BioTIME: A database of biodiversity time series for the Anthropocene

We need to talk about nonprobability samples

In most circumstances, probability sampling is the only way to ensure unbiased inference about population quantities where a complete census is not possible. As we enter the era of 'big data', however, nonprobability samples, whose sampling mechanisms are unknown, are undergoing a renaissance. We explain why the use of nonprobability samples can lead to spurious conclusions, and why seemingly large nonprobability samples can be (effectively) very small. We also review some recent controversies surrounding the use of nonprobability samples in biodiversity monitoring. These points notwithstanding, we argue that nonprobability samples can be useful, provided that their limitations are assessed, mitigated where possible and clearly communicated. Ecologists can learn much from other disciplines on each of these fronts.

Challenges and opportunities for using natural history collections to estimate insect population trends

Natural history collections (NHC) provide a wealth of information that can be used to understand the impacts of global change on biodiversity. As such, there is growing interest in using NHC data to estimate changes in species' distributions and abundance trends over historic time horizons when contemporary survey data are limited or unavailable. However, museum specimens were not collected with the purpose of estimating population trends and thus can exhibit spatiotemporal and collector-specific biases that can impose severe limitations to using NHC data for evaluating population trajectories. Here we review the challenges associated with using museum records to track long-term insect population trends, including spatiotemporal biases in sampling effort and sparse temporal coverage within and across years. We highlight recent methodological advancements that aim to overcome these challenges and discuss emerging research opportunities. Specifically, we examine the potential of integrating museum records and other contemporary data sources (e.g. collected via structured, designed surveys and opportunistic citizen science programs) in a unified analytical framework that accounts for the sampling biases associated with each data source. The emerging field of integrated modelling provides a promising framework for leveraging the wealth of collections data to accurately estimate long-term trends of insect populations and identify cases where that is not possible using existing data sources.

A reconstruction of parasite burden reveals one century of climate-associated parasite decline

Long-term data allow ecologists to assess trajectories of population abundance. Without this context, it is impossible to know whether a taxon is thriving or declining to extinction. For parasites of wildlife, there are few long-term data-a gap that creates an impediment to managing parasite biodiversity and infectious threats in a changing world. We produced a century-scale time series of metazoan parasite abundance and used it to test whether parasitism is changing in Puget Sound, United States, and, if so, why. We performed parasitological dissection of fluid-preserved specimens held in natural history collections for eight fish species collected between 1880 and 2019. We found that parasite taxa using three or more obligately required host species-a group that comprised 52% of the parasite taxa we detected-declined in abundance at a rate of 10.9% per decade, whereas no change in abundance was detected for parasites using one or two obligately required host species. We tested several potential mechanisms for the decline in 3+-host parasites and found that parasite abundance was negatively correlated with sea surface temperature, diminishing at a rate of 38% for every 1 °C increase. Although the temperature effect was strong, it did not explain all variability in parasite burden, suggesting that other factors may also have contributed to the long-term declines we observed. These data document one century of climate-associated parasite decline in Puget Sound-a massive loss of biodiversity, undetected until now.

Observed and dark diversity dynamics over millennial time scales: fast life-history traits linked to expansion lags of plants in northern Europe

Global change drivers (e.g. climate and land use) affect the species and functional traits observed in a local site but also its dark diversity-the set of species and traits locally suitable but absent. Dark diversity links regional and local scales and, over time, reveals taxa under expansion lags by depicting the potential biodiversity that remains suitable but is absent locally. Since global change effects on biodiversity are both spatially and temporally scale dependent, examining long-term temporal dynamics in observed and dark diversity would be relevant to assessing and foreseeing biodiversity change. Here, we used sedimentary pollen data to examine how both taxonomic and functional observed and dark diversity changed over the past 14 500 years in northern Europe. We found that taxonomic and functional observed and dark diversity increased over time, especially after the Late Glacial and during the Late Holocene. However, dark diversity dynamics revealed expansion lags related to species' functional characteristics (dispersal limitation and stress intolerance) and an extensive functional redundancy when compared to taxa in observed diversity. We highlight that assessing observed and dark diversity dynamics is a promising tool to examine biodiversity change across spatial scales, its possible causes, and functional consequences.

The dominance-diversity dilemma in animal conservation biology

The alteration of environmental conditions has two major outcomes on the demographics of living organisms: population decline of the common species and extinction of the rarest ones. Halting the decline of abundant species as well as the erosion of biodiversity require solutions that may be mismatched, despite being rooted in similar causes. In this study, we demonstrate how rank abundance distribution (RAD) models are mathematical representations of a dominance-diversity dilemma. Across 4,375 animal communities from a range of taxonomic groups, we found that a reversed RAD model correctly predicts species richness, based solely on the relative dominance of the most abundant species in a community and the total number of individuals. Overall, predictions from this RAD model explained 69% of the variance in species richness, compared to 20% explained by simply regressing species richness on the relative dominance of the most abundant species. Using the reversed RAD model, we illustrate how species richness is co-limited by the total abundance of a community and the relative dominance of the most common species. Our results highlight an intrinsic trade-off between species richness and dominance that is present in the structure of RAD models and real-world animal community data. This dominance-diversity dilemma suggests that withdrawing individuals from abundant populations might contribute to the conservation of species richness. However, we posit that the positive effect of harvesting on biodiversity is often offset by exploitation practices with negative collateral consequences, such as habitat destruction or species bycatches.

The ecological consequences of the timing of extreme climate events

Climate change is increasing the intensity, duration, and frequency of extreme climate events (ECEs). These ECEs can have major ecological consequences, e.g., changing nutrient flows, causing extirpation, and altering organismal development. Many ECEs are discrete events that occur at distinctive times during the biological processes they impact. Because of this, ECEs are likely to have differing ecological impacts depending on when they happen, yet we lack on studies that explore how the ecological consequences of ECEs vary with when they occur. Drawing upon evidence from physiological, population, and community ecology, and previous work on ecological disturbances, we suggest that the consequences of ECEs will be sensitive to when they occur. We illustrate the importance of timing by showing how the effects of an ECE could vary depending on when it occurs through the course of (1) organismal ontogeny, (2) population dynamics, and (3) community assembly. An enhanced focus on the timing of extreme weather in climate change research will reveal how and when ECEs are altering ecosystems, possible mechanisms behind these impacts, and what ecosystems or species are most vulnerable to ECEs, helping us to make more informed predictions about the ecological consequences of climate change.

Plankton response to global warming is characterized by non-uniform shifts in assemblage composition since the last ice age

Biodiversity is expected to change in response to future global warming. However, it is difficult to predict how species will track the ongoing climate change. Here we use the fossil record of planktonic foraminifera to assess how biodiversity responded to climate change with a magnitude comparable to future anthropogenic warming. We compiled time series of planktonic foraminifera assemblages, covering the time from the last ice age across the deglaciation to the current warm period. Planktonic foraminifera assemblages shifted immediately when temperature began to rise at the end of the last ice age and continued to change until approximately 5,000 years ago, even though global temperature remained relatively stable during the last 11,000 years. The biotic response was largest in the mid latitudes and dominated by range expansion, which resulted in the emergence of new assemblages without analogues in the glacial ocean. Our results indicate that the plankton response to global warming was spatially heterogeneous and did not track temperature change uniformly over the past 24,000 years. Climate change led to the establishment of new assemblages and possibly new ecological interactions, which suggests that current anthropogenic warming may lead to new, different plankton community composition.

The direct drivers of recent global anthropogenic biodiversity loss

Effective policies to halt biodiversity loss require knowing which anthropogenic drivers are the most important direct causes. Whereas previous knowledge has been limited in scope and rigor, here we statistically synthesize empirical comparisons of recent driver impacts found through a wide-ranging review. We show that land/sea use change has been the dominant direct driver of recent biodiversity loss worldwide. Direct exploitation of natural resources ranks second and pollution third; climate change and invasive alien species have been significantly less important than the top two drivers. The oceans, where direct exploitation and climate change dominate, have a different driver hierarchy from land and fresh water. It also varies among types of biodiversity indicators. For example, climate change is a more important driver of community composition change than of changes in species populations. Stopping global biodiversity loss requires policies and actions to tackle all the major drivers and their interactions, not some of them in isolation.

Herbivore species coexistence in changing rangeland ecosystems: First high resolution national open-source and open-access ensemble models for Iceland

Rangeland ecosystems are changing worldwide with the abandonment of extensive pastoralism practices and greater interest for species coexistence. However, the lack of compiled data on current changes in the abundance and distribution of herbivores challenges rangeland management decisions. Here we gathered and made available for the first time the most extensive set of occurrence data for rangeland herbivores in Iceland in an Open Access framework for transparent and repeatable science-based decisions. We mapped fine scale species distribution overlap to identify areas at risk for wildlife-livestock conflict and overgrazing. Nationwide and long term (1861-2021) occurrence data from 8 independent datasets were used alongside 11 predictor raster layers ("Big Data") to data mine and map the distribution of the domestic sheep (Ovis aries), feral reindeer (Rangifer tarandus tarandus), pink-footed geese (Anser brachyrhynchus), and rock ptarmigan (Lagopus muta islandorum) over the country during the summer. Using algorithms of Maxent in R, RandomForest, TreeNet (stochastic gradient boosting) and MARS (Splines) in Minitab-SPM 8.3, we computed 1 km pixel predictions from machine learning-based ensemble models. Our high-resolution models were tested with alternative datasets, and Area Under the Curve (AUC) values that indicated good (reindeer: 0.8817 and rock ptarmigan: 0.8844) to high model accuracy (sheep: 0.9708 and pink-footed goose: 0.9143). Whenever possible, source data and models are made available online and described with ISO-compliant metadata. Our results illustrate that sheep and pink-footed geese have the greatest overlap in distribution with potential implication for wildlife-livestock conflicts and continued ecosystem degradation even under diminishing livestock abundance at higher elevation. These nationwide models and data are a global asset and a first step in making available the best data for science-based sustainable decision-making about national herbivores affecting species coexistence and environmental management.

More losses than gains during one century of plant biodiversity change in Germany

Long-term analyses of biodiversity data highlight a 'biodiversity conservation paradox': biological communities show substantial species turnover over the past century^1,2, but changes in species richness are marginal^1,3-5. Most studies, however, have focused only on the incidence of species, and have not considered changes in local abundance. Here we asked whether analysing changes in the cover of plant species could reveal previously unrecognized patterns of biodiversity change and provide insights into the underlying mechanisms. We compiled and analysed a dataset of 7,738 permanent and semi-permanent vegetation plots from Germany that were surveyed between 2 and 54 times from 1927 to 2020, in total comprising 1,794 species of vascular plants. We found that decrements in cover, averaged across all species and plots, occurred more often than increments; that the number of species that decreased in cover was higher than the number of species that increased; and that decrements were more equally distributed among losers than were gains among winners. Null model simulations confirmed that these trends do not emerge by chance, but are the consequence of species-specific negative effects of environmental changes. In the long run, these trends might result in substantial losses of species at both local and regional scales. Summarizing the changes by decade shows that the inequality in the mean change in species cover of losers and winners diverged as early as the 1960s. We conclude that changes in species cover in communities represent an important but understudied dimension of biodiversity change that should more routinely be considered in time-series analyses.

ReSurveyGermany: Vegetation-plot time-series over the past hundred years in Germany

Vegetation-plot resurvey data are a main source of information on terrestrial biodiversity change, with records reaching back more than one century. Although more and more data from re-sampled plots have been published, there is not yet a comprehensive open-access dataset available for analysis. Here, we compiled and harmonised vegetation-plot resurvey data from Germany covering almost 100 years. We show the distribution of the plot data in space, time and across habitat types of the European Nature Information System (EUNIS). In addition, we include metadata on geographic location, plot size and vegetation structure. The data allow temporal biodiversity change to be assessed at the community scale, reaching back further into the past than most comparable data yet available. They also enable tracking changes in the incidence and distribution of individual species across Germany. In summary, the data come at a level of detail that holds promise for broadening our understanding of the mechanisms and drivers behind plant diversity change over the last century.

Matches and mismatches between the global distribution of major food crops and climate suitability

Over the course of history, humans have moved crops from their regions of origin to new locations across the world. The social, cultural and economic drivers of these movements have generated differences not only between current distributions of crops and their climatic origins, but also between crop distributions and climate suitability for their production. Although these mismatches are particularly important to inform agricultural strategies on climate change adaptation, they have, to date, not been quantified consistently at the global level. Here, we show that the relationships between the distributions of 12 major food crops and climate suitability for their yields display strong variation globally. After investigating the role of biophysical, socio-economic and historical factors, we report that high-income world regions display a better match between crop distribution and climate suitability. In addition, although crops are farmed predominantly in the same climatic range as their wild progenitors, climate suitability is not necessarily higher there, a pattern that reflects the legacy of domestication history on current crop distribution. Our results reveal how far the global distribution of major crops diverges from their climatic optima and call for greater consideration of the multiple dimensions of the crop socio-ecological niche in climate change adaptive strategies.

Simple statistical models can be sufficient for testing hypotheses with population time-series data

Time-series data offer wide-ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information about species detectability that is often unavailable. We propose that in many cases, simpler models are adequate for testing hypotheses. We consider three relatively simple regression models for time series, using simulated and empirical (fish and mammal) datasets. Model A is a conventional generalized linear model of abundance, model B adds a temporal autoregressive term, and model C uses an estimate of population growth rate as a response variable, with the option of including a term for density dependence. All models can be fit using Bayesian and non-Bayesian methods. Simulation results demonstrated that model C tended to have greater support for long-lived, lower-fecundity organisms (K life-history strategists), while model A, the simplest, tended to be supported for shorter-lived, high-fecundity organisms (r life-history strategists). Analysis of real-world fish and mammal datasets found that models A, B, and C each enjoyed support for at least some species, but sometimes yielded different insights. In particular, model C indicated effects of predictor variables that were not evident in analyses with models A and B. Bayesian and frequentist models yielded similar parameter estimates and performance. We conclude that relatively simple models are useful for testing hypotheses about the factors that influence abundance in time-series data, and can be appropriate choices for datasets that lack the information needed to fit more complicated models. When feasible, we advise fitting datasets with multiple models because they can provide complementary information.

Invasion impacts and dynamics of a European-wide introduced species

Globalization has led to the introduction of thousands of alien species worldwide. With growing impacts by invasive species, understanding the invasion process remains critical for predicting adverse effects and informing efficient management. Theoretically, invasion dynamics have been assumed to follow an "invasion curve" (S-shaped curve of available area invaded over time), but this dynamic has lacked empirical testing using large-scale data and neglects to consider invader abundances. We propose an "impact curve" describing the impacts generated by invasive species over time based on cumulative abundances. To test this curve's large-scale applicability, we used the data-rich New Zealand mud snail Potamopyrgus antipodarum, one of the most damaging freshwater invaders that has invaded almost all of Europe. Using long-term (1979-2020) abundance and environmental data collected across 306 European sites, we observed that P. antipodarum abundance generally increased through time, with slower population growth at higher latitudes and with lower runoff depth. Fifty-nine percent of these populations followed the impact curve, characterized by first occurrence, exponential growth, then long-term saturation. This behaviour is consistent with boom-bust dynamics, as saturation occurs due to a rapid decline in abundance over time. Across sites, we estimated that impact peaked approximately two decades after first detection, but the rate of progression along the invasion process was influenced by local abiotic conditions. The S-shaped impact curve may be common among many invasive species that undergo complex invasion dynamics. This provides a potentially unifying approach to advance understanding of large-scale invasion dynamics and could inform timely management actions to mitigate impacts on ecosystems and economies.

ROBITT: A tool for assessing the risk-of-bias in studies of temporal trends in ecology

Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete 'risk-of-bias' assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology.We introduce ROBITT, a structured tool for assessing the 'Risk-Of-Bias In studies of Temporal Trends in ecology'. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken.Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis.We propose that researchers should be strongly encouraged to include a ROBITT assessment when publishing studies of biodiversity trends, especially when using aggregated data. This will help researchers to structure their thinking, clearly acknowledge potential sampling issues, highlight where expert consultation is required and provide an opportunity to describe data checks that might go unreported. ROBITT will also enable reviewers, editors and readers to establish how well research conclusions are supported given a dataset combined with some analytical approach. In turn, it should strengthen evidence-based policy and practice, reduce differing interpretations of data and provide a clearer picture of the uncertainties associated with our understanding of reality.

Urbanisation and land-cover change affect functional, but not compositional turnover of bird communities

Land-use and land-cover change strongly affect biodiversity patterns and are assumed to be growing threats in the future. Particularly increasing urbanisation may affect species turnover and functional composition of biological communities. This study aimed to assess the characteristics of land-cover change in a medium-sized urban municipality from 2011 to 2018, and the effects of urbanisation on avian species- and functional diversity. The study was performed in Trondheim (Norway), using local land-cover maps and GBIF bird species occurrence records. GLMMs were used to model species turnover as a function of urbanisation, and the probability of species appearance and disappearance based on urbanisation and species traits. The extent of bird species turnover within a municipality-wide 500 × 500m2 grid was not predicted by a changes in developed area, but the probability of disappearance and appearance of bird species varied with urbanisation and bird functional traits. Species associated with urban- or open areas showed a decreasing probability of disappearing and an increasing probability of appearing with increasing amount of developed area within grid cells. Similarly, granivorous species showed a decreasing probability of disappearing. Species feeding above ground-level showed positive responses to changes in land-cover. The probability of both appearance and disappearance, thus species turnover, increased with increasing longevity. Most functional groups respond negatively to increasing urbanisation, indicating a potential impoverishment of local avifauna with future land-cover modifications. Considering planned future land-cover changes within the municipality, the local avian communities are in danger of homogenisation. The recommendations for local management are to minimise conversion of vulnerable habitats, such as wetlands and woodlands, in particular if these are converted to developed area.

Analyzing dynamic species abundance distributions using generalized linear mixed models

Understanding the mechanisms of ecological community dynamics and how they could be affected by environmental changes is important. Population dynamic models have well known ecological parameters that describe key characteristics of species such as the effect of environmental noise and demographic variance on the dynamics, the long‐term growth rate, and strength of density regulation. These parameters are also central for detecting and understanding changes in communities of species; however, incorporating such vital parameters into models of community dynamics is challenging. In this paper, we demonstrate how generalized linear mixed models specified as intercept‐only models with different random effects can be used to fit dynamic species abundance distributions. Each random effect has an ecologically meaningful interpretation either describing general and species‐specific responses to environmental stochasticity in time or space, or variation in growth rate and carrying capacity among species. We use simulations to show that the accuracy of the estimation depends on the strength of density regulation in discrete population dynamics. The estimation of different covariance and population dynamic parameters, with corresponding statistical uncertainties, is demonstrated for case studies of fish and bat communities. We find that species heterogeneity is the main factor of spatial and temporal community similarity for both case studies.

Introducing the combined atlas framework for large-scale web-based data visualization: The GloNAF atlas of plant invasion

Large-scale biodiversity data, for example, on species distribution and richness information, are being mobilized and becoming available at an increasing rate. Interactive web applications like atlases have been developed to visualize available datasets and make them accessible to a wider audience. Web mapping tools are changing rapidly, and different underlying concepts have been developed to visualize datasets at a high cartographic standard.Here, we introduce the Combined Atlas Framework for the development of interactive web atlases for ecological data visualization. We combine two existing approaches: the five stages of the user-centred design approach for web mapping applications and the three U approach for interface success.Subsequently, we illustrate the use of this framework by developing the Atlas of Plant Invasions based on the Global Naturalized Alien Flora (GloNAF) database. This case study illustrates how the newly developed Combined Atlas Framework with a user-centred design philosophy can generate measurable success through communication with the target user group, iterative prototyping and competitive analysis of other existing web mapping approaches.The framework is useful in creating an atlas that employs user feedback to determine usability and utility features within an interactive atlas system. Finally, this framework will enable a better-informed development process of future visualization and dissemination of biodiversity data through web mapping applications and interactive atlases.

Parasite communities in English Sole (Parophrys vetulus) have changed in composition but not richness in the Salish Sea, Washington, USA since 1930

Earth is rapidly losing free-living species. Is the same true for parasitic species? To reveal temporal trends in biodiversity, historical data are needed, but often such data do not exist for parasites. Here, parasite communities of the past were reconstructed by identifying parasites in fluid-preserved specimens held in natural history collections. Approximately 2500 macroparasites were counted from 109 English Sole (Parophrys vetulus ) collected between 1930 and 2019 in the Salish Sea, Washington, USA. Alpha and beta diversity were measured to determine if and how diversity changed over time. Species richness of parasite infracommunities and community dispersion did not vary over time, but community composition of decadal component communities varied significantly over the study period. Community dissimilarity also varied: prior to the mid-20th century, parasites shifted in abundance in a seemingly stochastic manner and, after this time period, a canalization of community change was observed, where species' abundances began to shift in consistent directions. Further work is needed to elucidate potential drivers of these changes and to determine if these patterns are present in the parasite communities of other fishes of the Salish Sea.

Decadal trend of plankton community change and habitat shoaling in the Arctic gateway recorded by planktonic foraminifera

The Fram Strait plays a crucial role in regulating the heat and sea-ice dynamics in the Arctic. In response to the ongoing global warming, the marine biota of this Arctic gateway is experiencing significant changes with increasing advection of Atlantic species. The footprint of this 'Atlantification' has been identified in isolated observations across the plankton community, but a systematic, multi-decadal perspective on how regional climate change facilitates the invasion of Atlantic species and affects the ecology of the resident species is lacking. Here we evaluate a series of 51 depth-resolved plankton profiles collected in the Fram Strait during seven surveys between 1985 and 2015, using planktonic foraminifera as a proxy for changes in both the pelagic community composition and species vertical habitat depth. The time series reveals a progressive shift towards more Atlantic species, occurring independently of changes in local environmental conditions. We conclude that this trend is reflecting higher production of the Atlantic species in the Nordic Seas, from where they are advected into the Fram Strait. At the same time, we observe the ongoing extensive sea-ice export from the Arctic and associated cooling-induced decline in density and habitat shoaling of the subpolar Turborotalita quinqueloba, whereas the resident Neogloboquadrina pachyderma persists. As a result, the planktonic foraminiferal community and vertical structure in the Fram Strait shift to a new state, driven by both remote forcing of the Atlantic invaders and local climatic changes acting on the resident species. The strong summer export of Arctic sea ice has so far buffered larger plankton transformation. We predict that if the sea-ice export will decrease, the Arctic gateway will experience rapid restructuring of the pelagic community, even in the absence of further warming. Such a large change in the gateway region will likely propagate into the Arctic proper.

Variability in nearshore fish biodiversity indicators after a mining disaster in eastern Brazil

The rupture of the Fundão mining dam (Doce river basin, Brazil) caused a wide range of negative impacts. Yet, assemblage-level implications to estuarine and coastal fishes remain unclear, partly due to the lack of pre-disaster information. Based on monthly otter trawl surveys, we analyzed spatial and seasonal variability in univariate (total biomass, biomass of species vulnerable to exploitation, rarefied richness and evenness) and multivariate (species composition and trophic composition) indicators of fish biodiversity in the Doce river delta, eastern Brazil. We determined the independent and interactive effects of environmental, seasonal and spatial variables on species composition to test whether environmental alterations provoked by mine tailings could affect assemblage's organization. Most indicators present idiosyncratic spatiotemporal patterns, suggesting they have complementary roles in revealing changes in fish biodiversity. Environmental variables, including those affected by the Fundão dam collapse such as turbidity, dissolved oxygen and pH, were much more important than seasonal and spatial predictors in explaining the variation in fish species composition. These findings highlight the potential from mine tailings to disrupt local ichthyofauna and indicate a preponderant role of environmental conditions in assemblage structuring. Given the lack of data prior to rupture, our results may be used as a baseline against which to assess temporal trends in fish biodiversity relative to changes detected in less disturbed estuarine and coastal assemblages.

Global patterns in functional rarity of marine fish

Rare species, which represent a large fraction of the taxa in ecological assemblages, account for much of the biological diversity on Earth. These species make substantial contributions to ecosystem functioning, and are targets of conservation policy. Here we adopt an integrated approach, combining information on the rarity of species trait combinations, and their spatial restrictedness, to quantify the biogeography of rare fish (a taxon with almost 13,000 species) in the world's oceans. We find concentrations of rarity, in excess of what is predicted by a null expectation, near the coasts and at higher latitudes. We also observe mismatches between these rarity hotspots and marine protected areas. This pattern is repeated for both major groupings of fish, the Actinopterygii (bony fish) and Elasmobranchii (sharks, skates and rays). These results uncover global patterns of rarity that were not apparent from earlier work, and highlight the importance of using metrics that incorporate information on functional traits in the conservation and management of global marine fishes.

No pervasive relationship between species size and local abundance trends

Although there is some evidence that larger species could be more prone to population declines, the potential role of size traits in determining changes in community composition has been underexplored in global-scale analyses. Here, we combine a large cross-taxon assemblage time series database (BioTIME) with multiple trait databases to show that there is no clear correlation within communities between size traits and changes in abundance over time, suggesting that there is no consistent tendency for larger species to be doing proportionally better or worse than smaller species at local scales.

Vertebrate population trends are influenced by interactions between land use, climatic position, habitat loss and climate change

Rapid human-driven environmental changes are impacting animal populations around the world. Currently, land-use and climate change are two of the biggest pressures facing biodiversity. However, studies investigating the impacts of these pressures on population trends often do not consider potential interactions between climate and land-use change. Further, a population's climatic position (how close the ambient temperature and precipitation conditions are to the species' climatic tolerance limits) is known to influence responses to climate change but has yet to be investigated with regard to its influence on land-use change responses over time. Consequently, important variations across species' ranges in responses to environmental changes may be being overlooked. Here, we combine data from the Living Planet and BioTIME databases to carry out a global analysis exploring the impacts of land use, habitat loss, climatic position, climate change and the interactions between these variables, on vertebrate population trends. By bringing these datasets together, we analyse over 7,000 populations across 42 countries. We find that land-use change is interacting with climate change and a population's climatic position to influence rates of population change. Moreover, features of a population's local landscape (such as surrounding land cover) play important roles in these interactions. For example, populations in agricultural land uses where maximum temperatures were closer to their hot thermal limit, declined at faster rates when there had also been rapid losses in surrounding semi-natural habitat. The complex interactions between these variables on populations highlight the importance of taking intraspecific variation and interactions between local and global pressures into account. Understanding how drivers of change are interacting and impacting populations, and how this varies spatially, is critical if we are to identify populations at risk, predict species' responses to future environmental changes and produce suitable conservation strategies.

Think globally, measure locally: The MIREN standardized protocol for monitoring plant species distributions along elevation gradients

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series, even more exciting results can be expected, especially about range shifts. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.

Long-term abundance trends of insect taxa are only weakly correlated

Changes in the abundances of animals, such as with the ongoing concern about insect declines, are often assumed to be general across taxa. However, this assumption is largely untested. Here, we used a database of assemblage-wide long-term insect and arachnid monitoring to compare abundance trends among co-occurring pairs of taxa. We show that 60% of co-occurring taxa qualitatively showed long-term trends in the same direction-either both increasing or both decreasing. However, in terms of magnitude, temporal trends were only weakly correlated (mean freshwater r = 0.05 (±0.03), mean terrestrial r = 0.12 (±0.09)). The strongest correlation was between trends of beetles and those of moths/butterflies (r = 0.26). Overall, even though there is some support for directional similarity in temporal trends, we find that changes in the abundance of one taxon provide little information on the changes of other taxa. No clear candidate for umbrella or indicator taxa emerged from our analysis. We conclude that obtaining a better picture of changes in insect abundances will require monitoring of multiple taxa, which remains uncommon, especially in the terrestrial realm.

Long-term changes in temperate marine fish assemblages are driven by a small subset of species

The species composition of plant and animal assemblages across the globe has changed substantially over the past century. How do the dynamics of individual species cause this change? We classified species into seven unique categories of temporal dynamics based on the ordered sequence of presences and absences that each species contributes to an assemblage time series. We applied this framework to 14,434 species trajectories comprising 280 assemblages of temperate marine fishes surveyed annually for 20 or more years. Although 90% of the assemblages diverged in species composition from the baseline year, this compositional change was largely driven by only 8% of the species' trajectories. Quantifying the reorganization of assemblages based on species shared temporal dynamics should facilitate the task of monitoring and restoring biodiversity. We suggest ways in which our framework could provide informative measures of compositional change, as well as leverage future research on pattern and process in ecological systems.

Modeling Eastern Russian High Arctic Geese (Anser fabalis, A. albifrons) during moult and brood rearing in the 'New Digital Arctic'

Many polar species and habitats are now affected by man-made global climate change and underlying infrastructure. These anthropogenic forces have resulted in clear implications and many significant changes in the arctic, leading to the emergence of new climate, habitats and other issues including digital online infrastructure representing a ‘New Artic’. Arctic grazers, like Eastern Russian migratory populations of Tundra Bean Goose Anser fabalis and Greater White-fronted Goose A. albifrons, are representative examples and they are affected along the entire flyway in East Asia, namely China, Japan and Korea. Here we present the best publicly-available long-term (24 years) digitized geographic information system (GIS) data for the breeding study area (East Yakutia and Chukotka) and its habitats with ISO-compliant metadata. Further, we used seven publicly available compiled Open Access GIS predictor layers to predict the distribution for these two species within the tundra habitats. Using BIG DATA we are able to improve on the ecological niche prediction inference for both species by focusing for the first time specifically on biological relevant population cohorts: post-breeding moulting non-breeders, as well as post-breeding parent birds with broods. To assure inference with certainty, we assessed it with 4 lines of evidence including alternative best-available open access field data from GBIF.org as well as occurrence data compiled from the literature. Despite incomplete data, we found a good model accuracy in support of our evidence for a robust inference of the species distributions. Our predictions indicate a strong publicly best-available relative index of occurrence (RIO). These results are based on the quantified ecological niche showing more realistic gradual occurrence patterns but which are not fully in agreement with the current strictly applied parsimonious flyway and species delineations. While our predictions are to be improved further, e.g. when synergetic data are made freely available, here we offer within data caveats the first open access model platform for fine-tuning and future predictions for this otherwise poorly represented region in times of a rapid changing industrialized ‘New Arctic’ with global repercussions.

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying fish species diversity in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, because eDNA concentration is low in marine environments, the reliability of eDNA to detect species diversity can be limited. Using an eDNA metabarcoding approach to identify fish Molecular Taxonomic Units (MOTUs) with a single 12S marker, we aimed to assess how the number of sampling replicates and filtered water volume affect biodiversity estimates. We used a paired sampling design of 30 L per replicate on 68 reef transects from 8 sites in 3 tropical regions. We quantified local and regional sampling variability by comparing MOTU richness, compositional turnover, and compositional nestedness. We found strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non-overlapping assemblages rather than subsets of one another. As a result, non-saturated localized diversity accumulation curves suggest that even 6 replicates (180 L) in the same location can underestimate local diversity (for an area <1 km). However, sampling regional diversity using ~25 replicates in variable locations (often covering 10 s of km) often saturated biodiversity accumulation curves. Our results demonstrate variability of diversity estimates possibly arising from heterogeneous distribution of eDNA in seawater, highly skewed frequencies of eDNA traces per MOTU, in addition to variability in eDNA processing. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes in local assemblages. Avoiding false-negative detections in future biomonitoring efforts requires increasing replicates or sampled water volume to better inform management of marine biodiversity using eDNA.

Temporal variability in population and community dynamics

Populations and communities fluctuate in their overall numbers through time, and the magnitude of fluctuations in individual species may scale to communities. However, the composite variability at the community scale is expected to be tempered by opposing fluctuations in individual populations, a phenomenon often called the portfolio effect. Understanding population variability, how it scales to community variability, and the spatial scaling in this variability are pressing needs given shifting environmental conditions and community composition. We explore evidence for portfolio effects using null community simulations and a large collection of empirical community time series from the BioTIME database. Additionally, we explore the relative roles of habitat type and geographic location on population and community temporal variability. We find strong portfolio effects in our theoretical community model, but weak effects in empirical data, suggesting a role for shared environmental responses, interspecific competition, or a litany of other factors. Furthermore, we observe a clear latitudinal signal - and differences among habitat types - in population and community variability. Together, this highlights the need to develop realistic models of community dynamics, and hints at spatial, and underlying environmental, gradients in variability in both population and community dynamics.

Biodiversity: Monitoring trends and implications for ecosystem functioning

Systematic, long-term monitoring provides crucial evidence regarding the vulnerability of biodiversity to environmental change. New research shows that trends in taxonomic diversity do not necessarily match trends in functional diversity. Interpreting the implications of different kinds of diversity change for ecosystem functioning remains a key priority.

Annual changes in the Biodiversity Intactness Index in tropical and subtropical forest biomes, 2001-2012

Few biodiversity indicators are available that reflect the state of broad-sense biodiversity—rather than of particular taxa—at fine spatial and temporal resolution. One such indicator, the Biodiversity Intactness Index (BII), estimates how the average abundance of the native terrestrial species in a region compares with their abundances in the absence of pronounced human impacts. We produced annual maps of modelled BII at 30-arc-second resolution (roughly 1 km at the equator) across tropical and subtropical forested biomes, by combining annual data on land use, human population density and road networks, and statistical models of how these variables affect overall abundance and compositional similarity of plants, fungi, invertebrates and vertebrates. Across tropical and subtropical biomes, BII fell by an average of 1.9 percentage points between 2001 and 2012, with 81 countries seeing an average reduction and 43 an average increase; the extent of primary forest fell by 3.9% over the same period. We did not find strong relationships between changes in BII and countries’ rates of economic growth over the same period; however, limitations in mapping BII in plantation forests may hinder our ability to identify these relationships. This is the first time temporal change in BII has been estimated across such a large region.