No abstract

SNP data sets can be used to infer a wealth of information about natural populations, including information about their structure, genetic diversity, and the presence of loci under selection. However, SNP data analysis can be a time‐consuming and challenging process, not in the least because at present many different software packages are needed to execute and depict the wide variety of mainstream population‐genetic analyses. Here, we present SambaR, an integrative and user‐friendly R package which automates and simplifies quality control and population‐genetic analyses of biallelic SNP data sets. SambaR allows users to perform mainstream population‐genetic analyses and to generate a wide variety of ready to publish graphs with a minimum number of commands (less than 10). These wrapper commands call functions of existing packages (including adegenet, ape, LEA, poppr, pcadapt and StAMPP) as well as new tools uniquely implemented in SambaR. We tested SambaR on online available SNP data sets and found that SambaR can process data sets of over 100,000 SNPs and hundreds of individuals within hours, given sufficient computing power. Newly developed tools implemented in SambaR facilitate optimization of filter settings, objective interpretation of ordination analyses, enhance comparability of diversity estimates from reduced representation library SNP data sets, and generate reduced SNP panels and structure‐like plots with Bayesian population assignment probabilities. SambaR facilitates rapid population genetic analyses on biallelic SNP data sets by removing three major time sinks: file handling, software learning, and data plotting. In addition, SambaR provides a convenient platform for SNP data storage and management, as well as several new utilities, including guidance in setting appropriate data filters. The SambaR source script, manual and example data set are distributed through GitHub: https://github.com/mennodejong1986/SambaR.

Despite ongoing loss of diversity in freshwater ecosystems, and despite mitigation measures to halt this loss, it is still not clear what ecological drivers underlies lotic biodiversity. A complicating factor is that two of the main drivers, oxygen and temperature, are correlated, and hence studies towards drivers of lotic diversity are confounded. Here, we undertook a systematic review, consisting of both qualitative and quantitative analyses, to disentangle these two drivers. We accessed two literature repositories and assessed papers for eligibility using a set of predetermined criteria. For the qualitative part of this systematic review, we used results on patterns of taxonomic richness and multivariate ordination analyses to expose effects of temperature and dissolved oxygen concentration on biodiversity. For the meta-analysis, we could only use raw data of a few papers in generalized linear models. The qualitative analysis did not show strong consistent effects of either dissolved oxygen concentration or temperature on diversity. However, the meta-analysis showed that taxonomic richness is positively related with dissolved oxygen concentration. Inversely a negative correlation with temperature was found, but adding temperature to a model which already included dissolved oxygen content did not significantly improve the model. These results show the strength of a systematic review and meta-analysis over a conventional review without a meta-analysis; we found no pattern with the qualitative analysis, but a strong pattern with the quantitative analysis.

No abstract

In areas where farmland borders protected areas, wildlife may be attracted to crops and cause substantial financial damage for farmers. Elephants, in particular, can destroy a year's harvest in a single night, and can also cause damage to buildings and other farm structures. Few studies have examined whether damage caused by wild elephants increases social inequalities in farmer communities. We interviewed settlement leaders and subsistence rice farmers living in the buffer zone of Bardiya National Park, Nepal, to examine (1) the variation and spatial distribution of wealth within the farmer community, (2) the severity and spatio-temporal distribution of damage inflicted by Asian elephants Elephas maximus, and (3) the willingness to insure against such damage. We investigated whether particular societal strata are disproportionally affected by negative interactions with elephants. We found that farmers near the boundary between agricultural and wilderness areas were significantly poorer and had smaller landholdings than those further into the cultivated lands. Concomitantly, damage to crops and houses was more frequent nearer the wilderness–agriculture boundary than further away from it. Hence, in the buffer zone of Bardiya National Park, farmers near the wilderness–cultivation boundary, with small landholdings, had a relatively higher cost of elephant damage, yet were less willing to pay for an insurance scheme. We infer that in areas where both social inequality and damage caused by wildlife are spatially structured, conservation success may cause economic hardship for the local community, particularly for the poorer class. We discuss causes of the current lack of communal mitigation measures against the damage caused by elephants in the Park, and potential solutions.