmental management with standard corporate reporting

Kareiva

McNally

McCormick

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Multinational corporations play a prominent role in shaping the environmental trajectory of the planet. The integration of environmental costs and benefits into corporate decision-making has enormous, but as yet unfulfilled, potential to promote sustainable development. To help steer business decisions toward better environmental outcomes, corporate reporting frameworks need to develop scientifically informed standards that consistently consider land use and land conversion, clean air (including greenhouse gas emissions), availability and quality of freshwater, degradation of coastal and marine habitats, and sustainable use of renewable resources such as soil, timber, and fisheries. Standardization by itself will not be enough-also required are advances in ecosystem modeling and in our understanding of critical ecological thresholds. With improving ecosystem science, the opportunity for realizing a major breakthrough in reporting corporate environmental impacts and dependencies has never been greater. Now is the time for ecologists to take advantage of an explosion of sustainability commitments from business leaders and expanding pressure for sustainable practices from shareholders, financial institutions, and consumers.corporate sustainability | ESG reporting | natural capital | ecosystem services | multinational corporations

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“…In ecological monitoring, the Countryside Survey in Great Britain has used stratification by environmental factors to capture the land's heterogeneity, and stratification has been proposed as a framework for national, European, and global ecological monitoring (Metzger et al, 2012). Stratification has also been proposed in sampling of Salmonella isolates for monitoring of microbial resistance (EFSA, 2014)…”

Section: Stratified Samplingmentioning

confidence: 99%

Data Representativeness: Issues and Solutions

Milanzi

Njagi

Bruckers

et al. 2015

EFSA Supporting Publications

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In its control programmes on maximum residue level compliance and exposure assessments, EFSA requires the participating countries to submit results, from specific numbers of food item samples, analyzed in the countries. These data are used to obtain estimates such as the proportion of samples exceeding the maximum residue limits, and the mean and maximum residue concentration per food item to assess exposure. An important consideration is the design and analysis of the programmes. In this report, we combine elements of survey sampling methodology, and statistical modeling, as a benchmark framework for the programmes, starting from the translation of research questions into statistical problems, to the statistical analysis and interpretation. Particular focus is placed on the issues that could affect the representativeness of the data, and remedial procedures are proposed. For example, in the absence of information on the sampling design, a sensitivity analysis, across a range of designs, is proposed. On the other hand, weighted generalized linear mixed models, and generalized linear mixed models combining both conjugate and normal random effects, are proposed, to address selection bias. Likelihood-based analysis methods are also proposed to address missing and censored data problems. Suggestions for improvements in the design and analysis of the programmes are also identified and discussed. For instance, incorporation of stratified sampling methodology, in determining both the total number, and the allocation of samples to the participating countries, is proposed. All through the report, statistical analysis models which properly take into account the hierarchical (and thus correlated) structure in which the data are collected are proposed.

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Environmental stratifications as the basis for national, European and global ecological monitoring

Cited by 71 publications

References 52 publications

Ecological landscape elements: long-term monitoring in Great Britain, the Countryside Survey 1978–2007 and beyond

Ecological landscape elements: long-term monitoring in Great Britain, the Countryside Survey 1978–2007 and beyond

Improving global environmental management with standard corporate reporting

Data Representativeness: Issues and Solutions

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