Effects of meteorological variation on mortality in populations of the spittlebug Deois flavopicta (Homoptera : Cercopidae)

We found that variation in temperature and humidity significantly affected mortality rates and population dynamics of the spittlebug Deois flavopicta Stal by monitoring cohorts of diapausing eggs and nymphs for three generations. Cohorts of quiescent eggs, when exposed to increasing periods of high moisture (free water), produced higher proportions of eggs resuming embryonic development in laboratory experiments. The accumulated number of eggs resuming development as a function of (lays of exposure to moist conditions was modeled using a 0 distribution. Periods of drought and high temperatures after the beginning of postdiapause development increased embryonic and nymphal mortality. Mortality was modeled with a linear function, and in combination with the development model allowed the simulation of varying mortality rates in the newly emerged nymphal population. Comparisons with field data demonstrated a close fit to the observed and expected proportion of nymphs hatching daily. By accurately simulating natural mortality, hatching distribution and population dynamics, the model promises to be useful for managing the spittlebug in the field.31229930

An ecologically-based method for selecting ecological indicators for assessing risks to biological diversity from genetically-engineered plants

The environmental risks associated with genetically-engineered (GE) organisms have been controversial, and so have the models for the assessment of these risks. We propose an ecologically-based environmental risk assessment (ERA) model that follows the 1998 USEPA guidelines, focusing on potential adverse effects to biological diversity. The approach starts by (1) identifying the local environmental values so the ERA addresses specific concerns associated with local biological diversity. The model simplifies the indicator endpoint selection problem by (2) classifying biological diversity into ecological functional groups and selecting those that deliver the identified environmental values. (3) All of the species or ecosystem processes related to the selected functional groups are identified and (4) multi-criteria decision analysis (MCDA) is used to rank the indicator endpoint entities, which may be species or ecological processes. MCDA focuses on those species and processes that are critical for the identified ecological functions and are likely to be highly exposed to the GE organism. The highest ranked indicator entities are selected for the next step. (5) Relevant risk hypotheses are identified. Knowledge about the specific transgene and its possible environmental effects in other countries can be used to assist development of risk hypotheses. (6) The risk hypotheses are ranked using MCDA with criteria related to the severity of the potential risk. The model emphasizes transparent, expert-driven, ecologically-based decision-making and provides formal methods for completing a screening level-ERA that can focus ERA on the most significant concerns. The process requires substantial human input but the human capital is available in most countries and regions of the world

Non-target and biological diversity risk assessment

This chapter discusses the following procedures for risk assessment in Bt cotton using the non-target risk assessment model developed by scientists of the GMO ERA Project ("International Project on GMO Environmental Risk Assessment Methodologies", which is a continuation of the GMO Guidelines Project, which was launched by scientists of the International Organization for Biological Control Global Working Group on "Transgenic Organisms in Integrated Pest Management and Biological Control"): (1) identify relevant functional groups of biological diversity associated with adverse effects, (2) list and prioritize species or ecological processes, (3) identify potential exposure pathways and adverse effects pathways, and use these to formulate and prioritize risk hypotheses, and (4) develop an analysis plan and suggest designs for experiments to test risk hypothese