Models of Diabrotica Populations: Demography, Population Genetics, Geographic Spread, and Management

David W Onstad1, Michael A Caprio2, Zaiqi Pan3

  • 1Corteva Agriscience, Johnston, IA 50131, USA.

Insects
|October 21, 2020
PubMed

Related Concept Videos

What are Populations and Communities?00:30

What are Populations and Communities?

Overview
36.5K
Conservation of Declining Populations02:07

Conservation of Declining Populations

Conservation of declining population focuses on ways of detecting, diagnosing, and halting a population decline. The approach uses methods to prevent populations from going extinct.
12.3K
Conservation of Small Populations02:04

Conservation of Small Populations

Small population sizes put a species at extreme risk of extinction due to a lack of variation, and a consequent decrease in adaptability. This weakens the chances of survival under pressures such as climate change, competition from other species, or new diseases. Large populations are more likely to survive pressures such as these, as such populations are more likely to harbor individuals that have genetic variants that are adaptive under new stresses. Small populations are much less...
16.3K
What is Population Genetics?01:25

What is Population Genetics?

A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
63.6K
Life Histories01:29

Life Histories

Overview
22.2K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
169