Showing papers by "Kevin Gross published in 2011"

Plant diversity and the stability of foodwebs.

Abstract: Insect outbreaks in forest and agriculture monocultures led Charles Elton to propose, a half-century ago, that higher plant diversity stabilized animal foodweb dynamics in natural ecosystems. We tested this hypothesis by studying arthropod community dynamics in a long-term experimental manipulation of grassland plant species diversity. Over the course of a decade, we found that higher plant diversity increased the stability (i.e. lowered year-to-year variability) of a diverse (>700 species) arthropod community across trophic levels. As the number of plant species increased, the stability of both herbivore and predator species richness and of total herbivore abundance increased. The underlying mechanisms driving these diversity-stability relationships were plant diversity, via effects on primary productivity and plant community stability, and portfolio effects. Taken together, our results show that higher plant diversity provides more temporally consistent food and habitat resources to arthropod foodwebs. Consequently, actively managing for high plant diversity may have stronger than expected benefits for increasing animal diversity and controlling pest outbreaks.

Quantifying secondary pest outbreaks in cotton and their monetary cost with causal‐inference statistics

Abstract: Secondary pest outbreaks occur when the use of a pesticide to reduce densities of an unwanted target pest species triggers subsequent outbreaks of other pest species. Although secondary pest outbreaks are thought to be familiar in agriculture, their rigorous documentation is made difficult by the challenges of performing randomized experiments at suitable scales. Here, we quantify the frequency and monetary cost of secondary pest outbreaks elicited by early-season applications of broad-spectrum insecticides to control the plant bug Lygus spp. (primarily L. hesperus) in cotton grown in the San Joaquin Valley, California, USA. We do so by analyzing pest-control management practices for 969 cotton fields spanning nine years and 11 private ranches. Our analysis uses statistical methods to draw formal causal inferences from nonexperimental data that have become popular in public health and economics, but that are not yet widely known in ecology or agriculture. We find that, in fields that received an early-season broad-spectrum insecticide treatment for Lygus, 20.2% +/- 4.4% (mean +/- SE) of late-season pesticide costs were attributable to secondary pest outbreaks elicited by the early-season insecticide application for Lygus. In 2010 U.S. dollars, this equates to an additional $6.00 +/- $1.30 (mean +/- SE) per acre in management costs. To the extent that secondary pest outbreaks may be driven by eliminating pests' natural enemies, these figures place a lower bound on the monetary value of ecosystem services provided by native communities of arthropod predators and parasitoids in this agricultural system.

Ecoinformatics for Integrated Pest Management: Expanding the Applied Insect Ecologist's Tool-Kit

Abstract: Experimentation has been the cornerstone of much of integrated pest management (IPM) research. Here, we aim to open a discussion on the possible merits of expanding the use of observational studies, and in particular the use of data from farmers or private pest management consultants in “ecoinformatics” studies, as tools that might complement traditional, experimental research. The manifold advantages of experimentation are widely appreciated: experiments provide definitive inferences regarding causal relationships between key variables, can produce uniform and high-quality data sets, and are highly flexible in the treatments that can be evaluated. Perhaps less widely considered, however, are the possible disadvantages of experimental research. Using the yield-impact study to focus the discussion, we address some reasons why observational or ecoinformatics approaches might be attractive as complements to experimentation. A survey of the literature suggests that many contemporary yield-impact studies lack sufficient statistical power to resolve the small, but economically important, effects on crop yield that shape pest management decision-making by farmers. Ecoinformatics-based data sets can be substantially larger than experimental data sets and therefore hold out the promise of enhanced power. Ecoinformatics approaches also address problems at the spatial and temporal scales at which farming is conducted, can achieve higher levels of “external validity,” and can allow researchers to efficiently screen many variables during the initial, exploratory phases of research projects. Experimental, observational, and ecoinformatics-based approaches may, if used together, provide more efficient solutions to problems in pest management than can any single approach, used in isolation.