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Journal ArticleDOI: 10.1126/SCIENCE.ABE5585

Fewer butterflies seen by community scientists across the warming and drying landscapes of the American West

05 Mar 2021-Science (American Association for the Advancement of Science)-Vol. 371, Iss: 6533, pp 1042-1045
Abstract: Uncertainty remains regarding the role of anthropogenic climate change in declining insect populations, partly because our understanding of biotic response to climate is often complicated by habitat loss and degradation among other compounding stressors. We addressed this challenge by integrating expert and community scientist datasets that include decades of monitoring across more than 70 locations spanning the western United States. We found a 1.6% annual reduction in the number of individual butterflies observed over the past four decades, associated in particular with warming during fall months. The pervasive declines that we report advance our understanding of climate change impacts and suggest that a new approach is needed for butterfly conservation in the region, focused on suites of species with shared habitat or host associations.

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Topics: Global warming (55%), Habitat destruction (54%), Climate change (53%)

13 results found

Journal ArticleDOI: 10.1038/S41559-021-01504-1
Erin R. Zylstra1, Leslie Ries2, Naresh Neupane2, Sarah P. Saunders3  +6 moreInstitutions (6)
Abstract: Declines in the abundance and diversity of insects pose a substantial threat to terrestrial ecosystems worldwide. Yet, identifying the causes of these declines has proved difficult, even for well-studied species like monarch butterflies, whose eastern North American population has decreased markedly over the last three decades. Three hypotheses have been proposed to explain the changes observed in the eastern monarch population: loss of milkweed host plants from increased herbicide use, mortality during autumn migration and/or early-winter resettlement and changes in breeding-season climate. Here, we use a hierarchical modelling approach, combining data from >18,000 systematic surveys to evaluate support for each of these hypotheses over a 25-yr period. Between 2004 and 2018, breeding-season weather was nearly seven times more important than other factors in explaining variation in summer population size, which was positively associated with the size of the subsequent overwintering population. Although data limitations prevent definitive evaluation of the factors governing population size between 1994 and 2003 (the period of the steepest monarch decline coinciding with a widespread increase in herbicide use), breeding-season weather was similarly identified as an important driver of monarch population size. If observed changes in spring and summer climate continue, portions of the current breeding range may become inhospitable for monarchs. Our results highlight the increasingly important contribution of a changing climate to insect declines.

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Topics: Population size (57%), Population (57%), Monarch butterfly (55%)

3 Citations

Journal ArticleDOI: 10.1016/J.COIS.2021.05.001
Abstract: Global change includes multiple overlapping and interacting drivers: 1) climate change, 2) land use change, 3) novel chemicals, and 4) the increased global transport of organisms. Recent studies have documented the complex and counterintuitive effects of these drivers on the behavior, life histories, distributions, and abundances of insects. This complexity arises from the indeterminacy of indirect, non-additive and combined effects. While there is wide consensus that global change is reorganizing communities, the available data are limited. As the pace of anthropogenic changes outstrips our ability to document its impacts, ongoing change may lead to increasingly unpredictable outcomes. This complexity and uncertainty argue for renewed efforts to address the fundamental drivers of global change.

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2 Citations


35 results found

Open accessJournal ArticleDOI: 10.1214/SS/1177011136
Abstract: The Gibbs sampler, the algorithm of Metropolis and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, however, iterative simulation can give misleading answers. Our methods are simple and generally applicable to the output of any iterative simulation; they are designed for researchers primarily interested in the science underlying the data and models they are analyzing, rather than for researchers interested in the probability theory underlying the iterative simulations themselves. Our recommended strategy is to use several independent sequences, with starting points sampled from an overdispersed distribution. At each step of the iterative simulation, we obtain, for each univariate estimand of interest, a distributional estimate and an estimate of how much sharper the distributional estimate might become if the simulations were continued indefinitely. Because our focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normality after transformations and marginalization, we derive our results as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations. The methods are illustrated on a random-effects mixture model applied to experimental measurements of reaction times of normal and schizophrenic patients.

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Topics: Bayesian inference (58%), Gibbs sampling (57%), Mixture model (55%) ... read more

12,022 Citations

01 Jan 2013-
Abstract: Statistics An Intduction to Stistical Lerning with Applications in R An Introduction to Statistical Learning provides an accessible overview of the fi eld of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fi elds ranging from biology to fi nance to marketing to astrophysics in the past twenty years. Th is book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classifi cation, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fi elds, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical soft ware platform. Two of the authors co-wrote Th e Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. Th is book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. Th e text assumes only a previous course in linear regression and no knowledge of matrix algebra.

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6,116 Citations

Open accessJournal ArticleDOI: 10.1371/JOURNAL.PONE.0185809
Caspar A. Hallmann1, Martin Sorg, Eelke Jongejans1, Henk Siepel1  +8 moreInstitutions (2)
18 Oct 2017-PLOS ONE
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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Topics: Biomass (ecology) (55%)

1,424 Citations

Journal ArticleDOI: 10.1111/1365-2664.12111
Dave Goulson1Institutions (1)
Abstract: Summary 1. Neonicotinoids are now the most widely used insecticides in the world. They act systemically, travelling through plant tissues and protecting all parts of the crop, and are widely applied as seed dressings. As neurotoxins with high toxicity to most arthropods, they provide effective pest control and have numerous uses in arable farming and horticulture. 2. However, the prophylactic use of broad-spectrum pesticides goes against the long-established principles of integrated pest management (IPM), leading to environmental concerns. 3. It has recently emerged that neonicotinoids can persist and accumulate in soils. They are water soluble and prone to leaching into waterways. Being systemic, they are found in nectar and pollen of treated crops. Reported levels in soils, waterways, field margin plants and floral resources overlap substantially with concentrations that are sufficient to control pests in crops, and commonly exceed the LC50 (the concentration which kills 50% of individuals) for beneficial organisms. Concentrations in nectar and pollen in crops are sufficient to impact substantially on colony reproduction in bumblebees. 4. Although vertebrates are less susceptible than arthropods, consumption of small numbers of dressed seeds offers a route to direct mortality in birds and mammals. 5. Synthesis and applications. Major knowledge gaps remain, but current use of neonicotinoids is likely to be impacting on a broad range of non-target taxa including pollinators and soil and aquatic invertebrates and hence threatens a range of ecosystem services.

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1,047 Citations

Open accessBook
12 Oct 2011-
Abstract: Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS and its open-source sister OpenBugs is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Comprehensive and richly-commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologist. All WinBUGS/OpenBUGS analyses are completely integrated in software R. Includes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R.

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Topics: Population (53%), Bayesian statistics (51%)

788 Citations

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