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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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Journal ArticleDOI

Glowing, glowing, gone? Monitoring long-term trends in glow-worm numbers in south-east England

TL;DR: This paper used additive mixed models (GAMMs) to control for varying sampling effort, temporal autocorrelation, non-stationarity of seasonal phenology and nonlinearity of temporal trajectories across sites.
Journal ArticleDOI

Analysis of tropical and temperate elevational gradients in arthropod abundance

TL;DR: It is suggested that future changes in the length of growing season will impact the elevation at which summer arthropod abundance peaks and the sharpness of the peak, likely affecting diversity and distribution of other taxa that interact with arthropods.
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Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany

TL;DR: This study compiled over 1 million occurrence records of Odonata (dragonflies and damselflies) from different regional databases across Germany and developed a novel approach using time-series clustering to identify groups of species with similar patterns of temporal change.
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.
Journal ArticleDOI

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.
Journal ArticleDOI

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.
Journal ArticleDOI

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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