Assessing bias in aerial surveys for cetaceans: Results from experiments conducted with the franciscana dolphin

Line transect aerial surveys are widely used for estimating abundance of biological populations, including threatened species. However, estimates obtained with data collected from aircraft are often underestimated because of visibility bias and bias in estimating group sizes from a fast-moving platform. An assessment of multiple sources of bias in aerial surveys were carried out in Brazilian coastal waters by experiments on multiple survey platforms (i.e., boat, airplane and helicopter). These studies focused on evaluating visibility bias (perception and availability bias) and potential differences in the estimation of group sizes from different types of platforms used in franciscana (Pontoporia blainvillei) abundance surveys. The ultimate goal was to develop correction factors to improve accuracy of estimates of density and population size for this threatened dolphin. Estimates of density and group sizes computed from boats were assumed to be unbiased and were compared to estimates of these quantities obtained from an airplane in the same area and period. In addition, helicopter surveys were conducted in two areas where water turbidity differed (clear vs. murky waters) to determine surfacing-diving intervals of franciscana groups and to estimate availability for aerial platforms. Abundance computed from the aerial survey data underestimated the true abundance by about 4-5 times, with ~70% of the total bias resulting from visibility bias (~80% from availability bias and ~20% from perception bias) and ~30% from bias in estimates of group size. The use of multiple survey platforms in contrasting habitats provided the opportunity to compute correction factors that can be used to refine range wide abundance estimates of the threatened franciscana given certain assumptions are met. Visibility bias and group size bias were substantial and clearly indicate the importance for accounting for such correction factors to produce unequivocal population assessment based on aerial survey data.Fil: Sucunza, Federico. Grupo de Estudio de Mamiferos Aquaticos de Rio Grande Do Sul.; Brasil. Universidade Federal de Juiz de Fora; Brasil. Instituto Aqualie; BrasilFil: Danilewicz, Daniel. Instituto Aqualie; Brasil. Grupo de Estudio de Mamiferos Aquaticos de Rio Grande Do Sul.; Brasil. Universidade Federal de Juiz de Fora; BrasilFil: Andriolo, Artur. Instituto Aqualie; Brasil. Universidade Federal de Juiz de Fora; BrasilFil: de Castro, Franciele R.. Instituto Aqualie; BrasilFil: Cremer, Marta. Universidade da Região de Joinville; BrasilFil: Denuncio, Pablo Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Ferreira, Emanuel. Associação R3 Animal; BrasilFil: Flores, Paulo A. C.. Instituto Chico Mendes para a Conservação da Biodiversidade; BrasilFil: Ott, Paulo H.. Universidade Estadual do Rio Grande do Sul; Brasil. Grupo de Estudio de Mamiferos Aquaticos de Rio Grande Do Sul.; BrasilFil: Perez, Martin S.. Grupo de Estudio de Mamiferos Aquaticos de Rio Grande Do Sul.; BrasilFil: Pretto, Dan. Instituto Chico Mendes Para A Conservação Da Biodiversidade; BrasilFil: Sartori, Camila M.. Universidade da Região de Joinville; BrasilFil: Secchi, Eduardo Resende. Universidade Federal do Rio Grande; BrasilFil: Zerbini, Alexandre. Marine Ecology And Telemetry Research; Estados Unidos. Cascadia Research Collective; Estados Unidos. Instituto Aqualie; Brasil. Universidade Federal de Juiz de Fora; Brasil. The George Washington University; Estados Unido

Genetic diversity and connectivity of southern right whales (Eubalaena australis) found in the Brazil and Chile-Peru wintering grounds and the South Georgia (Islas Georgias del Sur) feeding ground

As species recover from exploitation, continued assessments of connectivity and population structure are warranted to provide information for conservation and management. This is particularly true in species with high dispersal capacity, such as migratory whales, where patterns of connectivity could change rapidly. Here we build on a previous long-term, large-scale collaboration on southern right whales (Eubalaena australis) to combine new (nnew) and published (npub) mitochondrial (mtDNA) and microsatellite genetic data from all major wintering grounds and, uniquely, the South Georgia (Islas Georgias del Sur: SG) feeding grounds. Specifically, we include data from Argentina (npub mtDNA/microsatellite=208/46), Brazil (nnew mtDNA/microsatellite=50/50), South Africa (nnew mtDNA/microsatellite=66/77, npub mtDNA/microsatellite=350/47), Chile-Peru (nnew mtDNA/microsatellite=1/1), the Indo-Pacific (npub mtDNA/microsatellite=769/126), and SG (npub mtDNA/microsatellite=8/0, nnew mtDNA/microsatellite=3/11) to investigate the position of previously unstudied habitats in the migratory network: Brazil, SG and Chile-Peru. These new genetic data show connectivity between Brazil and Argentina, exemplified by weak genetic differentiation and the movement of one genetically identified individual between the South American grounds. The single sample from Chile-Peru had a mtDNA haplotype previously only observed in the Indo-Pacific and had a nuclear genotype that appeared admixed between the Indo-Pacific and South Atlantic, based on genetic clustering and assignment algorithms. The SG samples were clearly South Atlantic, and were more similar to the South American than the South African wintering grounds. This study highlights how international collaborations are critical to provide context for emerging or recovering regions, like the SG feeding ground, as well as those that remain critically endangered, such as Chile-Peru

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder