Measuring the effectiveness of management interventions at regional scales by integrating ecological monitoring and modelling

A - Papers appearing in refereed journals

Freckleton, R. P., Hicks, H. L., Comont, D., Crook, L., Hull, R. I., Neve, P. and Childs, D. Z. 2018. Measuring the effectiveness of management interventions at regional scales by integrating ecological monitoring and modelling. Pest Management Science. 74 (10), pp. 2287-2295.

AuthorsFreckleton, R. P., Hicks, H. L., Comont, D., Crook, L., Hull, R. I., Neve, P. and Childs, D. Z.
Abstract

BACKGROUND: Because of site-specific effects and outcomes, it is often difficult to know whether a management strategy for the control of pests has worked or not. Population dynamics of pests are typically spatially and temporally variable. Moreover, interventions at the scale of individual fields or farms are essentially unreplicated experiments; a decrease in a target population following management cannot safely be interpreted as success because, for example, it might simply be a poor year for that species. Here, we argue that if large-scale data are available, population models can be used to measure outcomes against the prevailing mean and variance. We apply this approach to the problem of rotational management of the weed Alopecurus myosuroides. RESULTS: We derived density-structured population models for a set of fields that were not subject to rotational management (continuous winter wheat) and another group that were (rotated into spring barley to control A. myosuroides). We used these models to construct means and variances of the outcomes of management for given starting conditions, and to conduct transient growth analysis. We show that, overall, this management strategy is successful in reducing densities of weeds, albeit with considerable variance. However, we also show that one variant (rotation to spring barley along with variable sowing) shows little evidence for additional control. CONCLUSION: Our results suggest that rotational strategies can be effective in the control of this weed, but also that strategies require careful evaluation against a background of spatiotemporal variation.

Keywordsdensity‐structured model; vector generalized additive model; integrated weed management; population model; weed ecology
Year of Publication2018
JournalPest Management Science
Journal citation74 (10), pp. 2287-2295
Digital Object Identifier (DOI)doi:10.1002/ps.4759
Open accessPublished as ‘gold’ (paid) open access
Funder project or codeMultiple Herbicide Resistance in Grass Weeds: from Genes to AgroEcosystems
FunderBiotechnology and Biological Sciences Research Council
Agriculture and Horticulture Development Board
Publisher's version
Output statusPublished
Publication dates
Online10 Oct 2017
Publication process dates
Accepted04 Oct 2017
PublisherJohn Wiley & Sons, Ltd
Wiley
Copyright licenseCC BY
Grant IDBB/L001489/1
ISSN1526-498X

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