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More than 75 percent decline over 27 years in total flying insect biomass in protected areas.

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TLDR
This analysis estimates a seasonal decline of 76%, and mid-summer decline of 82% in flying insect biomass over the 27 years of study, and shows that this decline is apparent regardless of habitat type, while changes in weather, land use, and habitat characteristics cannot explain this overall decline.
Abstract
Global declines in insects have sparked wide interest among scientists, politicians, and the general public. Loss of insect diversity and abundance is expected to provoke cascading effects on food webs and to jeopardize ecosystem services. Our understanding of the extent and underlying causes of this decline is based on the abundance of single species or taxonomic groups only, rather than changes in insect biomass which is more relevant for ecological functioning. Here, we used a standardized protocol to measure total insect biomass using Malaise traps, deployed over 27 years in 63 nature protection areas in Germany (96 unique location-year combinations) to infer on the status and trend of local entomofauna. Our analysis estimates a seasonal decline of 76%, and mid-summer decline of 82% in flying insect biomass over the 27 years of study. We show that this decline is apparent regardless of habitat type, while changes in weather, land use, and habitat characteristics cannot explain this overall decline. This yet unrecognized loss of insect biomass must be taken into account in evaluating declines in abundance of species depending on insects as a food source, and ecosystem functioning in the European landscape.

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The Sixth Mass Extinction: fact, fiction or speculation?

TL;DR: Differences in extinction rates are reviewed according to realms: marine species face significant threats but, although previous mass extinctions were largely defined by marine invertebrates, there is no evidence that the marine biota has reached the same crisis as the non-marine biota, and island species have suffered far greater rates than continental ones.
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Deep learning and computer vision will transform entomology.

TL;DR: In this paper, the authors connect recent developments in deep learning and computer vision to the urgent demand for more cost-efficient monitoring of insects and other invertebrates and discuss the challenges that lie ahead for the implementation of such solutions in entomology.
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The essential role of other effective area-based conservation measures in achieving big bold conservation targets

TL;DR: Other effective area-based conservation measures (OECMs. as discussed by the authors have been proposed as a way to support the conservation of areas that deliver conservation outcomes outside the protected area estate.
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Environmental DNA Time Series in Ecology.

TL;DR: How environmental DNA (eDNA) is starting to provide a powerful new source of temporal data for research questions that have so far been overlooked, by helping to resolve the ecological dynamics of populations, communities, and ecosystems over hundreds to thousands of years is highlighted.
Journal ArticleDOI

Isotopic evidence for oligotrophication of terrestrial ecosystems

Joseph M. Craine, +40 more
TL;DR: Foliar nitrogen (N) concentrations and isotope ratios obtained from >43,000 samples acquired over 37 years suggest global declines in N supply relative to plant demand, consistent with elevated atmospheric carbon dioxide.
References
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Journal ArticleDOI

Fitting Linear Mixed-Effects Models Using lme4

TL;DR: In this article, a model is described in an lmer call by a formula, in this case including both fixed-and random-effects terms, and the formula and data together determine a numerical representation of the model from which the profiled deviance or the profeatured REML criterion can be evaluated as a function of some of model parameters.
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Inference from Iterative Simulation Using Multiple Sequences

TL;DR: The focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normal- ity after transformations and marginalization, and the results are derived as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations.
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Bayesian measures of model complexity and fit

TL;DR: In this paper, the authors consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined and derive a measure pD for the effective number in a model as the difference between the posterior mean of the deviances and the deviance at the posterior means of the parameters of interest, which is related to other information criteria and has an approximate decision theoretic justification.
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Global pollinator declines: trends, impacts and drivers.

TL;DR: The nature and extent of reported declines, and the potential drivers of pollinator loss are described, including habitat loss and fragmentation, agrochemicals, pathogens, alien species, climate change and the interactions between them are reviewed.

JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling

TL;DR: JAGS is a program for Bayesian Graphical modelling which aims for compatibility with Classic BUGS and could eventually be developed as an R package.
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