Geology topics

B.A. Wintle

Publications and source records attributed to B.A. Wintle.

2 recordsLinked to original sources

USGS2010

Allocating monitoring effort in the face of unknown unknowns

There is a growing view that to make efficient use of resources, ecological monitoring should be hypothesis-driven and targeted to address specific management questions. 'Targeted' monitoring has been contrasted with other approaches in which a range of quantities are monitored in case they exhibit an alarming trend or provide ad hoc ecological insights. The second form of monitoring, described as surveillance, has been criticized because it does not usually aim to discern between competing hypotheses, and its benefits are harder to identify a priori. The alternative view is that the existence of surveillance data may enable rapid corroboration of emerging hypotheses or help to detect important 'unknown unknowns' that, if undetected, could lead to catastrophic outcomes or missed opportunities. We derive a model to evaluate and compare the efficiency of investments in surveillance and targeted monitoring. We find that a decision to invest in surveillance monitoring may be defensible if: (1) the surveillance design is more likely to discover or corroborate previously unknown phenomena than a targeted design and (2) the expected benefits (or avoided costs) arising from discovery are substantially higher than those arising from a well-planned targeted design. Our examination highlights the importance of being explicit about the objectives, costs and expected benefits of monitoring in a decision analytic framework. ?? 2010 Blackwell Publishing Ltd/CNRS.

Ecology Letters↗

USGS2006

Planning for robust reserve networks using uncertainty analysis

Planning land-use for biodiversity conservation frequently involves computer-assisted reserve selection algorithms. Typically such algorithms operate on matrices of species presence?absence in sites, or on species-specific distributions of model predicted probabilities of occurrence in grid cells. There are practically always errors in input data?erroneous species presence?absence data, structural and parametric uncertainty in predictive habitat models, and lack of correspondence between temporal presence and long-run persistence. Despite these uncertainties, typical reserve selection methods proceed as if there is no uncertainty in the data or models. Having two conservation options of apparently equal biological value, one would prefer the option whose value is relatively insensitive to errors in planning inputs. In this work we show how uncertainty analysis for reserve planning can be implemented within a framework of information-gap decision theory, generating reserve designs that are robust to uncertainty. Consideration of uncertainty involves modifications to the typical objective functions used in reserve selection. Search for robust-optimal reserve structures can still be implemented via typical reserve selection optimization techniques, including stepwise heuristics, integer-programming and stochastic global search.

Ecological Modelling↗