A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets

Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Raw data for "Linkage disequilibrium estimation of effective population size with immigrants from divergent populations: a case study on Spanish mackerel (Scomberomorus commerson)."

Abstract of Macbeth, G. M., Broderick, D., Buckworth, R. & Ovenden, J. R. (In press, Feb 2013). Linkage disequilibrium estimation of effective population size with immigrants from divergent populations: a case study on Spanish mackerel (Scomberomorus commerson). G3: Genes, Genomes and Genetics. Estimates of genetic effective population size (Ne) using molecular markers are a potentially useful tool for the management of endangered through to commercial species. But, pitfalls are predicted when the effective size is large, as estimates require large numbers of samples from wild populations for statistical validity. Our simulations showed that linkage disequilibrium estimates of Ne up to 10,000 with finite confidence limits can be achieved with sample sizes around 5000. This was deduced from empirical allele frequencies of seven polymorphic microsatellite loci in a commercially harvested fisheries species, the narrow barred Spanish mackerel (Scomberomorus commerson). As expected, the smallest standard deviation of Ne estimates occurred when low frequency alleles were excluded. Additional simulations indicated that the linkage disequilibrium method was sensitive to small numbers of genotypes from cryptic species or conspecific immigrants. A correspondence analysis algorithm was developed to detect and remove outlier genotypes that could possibly be inadvertently sampled from cryptic species or non-breeding immigrants from genetically separate populations. Simulations demonstrated the value of this approach in Spanish mackerel data. When putative immigrants were removed from the empirical data, 95% of the Ne estimates from jacknife resampling were above 24,000.

Production attributes of Merino sheep genetically divergent for wool growth are reflected in differing rumen microbiotas

Divergent genetic selection for wool growth as a single trait has led to major changes in sheep physiology and metabolism, including variations in rumen microbial protein production and uptake of α-amino nitrogen in portal blood. This study was conducted to determine if sheep with different genetic merit for wool growth exhibit distinct rumen bacterial diversity. Eighteen Merino wethers were separated into groups of contrasting genetic merit for clean fleece weight (CFW; low: WG− and high: WG+) and fed a blend of oaten and lucerne chaff diet at two levels of intake (LOI; 1 or 1.5 times maintenance energy requirements) for two seven-week periods in a crossover design. Bacterial diversity in rumen fluid collected by esophageal intubation was characterized using 454 amplicon pyrosequencing of the V3/V4 regions of the 16S rRNA gene. Bacterial diversity estimated by Phylogenetic distance, Chao1 and observed species did not differ significantly with CFW or LOI; however, the Shannon diversity index differed (P=0.04) between WG+ (7.67) and WG− sheep (8.02). WG+ animals had a higher (P=0.03) proportion of Bacteroidetes (71.9% vs 66.5%) and a lower (P=0.04) proportion of Firmicutes (26.6% vs 31.6%) than WG− animals. Twenty-four specific operational taxonomic units (OTUs), belonging to the Firmicutes and Bacteroidetes phyla, were shared among all the samples, whereas specific OTUs varied significantly in presence/abundance (P<0.05) between wool genotypes and 50 varied (P<0.05) with LOI. It appears that genetic selection for fleece weight is associated with differences in rumen bacterial diversity that persist across different feeding levels. Moderate correlations between seven continuous traits, such as methane production or microbial protein production, and the presence and abundance of 17 OTUs were found, indicating scope for targeted modification of the microbiome to improve the energetic efficiency of rumen microbial synthesis and reduce the greenhouse gas footprint of ruminants.

Random Mating Between Two Widely Divergent Mitochondrial Lineages of Cryptolestes ferrugineus (Coleoptera: Laemophloeidae): A Test of Species Limits in a Phosphine-Resistant Stored Product Pest

Effective pest management relies on accurate delimitation of species and, beyond this, on accurate species identification. Mitochondrial COI sequences are useful for providing initial indications in delimiting species but, despite acknowledged limitations in the method, many studies involving COI sequences and species problems remain unresolved. Here we illustrate how such impasses can be resolved with microsatellite and nuclear sequence data, to assess more directly the amount of gene flow between divergent lineages. We use a population genetics approach to test for random mating between two 8 ± 2% divergent COI lineages of the rusty grain beetle, Cryptolestes ferrugineus (Stephens). This species has become strongly resistant to phosphine, a fumigant used worldwide for disinfesting grain. The possibility of cryptic species would have significant consequences for resistance management, especially if resistance was confined to one mitochondrial lineage. We find no evidence of restricted gene flow or nonrandom mating across the two COI lineages of these beetles, rather we hypothesize that historic population structure associated with early Pleistocene climate changes likely contributed to divergent lineages within this species.