The direct drivers of recent global anthropogenic biodiversity loss

Science Advances, Год журнала: 2022, Номер 8(45)

Опубликована: Ноя. 9, 2022

Effective policies to halt biodiversity loss require knowing which anthropogenic drivers are the most important direct causes. Whereas previous knowledge has been limited in scope and rigor, here we statistically synthesize empirical comparisons of recent driver impacts found through a wide-ranging review. We show that land/sea use change dominant worldwide. Direct exploitation natural resources ranks second pollution third; climate invasive alien species have significantly less than top two drivers. The oceans, where dominate, different hierarchy from land fresh water. It also varies among types indicators. For example, is more community composition changes populations. Stopping global requires actions tackle all major their interactions, not some them isolation.

Язык: Английский

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Sampling biases shape our view of the natural world

Ecography, Год журнала: 2021, Номер 44(9), С. 1259 - 1269

Опубликована: Июнь 21, 2021

Spatial patterns of biodiversity are inextricably linked to their collection methods, yet no synthesis bias or consequences exists. As such, views organismal distribution and the ecosystems they make up may be incorrect, undermining countless ecological evolutionary studies. Using 742 million records 374 900 species, we explore global impacts biases related taxonomy, accessibility, ecotype data type across terrestrial marine systems. Pervasive sampling observation exist animals, with only 6.74% globe sampled, disproportionately poor tropical sampling. High elevations deep seas particularly unknown. Over 50% in most groups account for under 2% species citizen‐science exacerbates biases. Additional will needed overcome many these biases, but must increasingly value publication bridge this gap better represent species' distributions from more distant inaccessible areas, provide necessary basis conservation management.

Язык: Английский

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Endemism increases species' climate change risk in areas of global biodiversity importance

Biological Conservation, Год журнала: 2021, Номер 257, С. 109070 - 109070

Опубликована: Апрель 9, 2021

Язык: Английский

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Temperature-related biodiversity change across temperate marine and terrestrial systems

Nature Ecology & Evolution, Год журнала: 2020, Номер 4(7), С. 927 - 933

Опубликована: Май 4, 2020

Язык: Английский

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The soil plastisphere

Nature Reviews Microbiology, Год журнала: 2023, Номер 22(2), С. 64 - 74

Опубликована: Сен. 11, 2023

Язык: Английский

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Increasing the number of stressors reduces soil ecosystem services worldwide

Nature Climate Change, Год журнала: 2023, Номер 13(5), С. 478 - 483

Опубликована: Март 16, 2023

Increasing the number of environmental stressors could decrease ecosystem functioning in soils. Yet this relationship has never been globally assessed outside laboratory experiments. Here, using two independent global standardized field surveys, and a range natural human factors, we test between exceeding different critical thresholds maintenance multiple services across biomes. Our analysis shows that, stressors, from medium levels (>50%), negatively significantly correlates with impacts on services, that crossing high-level threshold (over 75% maximum observed levels), reduces soil biodiversity globally. The >75% was consistently seen as an important predictor therefore improving prediction functioning. findings highlight need to reduce dimensionality footprint ecosystems conserve function.

Язык: Английский

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A framework for the detection and attribution of biodiversity change

Philosophical Transactions of the Royal Society B Biological Sciences, Год журнала: 2023, Номер 378(1881)

Опубликована: Май 29, 2023

The causes of biodiversity change are great scientific interest and central to policy efforts aimed at meeting targets. Changes in species diversity high rates compositional turnover have been reported worldwide. In many cases, trends detected, but these rarely causally attributed possible drivers. A formal framework guidelines for the detection attribution is needed. We propose an inferential guide analyses, which identifies five steps—causal modelling, observation, estimation, attribution—for robust attribution. This workflow provides evidence relation hypothesized impacts multiple potential drivers can eliminate putative from contention. encourages a reproducible statement confidence about role after methods trend deployed. Confidence requires that data analyses used all steps follow best practices reducing uncertainty each step. illustrate with examples. could strengthen bridge between science support effective actions halt loss this has on ecosystems. article part theme issue ‘Detecting attributing change: needs, gaps solutions’.

Язык: Английский

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Looking back on biodiversity change: lessons for the road ahead

Philosophical Transactions of the Royal Society B Biological Sciences, Год журнала: 2023, Номер 378(1881)

Опубликована: Май 29, 2023

Estimating biodiversity change across the planet in context of widespread human modification is a critical challenge. Here, we review how has changed recent decades scales and taxonomic groups, focusing on four diversity metrics: species richness, temporal turnover, spatial beta-diversity abundance. At local scales, all metrics includes many examples both increases declines tends to be centred around zero, but with higher prevalence declining trends (increasing similarity composition space or biotic homogenization) The exception this pattern changes through time observed most assemblages. Less known about at regional although several studies suggest that richness are more prevalent than declines. Change global scale hardest estimate accurately, extinction rates probably outpacing speciation rates, elevated. Recognizing variability essential accurately portray unfolding, highlights much remains unknown magnitude direction multiple different scales. Reducing these blind spots allow appropriate management actions deployed. This article part theme issue ‘Detecting attributing causes change: needs, gaps solutions’.

Язык: Английский

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The undetectability of global biodiversity trends using local species richness

Ecography, Год журнала: 2023, Номер 2023(3)

Опубликована: Фев. 9, 2023

Although species are being lost at alarming rates, previous research has provided conflicting results on the extent and even direction of global biodiversity change local scale. Here, we assessed ability to detect trends using richness how it is affected by number monitoring sites, sampling interval (i.e. time between original survey re‐survey site), measurement error (error richness), spatial grain (a proxy for taxa mobility) biases site‐selection biases). We use PREDICTS model‐based estimates as a real‐world distribution randomly selected sites calculate trends. found that while network with hundreds could in within 30‐year period, detecting doubled decade, increased 10‐fold three years yearly were undetectable. Measurement errors had non‐linear effect statistical power, 1% reducing power slight margin 5% drastically reliably any trend. The was also related grain, making harder sampled smaller plot sizes. Spatial not only reduced negative but sometimes yielded positive conclude accurate may simply be unfeasible current approaches. suggest representative implemented national level, combined models accounting biases, can help improve our understanding change.

Язык: Английский

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Studying interactions among anthropogenic stressors in freshwater ecosystems: A systematic review of 2396 multiple‐stressor experiments

Ecology Letters, Год журнала: 2024, Номер 27(6)

Опубликована: Июнь 1, 2024

Abstract Understanding the interactions among anthropogenic stressors is critical for effective conservation and management of ecosystems. Freshwater scientists have invested considerable resources in conducting factorial experiments to disentangle stressor by testing their individual combined effects. However, diversity systems studied has hindered previous syntheses this body research. To overcome challenge, we used a novel machine learning framework identify relevant studies from over 235,000 publications. Our synthesis resulted new dataset 2396 multiple‐stressor freshwater systems. By summarizing methods these studies, quantifying trends popularity investigated stressors, performing co‐occurrence analysis, produce most comprehensive overview diverse field research date. We provide both taxonomy grouping 909 into 31 classes an open‐source interactive version ( https://jamesaorr.shinyapps.io/freshwater‐multiple‐stressors/ ). Inspired our results, help clarify whether statistical detected align with interest, outline general guidelines design any system. conclude highlighting directions required better understand ecosystems facing multiple stressors.

Язык: Английский

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