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Determining and increasing the sensitivity of existing environmental surveillance monitoring networks to detect unanticipated effects that may occur in the environment in response to the cultivation of genetically modified crops - CB0304

Description
Environmental Surveillance Networks (ESNs) provide long term (>20 years) time series of counts at multiple sites for many taxa in the UK, and estimates of changing abundance can act as indicators for changes in biodiversity and ecosystems more broadly. Such changes have acquired significant policy-making influence.
Such counts are usually undertaken by volunteer surveyors, under the leadership of leading NGOs specialising in the various groups. Differences in available resources and species’ ecology mean that field protocols vary, but the underlying, broad design is generally consistent – a site x year ‘matrix’ of annual counts (or series of counts within each year) is obtained at a large number of sites. This consistency in design has also led to a degree of convergence in analytical techniques, namely Poisson-based Generalized Linear Models with multi-level factors representing spatial and temporal variation between the counts. The potential of such existing schemes to assess the ecological impact of changing agricultural regimes or management practices is therefore considerable.
We propose here to investigate the statistical power of some of the most frequently adopted models to detect changes over time, or the differences in such changes between sites differing in some respect, using data from ESNs. Power can depend upon many such factors/assumptions, such as the scale and duration of the survey, the abundance of the organism and magnitude of its population change (and spatial variation in these), the influence of stochastic variation in the data available and the inevitable ‘turnover’ rate of sites. We propose to develop a single, simple linear model to estimate power inherent in a commonly-used Poisson model as a function of these factors. This model can also be used to estimate the number of sites required to achieve a certain level of power – so providing guidance on how extensions of existing networks would provide additional power and, in turn, informing judgements as to the cost-effectiveness of such extensions. The outputs of this model may also be explored under a range of scenarios. (In the context of the surveillance of GM crops, this might be the degree of uptake of GM crops, spatial distribution of uptake, and type of GM crop).
We will also explore alternative approaches using data from the monitoring of long-term, national scale impacts of management changes introduced under Environmental Stewardship (BTO), and exploring within year spatial analysis (Countryside Survey & Environment Agency). Our alternative approaches will represent an illustration and potential validation (through cross-referencing with real data simulations) of the application of aspects of the generic tool and a proof-of-concept with respect to the feasibility of detection of real effect sizes.
Objective
2.2 Objectives

1) To identify policy scenarios, indicator species and a plausible range of ecological and agricultural scenarios (extent of ‘take-up’) to underlie the simulations upon which a model is to be based.
2) To perform a large number of analyses of data simulated within the range ascertained above.
3) To use the simulation results above to produce and test a simple approximation of ‘power’, in terms of the various factors by which it is determined, in the form of a linear model that can be used to estimate power in a range of circumstances without the need for additional extensive simulation work.
4) To illustrate and validate its use via examples from current ESN plant, bird, butterfly and water quality data.
5) Prepare report/manuscript with a view to publication in scientific literature.

Each objective is dependent on those preceding it, except Objective 4, for which sufficient previous analytical development has been completed that work could proceed after Objective 1 is complete, but contemporaneously with Objectives 2 and 3.
Project Documents
• FRP - Final Report : CB0304 FINAL REPORT   (1402k)
Time-Scale and Cost
From: 2012

To: 2012

Cost: £56,278
Contractor / Funded Organisations
Centre For Ecology and Hydrology (CEH)
Keywords
Genetically modified food and crops              
GM Risk Assessment              
Fields of Study
Biotechnology and GMOs