Widespread shifts in body size within populations and assemblages

Biotic responses to global change include directional shifts in organismal traits. Body size, an integrative trait that determines demographic rates and ecosystem functions, is thought to be shrinking in the Anthropocene. Here, we assessed the prevalence of body size change in six taxon groups across 5025 assemblage time series spanning 1960 to 2020. Using the Price equation to partition this change into within-species body size versus compositional changes, we detected prevailing decreases in body size through time driven primarily by fish, with more variable patterns in other taxa. We found that change in assemblage composition contributes more to body size changes than within-species trends, but both components show substantial variation in magnitude and direction. The biomass of assemblages remains quite stable as decreases in body size trade off with increases in abundance.

Biodiversity time series are biased towards increasing species richness in changing environments

The discrepancy between global loss and local constant species richness has led to debates over data quality, systematic biases in monitoring programmes and the adequacy of species richness to capture changes in biodiversity. We show that, more fundamentally, null expectations of stable richness can be wrong, despite independent yet equal colonization and extinction. We analysed fish and bird time series and found an overall richness increase. This increase reflects a systematic bias towards an earlier detection of colonizations than extinctions. To understand how much this bias influences richness trends, we simulated time series using a neutral model controlling for equilibrium richness and temporal autocorrelation (that is, no trend expected). These simulated time series showed significant changes in richness, highlighting the effect of temporal autocorrelation on the expected baseline for species richness changes. The finite nature of time series, the long persistence of declining populations and the potential strong dispersal limitation probably lead to richness changes when changing conditions promote compositional turnover. Temporal analyses of richness should incorporate this bias by considering appropriate neutral baselines for richness changes. Absence of richness trends over time, as previously reported, can actually reflect a negative deviation from the positive biodiversity trend expected by default.

Some species flourish when many do not: a pattern in data on ecological communities

Patterns in species × sample tables of communities depend above all on the organisms of the data sets and the conditions involved. Patterns that surpass individual sets are of special interest. Our question, looking for a shared pattern in 12 sets, is if relative abundances among species are independent of the sample, or formulated alternatively, if species have abundances that are correlated with total abundances over samples. For exploration we study the overdispersion/aggregation of the data. A relatively high variation in the total abundances of samples is noticed, indicating an effect of environmental variation. Overdispersion imposes constraints on the accommodation of relatively high abundance values to samples with a relatively low total abundance. The null hypothesis of ‘no association’ is modelled by permutation/resampling of the data at the level of the individual. A correlation study of actual and permuted sets is performed. All actual sets contain a significant number of species that defy our question. These species flourish when many do not. The relation of our question with issues in theoretical ecology, such as the assumption of a neutral effect of environmental conditions and/or of neutral characteristics of species, is discussed.

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

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.

The geography of biodiversity change in marine and terrestrial assemblages

Human activities are fundamentally altering biodiversity. Projections of declines at the global scale are contrasted by highly variable trends at local scales, suggesting that biodiversity change may be spatially structured. Here, we examined spatial variation in species richness and composition change using more than 50,000 biodiversity time series from 239 studies and found clear geographic variation in biodiversity change. Rapid compositional change is prevalent, with marine biomes exceeding and terrestrial biomes trailing the overall trend. Assemblage richness is not changing on average, although locations exhibiting increasing and decreasing trends of up to about 20% per year were found in some marine studies. At local scales, widespread compositional reorganization is most often decoupled from richness change, and biodiversity change is strongest and most variable in the oceans.

Site-selection bias and apparent population declines in long-term studies

Detecting population declines is a critical task for conservation biology. Logistical difficulties and the spatiotemporal variability of populations make estimation of population declines difficult. For statistical reasons, estimates of population decline may be biased when study sites are chosen based on abundance of the focal species. In this situation, apparent population declines are likely to be detected even if there is no decline. This site-selection bias is mentioned in the literature but is not well known. We used simulations and real population data to examine the effects of site-selection biases on inferences about population trends. We used a left-censoring method to detect population-size patterns consistent with site-selection bias. The site-selection bias is an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis. Article impact statement: Estimates of population declines are biased if studies begin in large populations, and time-series data show a signature of such an effect.

BioTIME: A database of biodiversity time series for the Anthropocene

MOTIVATION

The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.

MAIN TYPES OF VARIABLES INCLUDED

The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.

SPATIAL LOCATION AND GRAIN

BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2).

TIME PERIOD AND GRAIN

BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.

MAJOR TAXA AND LEVEL OF MEASUREMENT

BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

SOFTWARE FORMAT

.csv and .SQL.

Quantifying long-term plant community dynamics with movement models: implications for ecological resilience

Quantification of rates and patterns of community dynamics is central for understanding the organization and function of ecosystems. These insights may support a greater empirical understanding of ecological resilience, and the application of resilience concepts toward ecosystem management. Distinct types of dynamics in natural communities can be used to interpret and apply resilience concepts, but quantitative methods that can systematically distinguish among them are needed. We develop a quantitative method to analyze long-term records of plant community dynamics using principles of movement ecology. We analyzed dissimilarity of species composition through time with linear and nonlinear statistical models to assign community change to four classes of movement trajectories. Compositional change in each sampled plot through time was classified into four classes, stability, abrupt nonlinear change, transient reversible change, and gradual linear drift, each representing a different aspect of ecological resilience. These competing models were evaluated based on estimated coefficients, goodness of fit, and parsimony. We tested our method's accuracy and robustness through simulations, or the ability to distinguish among trajectories and classify them correctly. We simulated 16,000 trajectories of four types, of which 94-100% were correctly classified. Next, we analyzed 13 long-term vegetation records from North American grasslands (annual grasslands with warm-season and cool-season communities, shortgrass, mixedgrass, and tallgrass prairies, and sagebrush steppe), and a record of primary succession at Mt. St. Helens volcano. Collectively, we analyzed 14,647 observations from 775 plots, between 1915 and 2012. Dynamics could be reliably assigned for 705 plots (91%), and overall statistical fit was high (goodness of fit, 0.77 ± 0.15 SD). Among the perennial grasslands, stability was most common (44% of all plots), followed by gradual linear (22%), abrupt nonlinear (17%), and reversible (6%) change. Among annual grasslands, abrupt nonlinear shifts (33%) were more common in the warm-season community than in the cool-season (20%). As expected, abrupt nonlinear change was common during primary succession (51%) while reversible change was rare (3%). Generally, reversible dynamics often required 2-3 decades. Analysis of long-term community change, or trajectories, with principles of movement ecology provides a quantitative basis to compare and interpret ecological resilience within and among ecosystems.

Community-level regulation of temporal trends in biodiversity

Many theoretical models of community dynamics predict that species richness (S) and total abundance (N) are regulated in their temporal fluctuations. We present novel evidence for widespread regulation of biodiversity. For 59 plant and animal assemblages from around the globe monitored annually for a decade or more, the majority exhibited regulated fluctuations compared to the null hypothesis of an unconstrained random walk. However, there was little evidence for statistical artifacts, regulation driven by correlations with average annual temperature, or local-scale compensatory fluctuations in S or N. In the absence of major environmental perturbations, such as urbanization or cropland transformation, species richness and abundance may be buffered and exhibit some resilience in their temporal trajectories. These results suggest that regulatory processes are occurring despite unprecedented environmental change, highlighting the need for community-level assessment of biodiversity trends, as well as extensions of existing theory to address open source pools and shifting environmental conditions.

The EcoData retriever: improving access to existing ecological data

Ecological research relies increasingly on the use of previously collected data. Use of existing datasets allows questions to be addressed more quickly, more generally, and at larger scales than would otherwise be possible. As a result of large-scale data collection efforts, and an increasing emphasis on data publication by journals and funding agencies, a large and ever-increasing amount of ecological data is now publicly available via the internet. Most ecological datasets do not adhere to any agreed-upon standards in format, data structure or method of access. Some may be broken up across multiple files, stored in compressed archives, and violate basic principles of data structure. As a result acquiring and utilizing available datasets can be a time consuming and error prone process. The EcoData Retriever is an extensible software framework which automates the tasks of discovering, downloading, and reformatting ecological data files for storage in a local data file or relational database. The automation of these tasks saves significant time for researchers and substantially reduces the likelihood of errors resulting from manual data manipulation and unfamiliarity with the complexities of individual datasets.

An experimental test of the response of macroecological patterns to altered species interactions

Macroecological patterns such as the species-area relationship (SAR), the species-abundance distribution (SAD), and the species-time relationship (STR) exhibit regular behavior across ecosystems and taxa. However, determinants of these patterns remain poorly understood. Emerging theoretical frameworks for macroecology attempt to understand this regularity by ignoring detailed ecological interactions and focusing on the influence of a small number of community-level state variables, such as species richness and total abundance, on these patterns. We present results from a 15-year rodent removal experiment evaluating the response of three different macroecological patterns in two distinct annual plant communities (summer and winter) to two levels of manipulated seed predation. Seed predator manipulations significantly impacted species composition on all treatments in both communities, but did not significantly impact richness, community abundance, or macroecological patterns in most cases. How'ever, winter community abundance and richness responded significantly to the removal of all rodents. Changes in richness and abundance were coupled with significant shifts in macroecological patterns (SADs, SARs, and STRs). Because altering species interactions only impacted macroecological patterns when the state variables of abundance and richness also changed, we suggest that, in this system, local-scale processes primarily act indirectly through these properties to determine macroecological patterns.

Quantifying temporal change in biodiversity: challenges and opportunities

Growing concern about biodiversity loss underscores the need to quantify and understand temporal change. Here, we review the opportunities presented by biodiversity time series, and address three related issues: (i) recognizing the characteristics of temporal data; (ii) selecting appropriate statistical procedures for analysing temporal data; and (iii) inferring and forecasting biodiversity change. With regard to the first issue, we draw attention to defining characteristics of biodiversity time series--lack of physical boundaries, uni-dimensionality, autocorrelation and directionality--that inform the choice of analytic methods. Second, we explore methods of quantifying change in biodiversity at different timescales, noting that autocorrelation can be viewed as a feature that sheds light on the underlying structure of temporal change. Finally, we address the transition from inferring to forecasting biodiversity change, highlighting potential pitfalls associated with phase-shifts and novel conditions.

Integrating spatial and temporal approaches to understanding species richness

Understanding species richness patterns represents one of the most fundamental problems in ecology. Most research in this area has focused on spatial gradients of species richness, with a smaller area of emphasis dedicated to understanding the temporal dynamics of richness. However, few attempts have been made to understand the linkages between the spatial and temporal patterns related to richness. Here, we argue that spatial and temporal richness patterns and the processes that drive them are inherently linked, and that our understanding of richness will be substantially improved by considering them simultaneously. The species-time-area relationship provides a case in point: successful description of the empirical spatio-temporal pattern led to a rapid development and testing of new theories. Other areas of research on species richness could also benefit from an explicitly spatio-temporal approach, and we suggest future directions for understanding the processes common to these two traditionally isolated fields of research.