Literature review of elasmobranch bycatch and retention rate

To address growing concern over the effects of fisheries non-target catch on elasmobranchs worldwide, the accurate reporting of elasmobranch catch is essential. This requires data on a combination of measures, including reported landings, retained and discarded non-target catch, and post-discard survival. Identification of the factors influencing discard vs. retention is needed to improve catch estimates and to determine wasteful fishing practices. To do this we compared retention rates of elasmobranch non-target catch in a broad subset of fisheries throughout the world by taxon, fishing country, and gear. A regression tree and random forest analysis indicated that taxon was the most important determinant of retention in this dataset, but all three factors together explained 59% of the variance. Estimates of total elasmobranch removals were calculated by dividing the FAO global elasmobranch landings by average retention rates and suggest that total elasmobranch removals may exceed FAO reported landings by as much as 400%. This analysis is the first effort to directly characterize global drivers of discards for elasmobranch non-target catch. Our results highlight the importance of accurate quantification of retention and discard rates to improve assessments of the potential impacts of fisheries on these species.

Detection histories for eight species of Amazona parrots in Venezuela during the NeoMaps bird surveys in 2010

Documenting changes in distribution is necessary for understanding species' response to environmental changes, but data on species distributions are heterogeneous in accuracy and resolution. Combining different data sources and methodological approaches can fill gaps in knowledge about the dynamic processes driving changes in species-rich, but data-poor regions. We combined recent bird survey data from the Neotropical Biodiversity Mapping Initiative (NeoMaps) with historical distribution records to estimate potential changes in the distribution of eight species of Amazon parrots in Venezuela. Using environmental covariates and presence-only data from museum collections and the literature, we first used maximum likelihood to fit a species distribution model (SDM) estimating a historical maximum probability of occurrence for each species. We then used recent, NeoMaps survey data to build single-season occupancy models (OM) with the same environmental covariates, as well as with time- and effort-dependent detectability, resulting in estimates of the current probability of occurrence. We finally calculated the disagreement between predictions as a matrix of probability of change in the state of occurrence. Our results suggested negative changes for the only restricted, threatened species, Amazona barbadensis, which has been independently confirmed with field studies. Two of the three remaining widespread species that were detected, Amazona amazonica, Amazona ochrocephala, also had a high probability of negative changes in northern Venezuela, but results were not conclusive for Amazona farinosa. The four remaining species were undetected in recent field surveys; three of these were most probably absent from the survey locations (Amazona autumnalis, Amazona mercenaria and Amazona festiva), while a fourth (Amazona dufresniana) requires more intensive targeted sampling to estimate its current status. Our approach is unique in taking full advantage of available, but limited data, and in detecting a high probability of change even for rare and patchily-distributed species. However, it is presently limited to species meeting the strong assumptions required for maximum-likelihood estimation with presence-only data, including very high detectability and representative sampling of its historical distribution.

Sampling sites, sampled birds and plants of young larch plantations in Tokachi district, eastern Hokkaido, northern Japan, 2011

Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

EPOCA/EUR-OCEANS data compilation on the effects of ocean acidification, 2011

The uptake of anthropogenic CO2 by the oceans has led to a rise in the oceanic partial pressure of CO2, and to a decrease in pH and carbonate ion concentration. This modification of the marine carbonate system is referred to as ocean acidification. Numerous papers report the effects of ocean acidification on marine organisms and communities but few have provided details concerning full carbonate chemistry and complementary observations. Additionally, carbonate system variables are often reported in different units, calculated using different sets of dissociation constants and on different pH scales. Hence the direct comparison of experimental results has been problematic and often misleading. The need was identified to (1) gather data on carbonate chemistry, biological and biogeochemical properties, and other ancillary data from published experimental data, (2) transform the information into common framework, and (3) make data freely available. The present paper is the outcome of an effort to integrate ocean carbonate chemistry data from the literature which has been supported by the European Network of Excellence for Ocean Ecosystems Analysis (EUR-OCEANS) and the European Project on Ocean Acidification (EPOCA). A total of 185 papers were identified, 100 contained enough information to readily compute carbonate chemistry variables, and 81 data sets were archived at PANGAEA - The Publishing Network for Geoscientific & Environmental Data. This data compilation is regularly updated as an ongoing mission of EPOCA.

Properties of seawater and particulate matter from a WETLabs AC-S spectrophotometer and a WETLabs chlorophyll fluorometer mounted on the continuous surface water sampling system during the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) was a global survey of ocean ecosystems aboard the Sailing Vessel Tara. It carried out extensive measurements of evironmental conditions and collected plankton (viruses, bacteria, protists and metazoans) for later analysis using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data publication provides permanent links to original and updated versions of validated data files containing measurements from the Continuous Surface Sampling System [CSSS]. Water was pumped at the front of the vessel from ~2m depth, then de-bubbled and circulated to a WETLabs AC-S spectrophotometer and a WETLabs chlorophyll fluorometer. Systems maintenance (instrument cleaning, flushing) was done approximately once a week and in port between successive legs. All data were stamped with a GPS.