Heterozygosity‐Fitness Correlations and Inbreeding Depression in Two Critically Endangered Mammals

The relation among inbreeding, heterozygosity, and fitness has been studied primarily among outbred populations, and little is known about these phenomena in endangered populations. Most researchers conclude that the relation between coefficient of inbreeding estimated from pedigrees and fitness traits (inbreeding‐fitness correlations) better reflects inbreeding depression than the relation between marker heterozygosity and fitness traits (heterozygosity‐fitness correlations). However, it has been suggested recently that heterozygosity‐fitness correlations should only be expected when inbreeding generates extensive identity disequilibrium (correlations in heterozygosity and homozygosity across loci throughout the genome). We tested this hypothesis in Mohor gazelle (Gazella dama mhorr) and Iberian lynx (Lynx pardinus). For Mohor gazelle, we calculated the inbreeding coefficient and measured heterozygosity at 17 microsatellite loci. For Iberian lynx, we measured heterozygosity at 36 microsatellite loci. In both species we estimated semen quality, a phenotypic trait directly related to fitness that is controlled by many loci and is affected by inbreeding depression. Both species showed evidence of extensive identity disequilibrium, and in both species heterozygosity was associated with semen quality. In the Iberian lynx the low proportion of normal sperm associated with low levels of heterozygosity was so extreme that it is likely to limit the fertility of males. In Mohor gazelle, although heterozygosity was associated with semen quality, inbreeding coefficient was not. This result suggests that when coefficient of inbreeding is calculated on the basis of a genealogy that begins after a long history of inbreeding, the coefficient of inbreeding fails to capture previous demographic information because it is a poor estimator of accumulated individual inbreeding. We conclude that among highly endangered species with extensive identity disequilibrium, examination of heterozygosity‐fitness correlations may be an effective way to detect inbreeding depression, whereas inbreeding‐fitness correlations may be poor indicators of inbreeding depression if the pedigree does not accurately reflect the history of inbreeding. Correlaciones Heterocigosidad‐ Adaptabilidad y Depresión Endogámica en Dos Especies de Mamíferos Críticamente en Peligro     

Environmental quality assessment combining sediment metal levels, biomarkers and macrobenthic communities: application to the óbidos coastal lagoon (Portugal)

Macroinvertebrate benthic communities are one of the key biological components considered for the assessment of benthic integrity in the context of the Water Framework Directive (WFD). However, under moderate contamination scenarios, the assessment of macrobenthic alterations at community level alone could be insufficient to discriminate the environmental quality of coastal and transitional waters. Keeping this in view, sediment quality of moderately contaminated sites in a coastal lagoon (óbidos lagoon, Portugal) was assessed by the combination of sediment metal levels, Carcinus maenas biomarkers (accumulated metals and oxidative stress responses) and macrobenthic communities. Two sites were selected in confined inner branches (BS and BB) and a third one in the middle lagoon (ML). The site BB presented slightly higher levels of metals in sediment but biological variables calculated for macrobenthic data were not significantly different between sites. The biotic index M-AMBI that is being applied to assess environmental quality of transitional waters in the scope of the WFD pointed either to high (site ML) or good quality status (BS and BB) in the selected sites. However, crabs from BB site presented significantly higher levels of Ni in hepatopancreas than those from ML and macrobenthic community structure was significantly different between BB and ML. Additionally, spatial differences were obtained for oxidative stress parameters suggesting that BB site presented stressors for crabs (higher GST and lower GSH_t at BB site). Factor analysis (PCA) integrating sediment contamination, biomarkers in crabs and macrobenthic data also distinguished BB site as the most environmentally disturbed. On the other hand, at ML site, some macrobenthic variables (equitability and polychaetes’ diversity) were found to be enhanced by current environmental conditions, suggesting the existence of a better sediment quality. Current results pointed to the usefulness of integrating macrobenthic community alterations with responses at organism level (bioaccumulation and biochemical endpoints) in order to increase the accuracy of environmental quality assessment in lagoon systems. Moreover, the application of different statistical methods was also found to be recommendable.     

Carbon footprint of canned mussels from a business-to-consumer approach. A starting point for mussel processors and policy makers

The increasing demand for environmental information on the global warming impact of products requires a solid methodological framework which guarantees comparability and communicability. The publicly available specification PAS 2050 combines approaches to a variety of greenhouse gas specific assessment issues to deliver a globally applicable product Carbon Footprinting (CF) method, which is expected to be widely accepted. Specifically, this paper aims to demonstrate the implementation of a CF scheme for a common canned mussel product according to PAS 2050 guidelines. A final value of 4.35 kg CO₂e per triple pack of round cans of mussels was calculated. Furthermore, this CF study led to identify primary packaging (can production) and mussel shell management as the main activities where efforts should focus for climate change mitigation. Throughout this case study, CF opportunities and drawbacks are discussed. The whole text tries to provide a starting point for both mussel processors and policy makers to benefit from the potential advantages of a responsible use of this increasingly popular tool.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.