Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends

Cardinale, Bradley J.; Gonzalez, Andrew; Allington, Ginger R.H.; Loreau, Michel

doi:10.1016/j.biocon.2017.12.021

Cited by 146 publications

(198 citation statements)

References 46 publications

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“…It is now recognised that large-scale biological changes are not always observed locally (Batt, Morley, Selden, Tingley, & Pinsky, 2017;Cardinale et al, 2018); results such as the present, showing increases in species richness and abundance, may seem counterintuitive given that a worldwide decline in biodiversity is unequivocal (Butchart et al, 2010;Scheffers et al, 2016). However, apparent increases in biodiversity may actually be only transient and probably mask profound underlying changes in species identity and community structure and composition.…”

Section: Change In Species Composition and Poleward Shift Of Fish Cmentioning

confidence: 70%

Poleward shift in large‐river fish communities detected with a novel meta‐analysis framework

et al. 2019

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Ongoing global changes are causing major ecological shifts worldwide. Biological trends need to be assessed over long periods of time to better understand past and current community responses. The present study developed a methodological framework for meta‐analyses to be conducted that account for the temporal and spatial autocorrelation of observational data. We provided the R code for processing this framework, which enables temporal trends to be tested through the analysis of long‐term, spatially structured datasets. Taking both types of autocorrelation into account resulted in more conservative but arguably more reliable statistical outcomes. This meta‐analysis framework was then applied to investigate long‐term trends in environmental and fish‐community time series in multiple stations in large French rivers over the past 4 decades. General significant upward and downward trends were highlighted in water temperature and flow discharge, respectively, over the study period. Concomitantly, the density of numerous species increased, resulting in large increases in both species richness (about + 50%) and total fish abundance (approximately four‐fold), but with no significant trend in species evenness. Strong changes in species composition were observed during the study period, with an overall upward trend in the relative abundance of newcomers (i.e. species not sampled during the first years of the survey), while the trend in relative abundance of non‐native species was non‐significant. Moreover, the strongest signal underlying community changes was replacement of northern by southern species. This study showed major changes in fish density and community structure in large rivers over the past 40 years and represents, to our knowledge, one of the first large‐scale actual demonstrations (i.e. based on observations rather than predictions) of an overall poleward shift of freshwater fish communities in response to ongoing global changes.

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Section: Change In Species Composition and Poleward Shift Of Fish Cmentioning

confidence: 70%

Poleward shift in large‐river fish communities detected with a novel meta‐analysis framework

et al. 2019

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“…Gonzalez et al () argued that the risk of biased estimates of change needs to be considered in short time series of species richness. Similarly, Cardinale, Gonzalez, Allington, and Loreau () drew attention to risks of using estimates of the earliest time point as baseline, pointing to the possibility of mistaking regressions to the mean for actual responses. Additionally, nonlinear data transformations can in particular affect the impression time series give us, as the distance between data points will change more in some intervals due to the transformation than in others.…”

Section: Methodsmentioning

confidence: 99%

“…Gonzalez et al (2016) argued that the risk of biased estimates of change needs to be considered in short time series of species richness. Similarly, Cardinale, Gonzalez, Allington, and Loreau (2018) drew attention to risks of using estimates of the earliest time point as baseline, pointing to the possibility of mistaking regressions to the mean for actual responses.…”

Section: Materials and Me Thodsmentioning

confidence: 99%

Assessing species richness trends: Declines of bees and bumblebees in the Netherlands since 1945

Dooren

2019

Ecology and Evolution

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Estimating and predicting temporal trends in species richness is of general importance, but notably difficult because detection probabilities of species are imperfect and many datasets were collected in an opportunistic manner. We need to improve our capabilities to assess richness trends using datasets collected in unstandardized procedures with potential collection bias. Two methods are proposed and applied to estimate richness change, which both incorporate models for sampling effects and detection probability: (a) nonlinear species accumulation curves with an error variance model and (b) Pradel capture–recapture models. The methods are used to assess nationwide temporal trends (1945–2018) in the species richness of wild bees in the Netherlands. Previously, a decelerating decline in wild bee species richness was inferred for part of this dataset. Among the species accumulation curves, those with nonconstant changes in species richness are preferred. However, when analyzing data subsets, constant changes became selected for non‐Bombus bees (for samples in collections) and bumblebees (for spatial grid cells sampled in three periods). Smaller richness declines are predicted for non‐Bombus bees than bumblebees. However, when relative losses are calculated from confidence intervals limits, they overlap and touch zero loss. Capture–recapture analysis applied to species encounter histories infers a constant colonization rate per year and constant local species survival for bumblebees and other bees. This approach predicts a 6% reduction in non‐Bombus species richness from 1945 to 2018 and a significant 19% reduction for bumblebees. Statistical modeling to detect species richness time trends should be systematically complemented with model checking and simulations to interpret the results. Data inspection, assessing model selection bias, and comparisons of trends in data subsets were essential model checking strategies in this analysis. Opportunistic data will not satisfy the assumptions of most models and this should be kept in mind throughout.

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“…A key task of ecology is to quantify and predict changes in community abundance and richness in response to anthropogenic increases in temperatures, species invasions, eutrophication, and habitat destruction (Vitousek 1994). However, given the challenges in interpreting meta-analyses after the fact (Gonzalez et al 2016), there remains a need for hypothesis-driven, standardized data on community trajectories (Cardinale et al 2018) especially for invertebrates (McGill et al 2015). However, given the challenges in interpreting meta-analyses after the fact (Gonzalez et al 2016), there remains a need for hypothesis-driven, standardized data on community trajectories (Cardinale et al 2018) especially for invertebrates (McGill et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Species energy and Thermal Performance Theory predict 20‐yr changes in ant community abundance and richness

Kaspari

Bujan

Roeder

et al. 2019

Ecology

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In an era of rapid climate change, and with it concern over insect declines, we used two theories to predict 20-yr changes in 34 North American ant communities. The ecosystems, from deserts to hardwood forests, were first surveyed in the 1990s. When resurveyed in 2016-2017, they averaged 1°C warmer with 200 g CÁm À2 Áyr À1 higher plant productivity. Ant colony abundance changed from À49% to +61%. Consistent with Thermal Performance Theory, colony abundance increased with temperature increases < 1°C, then decreased as a site's mean monthly temperature change increased up to +2.4°C. Consistent with Species Energy Theory, (1) ant abundance tracked changes in a measure of energy availability (net aboveground productivity, g CÁm À2 Áyr À1 ) and (2) increases in colony abundance drove increases in local plot-and transect-level species richness but not that of Chao 2, an estimate of the size of the species pool. Even after accounting for these drivers, local species richness was still higher 20 yr after the original surveys, likely due to the increased activity of ant workers. These results suggest community changes are predictable using theory from geographical ecology, and that warming can first enhance but may ultimately decrease the abundance of this important insect taxon.

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Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends

Cited by 146 publications

References 46 publications

Poleward shift in large‐river fish communities detected with a novel meta‐analysis framework

Poleward shift in large‐river fish communities detected with a novel meta‐analysis framework

Assessing species richness trends: Declines of bees and bumblebees in the Netherlands since 1945

Species energy and Thermal Performance Theory predict 20‐yr changes in ant community abundance and richness

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