Intraspecific variation influences natural settlement of eastern oysters.

As populations decline, their intraspecific diversity also diminishes. Population decline may be exacerbated if a decrease in intraspecific diversity also reduces important ecological functions that maintain population numbers. Oyster reefs are severely overharvested, declining by ~85 % worldwide. We tested how increasing within-species diversity of eastern oysters (Crassostrea virginica) using transplants would affect recruitment of oyster larvae, a key function necessary to maintain future populations. If harvesting reduces population numbers, within-species diversity, and connectivity, then oysters may lose the ability to adapt to changing environmental conditions as well as incur lower levels of recruitment that may hasten their decline. Results from laboratory and field studies indicated that oyster larvae use chemical cues from adult oysters and not from associated fouling communities to select settlement sites. To test how increasing within-species diversity of oysters affected recruitment, we collected oysters from three distinct bay systems in Texas, USA, and compared natural settlement in treatments where all oysters were from a single bay to a mixture of all three bays. Significantly greater recruitment occurred in mixed treatments in 2010, 2011, and 2012 even though oyster recruitment varied by order of magnitude during this time. The net biodiversity effect was positive in all 3 years, indicating that increased recruitment in mixed treatments can be greater than the additive effect of the single bay treatments. Losing intraspecific diversity may reduce recruitment and lead to further declines in oyster populations, illustrating the need for understanding how intraspecific diversity influences ecological functions.

Isolation and characterization of microsatellite markers for Bothriochloa ischaemum (Poaceae).

PREMISE OF THE STUDY: Microsatellite primers were developed for Bothriochloa ischaemum to investigate the structure of invasive populations within Texas and determine the origin of introduction from within the native range. METHODS AND RESULTS: We adapted the biotinylated nucleotide method of developing an enriched genomic library to isolate and characterize 10 polymorphic microsatellite markers. The number of alleles per locus (A) ranged from five to 18 (mean A = 10.45), expected heterozygosity (H(E)) ranged from 0.620 to 0.895 (mean H(E) = 0.785), and expected heterozygosity corrected for sample size (H(EC)) ranged from 0.635 to 0.909 (mean H(EC) = 0.799). The primers were also tested for amplification in Schizachyrium scoparium var. scoparium, Andropogon gerardii, Bothriochloa saccharoides, and Dichanthium annulatum. CONCLUSIONS: The use of microsatellite markers may assist in understanding the pattern of spread, determining the source of invasive populations, and developing biological control agents for invasive populations of Bothriochloa ischaemum.

Genetic diversity across the mitochondrial genome of eastern oysters (Crassostrea virginica) in the northern Gulf of Mexico.

The eastern oyster, Crassostrea virginica, is divided into four populations along the western North Atlantic, however, the only published mitochondrial genome sequence was assembled using one individual in Delaware. This study aimed to (1) assemble C. virginica mitochondrial genomes from Texas with pooled restriction-site-associated DNA sequencing (ezRAD), (2) evaluate the validity of the mitochondrial genome assemblies including comparison with Sanger sequencing data, and (3) evaluate genetic differentiation both between the Delaware and Texas genomes, as well as among three bays in Texas. The pooled-genome-assembled-genomes (PAGs) from Texas exhibited several characteristics indicating that they were valid, including elevated nucleotide diversity in non-coding and the third position of codons, placement as the sister haplotype of the genome from Delaware in a phylogenetic reconstruction of Crassostrea mitochondrial genomes, and a lack of genetic structure in the ND4 gene among the three Texas bays as was found with Sanger amplicons in samples from the same bays several years prior. In the comparison between the Delaware and Texas genome, 27 of 38 coding regions exhibited variability between the two populations, which were differentiated by 273 mutations, versus 1-13 mutations among the Texas samples. Using the full PAGs, there was no additional evidence for population structure among the three Texas bays. While population genetics is rapidly moving towards larger high-density datasets, studies of mitochondrial DNA (and genomes) can be particularly useful for comparing historic data prior to the modern era of genomics. As such, being able to reliably compile mitochondrial genomes from genomic data can improve the ability to compare results across studies.

Detection of density dependence requires density manipulations and calculation of lambda.

To investigate density-dependent population regulation in the perennial bunchgrass Bouteloua rigidiseta, we experimentally manipulated density by removing adults or adding seeds to replicate quadrats in a natural population for three annual intervals. We monitored the adjacent control quadrats for 14 annual intervals. We constructed a population projection matrix for each quadrat in each interval, calculated lambda, and did a life table response experiment (LTRE) analysis. We tested the effects of density upon lambda by comparing experimental and control quadrats, and by an analysis of the 15-year observational data set. As measured by effects on lambda and on N(t+1/Nt in the experimental treatments, negative density dependence was strong: the population was being effectively regulated. The relative contributions of different matrix elements to treatment effect on lambda differed among years and treatments; overall the pattern was one of small contributions by many different life cycle stages. In contrast, density dependence could not be detected using only the observational (control quadrats) data, even though this data set covered a much longer time span. Nor did experimental effects on separate matrix elements reach statistical significance. These results suggest that ecologists may fail to detect density dependence when it is present if they have only descriptive, not experimental, data, do not have data for the entire life cycle, or analyze life cycle components separately.