Search for: All records

Abstract A fundamental pattern in ecology is that smaller organisms are more abundant than larger organisms. This pattern is known as the individual size distribution (ISD), which is the frequency distribution of all individual body sizes in an ecosystem.The ISD is described by a power law and a major goal of size spectra analyses is to estimate the exponent of the power law,λ. However, while numerous methods have been developed to do this, they have focused almost exclusively on estimatingλfrom single samples.Here, we develop an extension of the truncated Pareto distribution within the probabilistic modelling language Stan. We use it to estimate multipleλs simultaneously in a hierarchical modelling approach.The most important result is the ability to examine hypotheses related to size spectra, including the assessment of fixed and random effects, within a single Bayesian generalized mixed model. While the example here uses size spectra, the technique can also be generalized to any data that follow a power law distribution. 

Abstract Aquatic invasive species (AIS) threaten biodiversity and ecosystem services around the world, but their management has been hampered by the lack of quantifiable control targets. The introduction of Silver Carp (Hypophthalmichthys molitrix) throughout the mid‐western United States epitomizes both the impacts of AIS and the need for quantitative control targets. Silver Carp are large‐bodied planktivores that compete with native planktivores, which can cause cascading effects throughout the food web. Our study tested the threshold of abundance beyond which Silver Carp alter fish assemblage structure. We used a community size spectra (CSS) approach to evaluate fish community size structure across temporal and spatial gradients of Silver Carp abundances. We hypothesized that Silver Carp would flatten the size spectra slope because they are large‐bodied and feed at a low trophic position. Electrofishing data were obtained for the La Grange Pool of the Illinois River (1994–2021) and for six pools of the Ohio River (2015–2020). Results supported our hypothesis, showing a 98% probability that the relative biomass of Silver Carp is positively related to the CSS slope (resulting in “flattening”). This pattern was strongest in the Illinois River, where Silver Carp made up >30% of fish assemblage biomass in recent years. The pattern was weakest in the Ohio River (78% probability of a positive relationship) where Silver Carp rarely exceeded 20% of total fish biomass. Subsequent changepoint models indicated that a Silver Carp relative biomass of ~24% represents a threshold below which negative food web impacts should be minimized. Our study demonstrates a clear shift in fish community size structure following invasion by Silver Carp and suggests that pre‐invasion CSS slopes may serve as a restoration target. It also illustrates the benefits of CSS to guide Silver Carp and other AIS management. 

Abstract Individual body size distributions (ISD) within communities are remarkably consistent across habitats and spatiotemporal scales and can be represented by size spectra, which are described by a power law. The focus of size spectra analysis is to estimate the exponent () of the power law. A common application of size spectra studies is to detect anthropogenic pressures.Many methods have been proposed for estimating most of which involve binning the data, counting the abundance within bins, and then fitting an ordinary least squares regression in log–log space. However, recent work has shown that binning procedures return biased estimates of compared to procedures that directly estimate using maximum likelihood estimation (MLE). While it is clear that MLE produces less biased estimates of site‐specificλ's, it is less clear how this bias affects the ability to test for changes inλacross space and time, a common question in the ecological literature.Here, we used simulation to compare the ability of two normalised binning methods (equal logarithmic and log₂bins) and MLE to (1) recapture known values of , and (2) recapture parameters in a linear regression measuring the change in across a hypothetical environmental gradient. We also compared the methods using two previously published body size datasets across a natural temperature gradient and an anthropogenic pollution gradient.Maximum likelihood methods always performed better than common binning methods, which demonstrated consistent bias depending on the simulated values of . This bias carried over to the regressions, which were more accurate when was estimated using MLE compared to the binning procedures. Additionally, the variance in estimates using MLE methods is markedly reduced when compared to binning methods.The error induced by binning methods can be of similar magnitudes as the variation previously published in experimental and observational studies, bringing into question the effect sizes of previously published results. However, while the methods produced different regression slope estimates, they were in qualitative agreement on the sign of those slopes (i.e. all negative or all positive). Our results provide further support for the direct estimation of and its relative variation across environmental gradients using MLE over the more common methods of binning. 

The study explores the individual size distribution (ISD) pattern in ecological communities, characterized by a negative correlation between individual body size and abundance (N ∼ M^λ). The parameter λ denotes the rate of decline in relative abundance from small to large individuals. Despite known influences of temperature and resource availability on body size, their effects on λ remain diverse. Leveraging data from 2.4 million individual body sizes in continental freshwater streams, the research the hypothesis that λ varies as a function of temperature and resource supply. Surprisingly, despite varied environmental conditions and complete species turnover, minimal variation in λ (mean = −1.2, sd = 0.04) was observed, with no discernible impact from temperature or resource supply. The unexpected λ value of −1.2 suggests a higher-than-expected relative abundance of large individuals, challenging assumptions of metabolic scaling at 0.75 and implying large subsidy inputs to large predators. Simulation and mesocosm experiments support a metabolic scaling coefficient of ∼0.4 for freshwater macroinvertebrates. The findings underscore remarkable consistency of individual size distributions in freshwater streams, likely driven by shallow metabolic scaling and large subsidies to large consumers. 

Abstract AimCommunities contain more individuals of small species and fewer individuals of large species. According to the ‘metabolic theory of ecology’, the relationship of log mean abundance with log mean body size across communities should exhibit a slope of −3/4 that is invariant across environmental conditions. Here, we investigate whether this slope is indeed invariant or changes systematically across gradients in temperature, resource availability and predation pressure. Location1048 lakes across the USA. Time Period2012. Major Taxa StudiedPhytoplankton. ResultsWe found that the size–abundance relationship across all sampled phytoplankton communities was significantly lower than −3/4 and near −1 overall. More importantly, we found strong evidence that the environment affects the slope: it varies between −0.33 and −0.93 across interacting gradients of temperature, resource (phosphorus) supply and zooplankton predation pressure. Therefore, phytoplankton communities have orders of magnitude more small or large cells depending on environmental conditions across geographical locations. ConclusionOur results emphasise the importance of the environmental factors' effect on macroecological patterns that arise through physiological and ecological processes. An investigation of the mechanisms underlying the link between individual energetics constrain and macroecological patterns would allow to predict how global warming and changes in nutrients will alter large‐scale ecological patterns in the future. 

Abstract Bayesian data analysis is increasingly used in ecology, but prior specification remains focused on choosing non‐informative priors (e.g., flat or vague priors). One barrier to choosing more informative priors is that priors must be specified on model parameters (e.g., intercepts, slopes, and sigmas), but prior knowledge often exists on the level of the response variable. This is particularly true for common models in ecology, like generalized linear mixed models that have a link function and potentially dozens of parameters, each of which needs a prior distribution. We suggest that this difficulty can be overcome by simulating from the prior predictive distribution and visualizing the results on the scale of the response variable. In doing so, some common choices for non‐informative priors on parameters can easily be seen to produce biologically impossible values of response variables. Such implications of prior choices are difficult to foresee without visualization. We demonstrate a workflow for prior selection using simulation and visualization with two ecological examples (predator–prey body sizes and spider responses to food competition). This approach is not new, but its adoption by ecologists will help to better incorporate prior information in ecological models, thereby maximizing one of the benefits of Bayesian data analysis. 

Abstract Parameters describing the negative relationship between abundance and body size within ecological communities provide a summary of many important biological processes. While it is considered to be one of the few consistent patterns in ecology, spatiotemporal variation of this relationship across continental scale temperature gradients is unknown. Using a database of stream communities collected across North America (18–68°N latitude, −4 to 25°C mean annual air temperature) over 3 years, we constructed 160 individual size distribution (ISD) relationships (i.e. abundance size spectra). The exponent parameter describing ISD’s decreased (became steeper) with increasing mean annual temperature, with median slopes varying by ~0.2 units across the 29°C temperature gradient. In addition, total community biomass increased with increasing temperatures, contrary with theoretical predictions. Our study suggests conservation of ISD relationships in streams across broad natural environmental gradients. This supports the emerging use of size‐spectra deviations as indicators of fundamental changes to the structure and function of ecological communities.