scholarly journals Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities

2018 ◽  
Author(s):  
Jonathan M. Chase ◽  
Brian J. McGill ◽  
Daniel J. McGlinn ◽  
Felix May ◽  
Shane A. Blowes ◽  
...  

AbstractBecause biodiversity is multidimensional and scale-dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale-dependence matters for empirical studies, and (2) if it does matter, how exactly we should quantify biodiversity change. To address the first question, we analyzed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity—species richness—was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale-dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi-dimensional and multi-scale perspective informs the responses of biodiversity to ecological drivers.Statement of AuthorshipJC and BM conceived the study and the overall approach, and all authors participated in multiple working group meetings to develop and refine the approach. BM collected the data for the meta-analysis that led to Fig. 2,3; JC collected the data for the metaanalysis that led to Figure 4 and S1; SB and FM did the analyses for Figures 2-4; DM, FM and XX wrote the code for the analysis used for the recipe and case study in Figure 6. JC, BM and NG wrote first drafts of most sections, and all authors contributed substantially to revisions.Figure 1.A. Individual-based rarefaction curves of three hypothetical communities (labelled A,B, C) where ranked differences between communities are consistent across scales. B. Individual-based rarefaction curves of three hypothetical communities (labelled A,B, C) where rankings between communities switch because of differences in the total numbers of species, and their relative abundances. Dotted vertical lines illustrate sampling scales where rankings switch. These curves were generated using the sim_sad function from the mobsim R package (May et al. 2018).Figure 2.Bivariate relationships between N, SPIE and S for 346 communities across the 37 datasets taken from McGill (2011b)(see Appendix 1). (A) S as a function of N; (B) S as a function of SPIE. (N vs SPIE not shown). Black lines depict the relationships across studies (and correspond to R2 fixed); colored points and lines show the relationships within studies. All axes are log-scale. Insets are histograms of the study-level slopes, with the solid line representing the slope across all studies. Gray bars indicate the study-level slope did not differ from zero, blue indicates a significant positive slope, and red indicates a significant negative slope.Figure 3.Representative rarefaction curves, the proportion of curves that crossed, and counts of how often curves crossed. (A) Rarefaction curves for different local communities within two datasets: marine invertebrates (nematodes) along a gradient from a waste plant outlet (Lambshead 1986), and trees in a Ugandan rainforest (Eggeling 1947); axes are log-transformed. (B) Counts of how many times pairs of rarefaction curves (from the same community) crossed; y-axis is on a log-scale.Data accessibility statementAll data for meta-analyses and case study will be deposited in a publically available repository with DOI upon acceptance (available in link for submission).

Author(s):  
Alessandra R. Kortz ◽  
Anne E. Magurran

AbstractHow do invasive species change native biodiversity? One reason why this long-standing question remains challenging to answer could be because the main focus of the invasion literature has been on shifts in species richness (a measure of α-diversity). As the underlying components of community structure—intraspecific aggregation, interspecific density and the species abundance distribution (SAD)—are potentially impacted in different ways during invasion, trends in species richness provide only limited insight into the mechanisms leading to biodiversity change. In addition, these impacts can be manifested in distinct ways at different spatial scales. Here we take advantage of the new Measurement of Biodiversity (MoB) framework to reanalyse data collected in an invasion front in the Brazilian Cerrado biodiversity hotspot. We show that, by using the MoB multi-scale approach, we are able to link reductions in species richness in invaded sites to restructuring in the SAD. This restructuring takes the form of lower evenness in sites invaded by pines relative to sites without pines. Shifts in aggregation also occur. There is a clear signature of spatial scale in biodiversity change linked to the presence of an invasive species. These results demonstrate how the MoB approach can play an important role in helping invasion ecologists, field biologists and conservation managers move towards a more mechanistic approach to detecting and interpreting changes in ecological systems following invasion.


2020 ◽  
Author(s):  
Tomas Havranek ◽  
Jiri Novak ◽  
Diana Zigraiova

A key theoretical prediction in financial economics is that under risk neutrality and rational expectations a currency's forward rates should form unbiased predictors of future spot rates. Yet scores of empirical studies report negative slope coefficients from regressions of spot rates on forward rates. We collect 3,643 estimates from 91 research articles and using recently developed techniques investigate the effect of publication and misspecification biases on the reported results. Correcting for these biases yields slope coefficients of 0.31 and 0.98 for developed and emerging currencies respectively, which implies that empirical evidence is in line with the theoretical prediction for emerging economies and less puzzling than commonly thought for developed economies. Our results also suggest that the coefficients are systematically influenced by the choice of data, numeraire currency, and estimation method.


2020 ◽  
Author(s):  
Víctor M Escobedo ◽  
Rodrigo S Rios ◽  
Yulinka Alcayaga-Olivares ◽  
Ernesto Gianoli

Abstract Background and Aims There is a paucity of empirical research and a lack of predictive models concerning the interplay between spatial scale and disturbance as they affect the structure and assembly of plant communities. We proposed and tested a trait dispersion-based conceptual model hypothesizing that disturbance reinforces assembly processes differentially across spatial scales. Disturbance would reinforce functional divergence at the small scale (neighbourhood), would not affect functional dispersion at the intermediate scale (patch) and would reinforce functional convergence at the large scale (site). We also evaluated functional and species richness of native and exotic plants to infer underlying processes. Native and exotic species richness were expected to increase and decrease with disturbance, respectively, at the neighbourhood scale, and to show similar associations with disturbance at the patch (concave) and site (negative) scales. Methods In an arid shrubland, we estimated species richness and functional dispersion and richness within 1 m2 quadrats (neighbourhood) nested within 100 m2 plots (patch) along a small-scale natural disturbance gradient caused by an endemic fossorial rodent. Data for the site scale (2500 m2 plots) were taken from a previous study. We also tested the conceptual model through a quantitative literature review and a meta-analysis. Key Results As spatial scale increased, disturbance sequentially promoted functional divergence, random trait dispersion and functional convergence. Functional richness was unaffected by disturbance across spatial scales. Disturbance favoured natives over exotics at the neighbourhood scale, while both decreased under high disturbance at the patch and site scales. Conclusions The results supported the hypothesis that disturbance reinforces assembly processes differentially across scales and hampers plant invasion. The quantitative literature review and the meta-analysis supported most of the model predictions.


The environment has always been a central concept for archaeologists and, although it has been conceived in many ways, its role in archaeological explanation has fluctuated from a mere backdrop to human action, to a primary factor in the understanding of society and social change. Archaeology also has a unique position as its base of interest places it temporally between geological and ethnographic timescales, spatially between global and local dimensions, and epistemologically between empirical studies of environmental change and more heuristic studies of cultural practice. Drawing on data from across the globe at a variety of temporal and spatial scales, this volume resituates the way in which archaeologists use and apply the concept of the environment. Each chapter critically explores the potential for archaeological data and practice to contribute to modern environmental issues, including problems of climate change and environmental degradation. Overall the volume covers four basic themes: archaeological approaches to the way in which both scientists and locals conceive of the relationship between humans and their environment, applied environmental archaeology, the archaeology of disaster, and new interdisciplinary directions.The volume will be of interest to students and established archaeologists, as well as practitioners from a range of applied disciplines.


2018 ◽  
Vol 613 ◽  
pp. A15 ◽  
Author(s):  
Patrick Simon ◽  
Stefan Hilbert

Galaxies are biased tracers of the matter density on cosmological scales. For future tests of galaxy models, we refine and assess a method to measure galaxy biasing as a function of physical scalekwith weak gravitational lensing. This method enables us to reconstruct the galaxy bias factorb(k) as well as the galaxy-matter correlationr(k) on spatial scales between 0.01hMpc−1≲k≲ 10hMpc−1for redshift-binned lens galaxies below redshiftz≲ 0.6. In the refinement, we account for an intrinsic alignment of source ellipticities, and we correct for the magnification bias of the lens galaxies, relevant for the galaxy-galaxy lensing signal, to improve the accuracy of the reconstructedr(k). For simulated data, the reconstructions achieve an accuracy of 3–7% (68% confidence level) over the abovek-range for a survey area and a typical depth of contemporary ground-based surveys. Realistically the accuracy is, however, probably reduced to about 10–15%, mainly by systematic uncertainties in the assumed intrinsic source alignment, the fiducial cosmology, and the redshift distributions of lens and source galaxies (in that order). Furthermore, our reconstruction technique employs physical templates forb(k) andr(k) that elucidate the impact of central galaxies and the halo-occupation statistics of satellite galaxies on the scale-dependence of galaxy bias, which we discuss in the paper. In a first demonstration, we apply this method to previous measurements in the Garching-Bonn Deep Survey and give a physical interpretation of the lens population.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Thomas J. Vanasse ◽  
Peter T. Fox ◽  
P. Mickle Fox ◽  
Franco Cauda ◽  
Tommaso Costa ◽  
...  

AbstractNetwork architecture is a brain-organizational motif present across spatial scales from cell assemblies to distributed systems. Structural pathology in some neurodegenerative disorders selectively afflicts a subset of functional networks, motivating the network degeneration hypothesis (NDH). Recent evidence suggests that structural pathology recapitulating physiology may be a general property of neuropsychiatric disorders. To test this possibility, we compared functional and structural network meta-analyses drawing upon the BrainMap database. The functional meta-analysis included results from >7,000 experiments of subjects performing >100 task paradigms; the structural meta-analysis included >2,000 experiments of patients with >40 brain disorders. Structure-function network concordance was high: 68% of networks matched (pFWE < 0.01), confirming the broader scope of NDH. This correspondence persisted across higher model orders. A positive linear association between disease and behavioral entropy (p = 0.0006;R2 = 0.53) suggests nodal stress as a common mechanism. Corroborating this interpretation with independent data, we show that metabolic ‘cost’ significantly differs along this transdiagnostic/multimodal gradient.


2021 ◽  
pp. 1-52
Author(s):  
Michel Beine ◽  
Lionel Jeusette

Abstract Recent surveys of the literature on climate change and migration emphasize the important diversity of outcomes and approaches of the empirical studies. In this paper, we conduct a meta-analysis in order to investigate the role of the methodological choices of these empirical studies in finding some particular results concerning the role of climatic factors as drivers of human mobility. We code 51 papers representative of the literature in terms of methodological approaches. This results in the coding of more than 85 variables capturing the methodology of the main dimensions of the analysis at the regression level. These dimensions include authors' reputation, type of mobility, measures of mobility, type of data, context of the study, econometric methods, and last but not least measures of the climatic factors. We look at the influence of these characteristics on the probability of finding any effect of climate change, a displacement effect, an increase in immobility, and evidence in favor of a direct vs. an indirect effect. Our results highlight the role of some important methodological choices, such as the frequency of the data on mobility, the level of development, the measures of human mobility and of the climatic factors as well as the econometric methodology.


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