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Hougaard Lau posted an update 6 months, 2 weeks ago
By assessing the taxonomic composition of the samples, we show that metabarcoding data allowed the detection of previously recorded nonindigenous species as well as to reveal presence of new ones, even if in low abundance. Synthesis and application. Our comprehensive assessment of metabarcoding for port biological baseline surveys sets the basics for cost-effective, standardized, and comprehensive monitoring of nonindigenous species and for performing risk assessments in ports. This development will contribute to the implementation of the recently entered into force International Convention for the Control and Management of Ships’ Ballast Water and Sediments. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.The abundance of insects has decreased for the last decades in many parts of the world although so far few studies have quantified this reduction because there have only been few baseline studies dating back decades that have allowed comparison of ancient and recent population estimates. Such a paired design is particularly powerful because it reduces or eliminates bias caused by differences in identity and experience of observers, identity of study sites, years, time of season, and time of day, and it ensures identity of sampling procedures. Here, I compiled information on the reduction in abundance of insects in Europe and Algeria by the same persons compiling the abundance of insects from the same 21 study sites during 1951-1997 and again a second time in 1998-2018. There was a reduction by 47% in the abundance of insects. The difference in abundance in old compared to new samples declined with latitude, with a significant variance among taxa. This reduction in abundance of insects was of such a magnitude that it must have consequences for insectivores and the role that insects play in ecosystems. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Environmental change and habitat fragmentation will affect population densities for many species. For those species that have locally adapted to persist in changed or stressful habitats, it is uncertain how density dependence will affect adaptive responses. Anurans (frogs and toads) are typically freshwater organisms, but some coastal populations of green treefrogs (Hyla cinerea) have adapted to brackish, coastal wetlands. Tadpoles from coastal populations metamorphose sooner and demonstrate faster growth rates than inland populations when reared solitarily. Although saltwater exposure has adaptively reduced the duration of the larval period for coastal populations, increases in densities during larval development typically increase time to metamorphosis and reduce rates of growth and survival. We test how combined stressors of density and salinity affect larval development between salt-adapted (“coastal”) and nonsalt-adapted (“inland”) populations by measuring various developmental and metamorphic phenotypes. We found that increased tadpole density strongly affected coastal and inland tadpole populations similarly. In high-density treatments, both coastal and inland populations had reduced growth rates, greater exponential decay of growth, a smaller size at metamorphosis, took longer to reach metamorphosis, and had lower survivorship at metamorphosis. Salinity only exaggerated the effects of density on the time to reach metamorphosis and exponential decay of growth. Location of origin affected length at metamorphosis, with coastal tadpoles metamorphosing slightly longer than inland tadpoles across densities and salinities. These findings confirm that density has a strong and central influence on larval development even across divergent populations and habitat types and may mitigate the expression (and therefore detection) of locally adapted phenotypes. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Ecological data sets often record the abundance of species, together with a set of explanatory variables. Multivariate statistical methods are optimal to analyze such data and are thus frequently used in ecology for exploration, visualization, and inference. Most approaches are based on pairwise distance matrices instead of the sites-by-species matrix, which stands in stark contrast to univariate statistics, where data models, assuming specific distributions, are the norm. However, through advances in statistical theory and computational power, models for multivariate data have gained traction. Systematic simulation-based performance evaluations of these methods are important as guides for practitioners but still lacking. Here, we compare two model-based methods, multivariate generalized linear models (MvGLMs) and constrained quadratic ordination (CQO), with two distance-based methods, distance-based redundancy analysis (dbRDA) and canonical correspondence analysis (CCA). We studied the performance of the methods to discriminate between causal variables and noise variables for 190 simulated data sets covering different sample sizes and data distributions. MvGLM and dbRDA differentiated accurately between causal and noise variables. The former had the lowest false-positive rate (0.008), while the latter had the lowest false-negative rate (0.027). CQO and CCA had the highest false-negative rate (0.291) and false-positive rate (0.256), respectively, where these error rates were typically high for data sets with linear responses. Our study shows that both model- and distance-based methods have their place in the ecologist’s statistical toolbox. MvGLM and dbRDA are reliable for analyzing species-environment relations, whereas both CQO and CCA exhibited considerable flaws, especially with linear environmental gradients. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.Improved efficiency of Markov chain Monte Carlo facilitates all aspects of statistical analysis with Bayesian hierarchical models. Identifying strategies to improve MCMC performance is becoming increasingly crucial as the complexity of models, and the run times to fit them, increases. We evaluate different strategies for improving MCMC efficiency using the open-source software NIMBLE (R package nimble) using common ecological models of species occurrence and abundance as examples. selleck chemical We ask how MCMC efficiency depends on model formulation, model size, data, and sampling strategy. For multiseason and/or multispecies occupancy models and for N-mixture models, we compare the efficiency of sampling discrete latent states vs. integrating over them, including more vs. fewer hierarchical model components, and univariate vs. block-sampling methods. We include the common MCMC tool JAGS in comparisons. For simple models, there is little practical difference between computational approaches. As model complexity increases, there are strong interactions between model formulation and sampling strategy on MCMC efficiency.
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