Predicting species abundance distributions by simultaneously using number and biomass as units of measurement

The universal observation that some species in an ecological community are common, but many more are rare, is neatly encapsulated in a species abundance distribution (SAD)1. However, the shape of the distribution can depend on the currency used to measure abundance 2. Here we show how the SADs for numerical abundance and biomass are related and how this relationship can be used to predict the form of the SAD. When plotted in log numerical abundance, log biomass space, species points lie within an approximately triangular area the limits of which are set by body size range, and the upper limit of abundance in both metrics. Under the simplifying, but reasonable, assumption that the observed scatter of species within this region is random, the shape of the SAD is immediately derived from simple geometrical considerations. For the SAD of numerical abundance this is a power curve. The biomass SAD can be either a power curve or, more frequently, a unimodal curve, which can approximate a log normal. This log triangular random placement model serves as a null hypothesis against which actual communities can be compared. Data from two intensively surveyed local communities indicate that it can give a good approximation, with species scattered within a triangle. Further, we can predict the consequences, for the SAD, of size-selective sampling protocols. We argue that mechanistic models of SADs must be able to account for the relative abundance of species in alternative currencies. Moreover, this approach will shed light on niche packing and may have application in environmental monitoring

Temporal turnover and the maintenance of diversity in ecological assemblages

Temporal variation in species abundances occurs in all ecological communities. Here, we explore the role that this temporal turnover plays in maintaining assemblage diversity. We investigate a three-decade time series of estuarine fishes and show that the abundances of the individual species fluctuate asynchronously around their mean levels. We then use a time-series modelling approach to examine the consequences of different patterns of turnover, by asking how the correlation between the abundance of a species in a given year and its abundance in the previous year influences the structure of the overall assemblage. Classical diversity measures that ignore species identities reveal that the observed assemblage structure will persist under all but the most extreme conditions. However, metrics that track species identities indicate a narrower set of turnover scenarios under which the predicted assemblage resembles the natural one. Our study suggests that species diversity metrics are insensitive to change and that measures that track species ranks may provide better early warning that an assemblage is being perturbed. It also highlights the need to incorporate temporal turnover in investigations of assemblage structure and function

Inferring macro-ecological patterns from local presence/absence data

Biodiversity provides support for life, vital provisions, regulating services and has positive cultural impacts. It is therefore important to have accurate methods to measure biodiversity, in order to safeguard it when we discover it to be threatened. For practical reasons, biodiversity is usually measured at fine scales whereas diversity issues (e.g. conservation) interest regional or global scales. Moreover, biodiversity may change across spatial scales. It is therefore a key challenge to be able to translate local information on biodiversity into global patterns. Many databases give no information about the abundances of a species within an area, but only its occurrence in each of the surveyed plots. In this paper, we introduce an analytical framework (implemented in a ready‐to‐use R code) to infer species richness and abundances at large spatial scales in biodiversity‐rich ecosystems when species presence/absence information is available on various scattered samples (i.e. upscaling). This framework is based on the scale‐invariance property of the negative binomial. Our approach allows to infer and link within a unique framework important and well‐known biodiversity patterns of ecological theory, such as the species accumulation curve (SAC) and the relative species abundance (RSA) as well as a new emergent pattern, which is the relative species occupancy (RSO). Our estimates are robust and accurate, as confirmed by tests performed on both in silico‐generated and real forests. We demonstrate the accuracy of our predictions using data from two well‐studied forest stands. Moreover, we compared our results with other popular methods proposed in the literature to infer species richness from presence to absence data and we showed that our framework gives better estimates. It has thus important applications to biodiversity research and conservation practice

The impact of resource dependence of the mechanisms of life on the spatial population dynamics of an in silico microbial community

Biodiversity has a critical impact on ecosystem functionality and stability, and thus the current biodiversity crisis has motivated many studies of the mechanisms that sustain biodiversity, a notable example being non-transitive or cyclic competition. We therefore extend existing microscopic models of communities with cyclic competition by incorporating resource dependence in demographic processes, characteristics of natural systems often oversimplified or overlooked by modellers. The spatially explicit nature of our individual-based model of three interacting species results in the formation of stable spatial structures, which have significant effects on community functioning, in agreement with experimental observations of pattern formation in microbial communities. Published by AIP Publishing

Dominance structure of assemblages is regulated over a period of rapid environmental change

F.A.M.J. is financed by the School of Biology, University of St Andrews. A.E.M. acknowledges funding from the European Research Council (ERCAdG BioTIME 250189 and ERCPoC BioCHANGE 727440).Ecological assemblages are inherently uneven, with numerically dominant species contributing disproportionately to ecosystem services. Marked biodiversity change due to growing pressures on the world's ecosystems is now well documented. However, the hypothesis that dominant species are becoming relatively more abundant has not been tested. We examined the prediction that the dominance structure of contemporary communities is shifting, using a meta-analysis of 110 assemblage timeseries. Changes in relative and absolute dominance were evaluated with mixed and cyclic-shift permutation models. Our analysis uncovered no evidence of a systematic change in either form of dominance, but established that relative dominance is preserved even when assemblage size (total N) changes. This suggests that dominance structure is regulated alongside richness and assemblage size, and highlights the importance of investigating multiple components of assemblage diversity when evaluating ecosystem responses to environmental drivers.PostprintPeer reviewe

Gradients in predation risk in a tropical river system

We are grateful for 2 European Research Council grants (BIOTIME 250189 and BioCHANGE 727440).The importance of predation risk as a key driver of evolutionary change is exemplified by the Northern Range in Trinidad, where research on guppies living in multiple parallel streams has provided invaluable insights into the process of evolution by natural selection. Although Trinidadian guppies are now a textbook example of evolution in action, studies have generally categorized predation as a dichotomous variable, representing high or low risk. Yet, ecologists appreciate that community structure and the attendant predation risk vary substantially over space and time. Here, we use data from a longitudinal study of fish assemblages at 16 different sites in the Northern Range to quantify temporal and spatial variation in predation risk. Specifically we ask: 1) Is there evidence for a gradient in predation risk? 2) Does the ranking of sites (by risk) change with the definition of the predator community (in terms of species composition and abundance currency), and 3) Are site rankings consistent over time? We find compelling evidence that sites lie along a continuum of risk. However, site rankings along this gradient depend on how predation is quantified in terms of the species considered to be predators and the abundance currency is used. Nonetheless, for a given categorization and currency, rankings are relatively consistent over time. Our study suggests that consideration of predation gradients will lead to a more nuanced understanding of the role of predation risk in behavioral and evolutionary ecology. It also emphasizes the need to justify and report the definition of predation risk being used.Publisher PDFPeer reviewe

Quantifying the importance of functional traits for primary production in aquatic plant communities

1. Aquatic plant meadows are important coastal habitats that sustain many ecosystem functions such as primary production and carbon sequestration. Currently, there is a knowledge gap in understanding which plant functional traits, for example, leaf size or plant height underlie primary production in aquatic plant communities. 2. To study how plant traits are related to primary production, we conducted a field survey in the Baltic Sea, Finland, which is characterized by high plant species and functional diversity. Thirty sites along an exposure gradient were sampled (150 plots), and nine plant morphological and chemical traits measured. The aim was to discern how community-weighted mean traits affect community production and whether this relationship changes along an environmental gradient using structural equation modelling (SEM). 3. Plant height had a direct positive effect on production along an exposure gradient (r = 0.33) and indirect effects through two leaf chemical traits, leaf δ15N and leaf δ13C (r = 0.24 and 0.18, respectively) resulting in a total effect of 0.28. In plant communities experiencing varying exposure, traits such as root N concentration and leaf δ15N had positive and negative effects on production, respectively. 4. Synthesis. Our results demonstrate that the relationship between aquatic plant functional traits and community production is variable and changes over environmental gradients. Plant height generally has a positive effect on community production along an exposure gradient, while the link between other traits and production changes in plant communities experiencing varying degrees of exposure. Thus, the underlying biological mechanisms influencing production differ in plant communities, emphasizing the need to resolve variability and its drivers in real-world communities. Importantly, functionally diverse plant communities sustain ecosystem functioning differently andPeer reviewe

Measuring temporal change in alpha diversity : a framework integrating taxonomic, phylogenetic and functional diversity and the iNEXT.3D standardization

Funding: This work is jointly supported by the Natural Environment Research Council, UK (NE/T004487/1 for AM and MD) and the Taiwan Ministry of Science and Technology under Contracts NERC-MOST 108-2923-M-007-003 (for AC and CC). AM and MD also acknowledge support from the Leverhulme Trust (RPG-2019-401).1. Biodiversity is a multifaceted concept covering different levels of organisation from genes to ecosystems. Biodiversity has at least three dimensions: (i) Taxonomic diversity (TD): a measure that is sensitive to the number and abundances of species. (ii) Phylogenetic diversity (PD): a measure that incorporates not only species abundances but also species evolutionary histories. (iii) Functional diversity (FD): a measure that considers not only species abundances but also species? traits. 2. We integrate the three dimensions of diversity under a unified framework of Hill numbers and their generalizations. Our TD quantifies the effective number of equally-abundant species, PD quantifies the effective total branch length, mean-PD (PD divided by tree depth) quantifies the effective number of equally-divergent lineages, and FD quantifies the effective number of equally-distinct virtual functional groups (or functional ?species?). Thus, TD, mean-PD and FD are all in the same units of species/lineage equivalents and can be meaningfully compared. 3. Like species richness, empirical TD, PD and FD based on sampling data, depend on sampling effort and sample completeness. For TD (Hill numbers), the iNEXT (interpolation and extrapolation) standardization was developed for standardizing sample size or sample completeness (as measured by sample coverage, the fraction of individuals that belong to the observed species) to make objective comparisons across studies. This paper extends the iNEXT method to the iNEXT.3D standardization to encompass all three dimensions of diversity via sample-size- and sample-coverage-based rarefaction and extrapolation under the unified framework. The asymptotic diversity estimates (i.e., sample size tends to infinity and sample coverage tends to unity) are also derived. In addition to individual-based abundance data, the proposed iNEXT.3D standardization is adapted to deal with incidence-based occurrence data. 4. We apply the integrative framework and the proposed iNEXT.3D standardization to measure temporal alpha-diversity changes for estuarine fish assemblage data spanning four decades. The influence of environmental drivers on diversity change are also assessed. Our analysis informs a mechanistic interpretation of biodiversity change in the three dimensions of diversity. The accompanying freeware, iNEXT.3D, developed during this project, facilitates all computation and graphics.PostprintPeer reviewe

Landscape-scale forest loss as a catalyst of population and biodiversity change

The BioTIME database was supported by ERC AdG BioTIME 250189 and ERC PoC BioCHANGE 727440. We thank the ERC projects BioTIME and BioCHANGE for supporting the initial data synthesis work that led to this study, and the Leverhulme Centre for Anthropocene Biodiversity for continued funding of the database. Also supported by a Carnegie-Caledonian PhD Scholarship and NERC doctoral training partnership grant NE/L002558/1 (G.N.D.), a Leverhulme Fellowship and the Leverhulme Centre for Anthropocene Biodiversity (M.D.), Leverhulme Project Grant RPG-2019-402 (A.E.M. and M.D.), and the German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (funded by the German Research Foundation; FZT 118, S.A.B.).Global biodiversity assessments have highlighted land-use change as a key driver of biodiversity change. However, there is little empirical evidence of how habitat transformations such as forest loss and gain are reshaping biodiversity over time. We quantified how change in forest cover has influenced temporal shifts in populations and ecological assemblages from 6090 globally distributed time series across six taxonomic groups. We found that local-scale increases and decreases in abundance, species richness, and temporal species replacement (turnover) were intensified by as much as 48% after forest loss. Temporal lags in population- and assemblage-level shifts after forest loss extended up to 50 years and increased with species’ generation time. Our findings that forest loss catalyzes population and biodiversity change emphasize the complex biotic consequences of land-use change.PostprintPeer reviewe

The spatial sensitivity of the spectral diversity–biodiversity relationship: an experimental test in a prairie grassland

Remote sensing has been used to detect plant biodiversity in a range of ecosystems based on the varying spectral properties of different species or functional groups. However, the most appropriate spatial resolution necessary to detect diversity remains unclear. At coarse resolution, differences among spectral patterns may be too weak to detect. In contrast, at fine resolution, redundant information may be introduced. To explore the effect of spatial resolution, we studied the scale dependence of spectral diversity in a prairie ecosystem experiment at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Our study involved a scaling exercise comparing synthetic pixels resampled from high-resolution images within manipulated diversity treatments. Hyperspectral data were collected using several instruments on both ground and airborne platforms. We used the coefficient of variation (CV) of spectral reflectance in space as the indicator of spectral diversity and then compared CV at different scales ranging from 1 mm2 to 1 m2 to conventional biodiversity metrics, including species richness, Shannon’s index, Simpson’s index, phylogenetic species variation, and phylogenetic species evenness. In this study, higher species richness plots generally had higher CV. CV showed higher correlations with Shannon’s index and Simpson’s index than did species richness alone, indicating evenness contributed to the spectral diversity. Correlations with species richness and Simpson’s index were generally higher than with phylogenetic species variation and evenness measured at comparable spatial scales, indicating weaker relationships between spectral diversity and phylogenetic diversity metrics than with species diversity metrics. High resolution imaging spectrometer data (1 mm2 pixels) showed the highest sensitivity to diversity level. With decreasing spatial resolution, the difference in CV between diversity levels decreased and greatly reduced the optical detectability of biodiversity. The optimal pixel size for distinguishing a diversity in these prairie plots appeared to be around 1 mm to 10 cm, a spatial scale similar to the size of an individual herbaceous plant. These results indicate a strong scaledependence of the spectral diversity-biodiversity relationships, with spectral diversity best able to detect a combination of species richness and evenness, and more weakly detecting phylogenetic diversity. These findings can be used to guide airborne studies of biodiversity and develop more effective large-scale biodiversity sampling methods