PubMed · 11628647
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J P Bardet, K A Lynch, G P Mineau, M Hainsworth, M Skolnick. 1981. [Not Available].. https://pubmed.ncbi.nlm.nih.gov/11628647/
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Spatial autocorrelation (SA) methods were recently extended to detect local spatial autocorrelation (LSA) at individual localities. LSA statistics serve as useful indicators of local genetic population structure. We applied this method to 15 allele frequencies from 43 villages of a South American tribe, the Yanomama. Based on a network of links <or=51 km between neighboring villages, we calculated LSA statistics for Moran, Geary, and Getis-Ord coefficients. We also developed two new, rescaled indices of local SA. Local indicators of positive SA highlight villages surrounded by genetically similar near neighbors. Negative LSA statistics indicate sharp genetic differences from near neighbors. Markedly positive LSA was found for all 11 outlier villages. The most negatively LSA villages are in the central, densely connected cluster. The Getis-Ord coefficients of suitably transformed allele frequencies point to clusters of villages with unusually high or low allelic polymorphisms. The most homozygous villages are all in the four geographically isolated village clusters. The most polymorphic villages are all in the large, densely settled Yanomame dialect group. An ad hoc linguistic isolation index between neighboring villages showed that villages in isolated pairs and triplets have linguistically similar neighbors, whereas nine villages with notably negative LSA are all near dialect and kinship boundaries. The location of a village with respect to the graph structure of its neighborhood affects its LSA and genetic polymorphism. The implications of these findings for the population structure of the Yanomama are compatible with those from an earlier study of global SA in these villages.
Pesticides are widely used in the home and garden to kill insects, weeds and other unwanted pests. There is mounting evidence that this usage may also have health consequences particularly on children. Using the ALSPAC cohort of 13,391 families with self-reported usage data up to age 4 years of the study child, the main users of pesticides appeared to be older, Caucasian, better educated, have higher incomes and more likely to own their home or to belong to non-manual social classes compared to less frequent users. There was some suggestion that different factors may affect weed-killer compared to other pesticide use. In particular, income appeared unrelated to other pesticide use. This may reflect different attitudes to indoor compared to garden applications. Alternatively, it may reflect whether the main user was the mother or the partner. Some authorities are currently encouraging domestic users to consider other non-chemical means of pest control before using pesticides. These results may help in targeting particular groups if further reductions in pesticide usage are desired. They have also helped in identifying the important confounders for adjusting future analyses on the potential health consequences of pesticides and weed-killers.
A growing body of literature points to a large-scale research approach as essential for understanding population and community ecology. Many of our advances regarding the spatial ecology of predators and prey can be attributed to research with insect parasitoids and their hosts. In this review, we focus on the progress that has been made in the study of the movement and population dynamics of hosts and their parasitoids in heterogeneous landscapes, and how this research approach may be beneficial to pest management programs. To date, few studies have quantified prey and predator rates and ranges of dispersal and population dynamics at the patch level--the minimum of information needed to characterize population structure. From host-parasitoid studies with sufficient data, it is clear that the spatial scale of dispersal can differ significantly between a prey and its predators, local prey extinctions can be attributed to predators and predator extinction risk at the patch level often exceeds that of the prey. It is also evident that populations can be organized as a single, highly connected (patchy) population or as semi-independent extinction-prone local populations that collectively form a persistent metapopulation. A prey and its predators can also differ in population structure. At the landscape level, agricultural studies indicate that predator effects on its prey often spill over between the crop and surrounding area (matrix) and can depend strongly on landscape structure (e.g. the proportion of suitable habitat) at scales extending well beyond the crop margins. In light of existing empirical data, predator-prey models are typically spatially unrealistic, lacking important details on boundary responses and movement behaviour within and among patches. The tools exist for conducting empirical and theoretical research at the landscape level and we hope that this review calls attention to fertile areas for future exploration.