Disproportionate declines of formerly abundant species underlie insect loss.

Studies have reported widespread declines in terrestrial insect abundances in recent years1-4, but trends in other biodiversity metrics are less clear-cut5-7. Here we examined long-term trends in 923 terrestrial insect assemblages monitored in 106 studies, and found concomitant declines in abundance and species richness. For studies that were resolved to species level (551 sites in 57 studies), we observed a decline in the number of initially abundant species through time, but not in the number of very rare species. At the population level, we found that species that were most abundant at the start of the time series showed the strongest average declines (corrected for regression-to-the-mean effects). Rarer species were, on average, also declining, but these were offset by increases of other species. Our results suggest that the observed decreases in total insect abundance2 can mostly be explained by widespread declines of formerly abundant species. This counters the common narrative that biodiversity loss is mostly characterized by declines of rare species8,9. Although our results suggest that fundamental changes are occurring in insect assemblages, it is important to recognize that they represent only trends from those locations for which sufficient long-term data are available. Nevertheless, given the importance of abundant species in ecosystems10, their general declines are likely to have broad repercussions for food webs and ecosystem functioning.

Ecosystem decay exacerbates biodiversity loss with habitat loss.

Although habitat loss is the predominant factor leading to biodiversity loss in the Anthropocene1,2, exactly how this loss manifests-and at which scales-remains a central debate3-6. The 'passive sampling' hypothesis suggests that species are lost in proportion to their abundance and distribution in the natural habitat7,8, whereas the 'ecosystem decay' hypothesis suggests that ecological processes change in smaller and more-isolated habitats such that more species are lost than would have been expected simply through loss of habitat alone9,10. Generalizable tests of these hypotheses have been limited by heterogeneous sampling designs and a narrow focus on estimates of species richness that are strongly dependent on scale. Here we analyse 123 studies of assemblage-level abundances of focal taxa taken from multiple habitat fragments of varying size to evaluate the influence of passive sampling and ecosystem decay on biodiversity loss. We found overall support for the ecosystem decay hypothesis. Across all studies, ecosystems and taxa, biodiversity estimates from smaller habitat fragments-when controlled for sampling effort-contain fewer individuals, fewer species and less-even communities than expected from a sample of larger fragments. However, the diversity loss due to ecosystem decay in some studies (for example, those in which habitat loss took place more than 100 years ago) was less than expected from the overall pattern, as a result of compositional turnover by species that were not originally present in the intact habitats. We conclude that the incorporation of non-passive effects of habitat loss on biodiversity change will improve biodiversity scenarios under future land use, and planning for habitat protection and restoration.

Genotype diversity enhances invasion resistance of native plants via soil biotic feedbacks.

Although native species diversity is frequently reported to enhance invasion resistance, within-species diversity of native plants can also moderate invasions. While the positive diversity-invasion resistance relationship is often attributed to competition, indirect effects mediated through plant-soil feedbacks can also influence the relationship. We manipulated the genotypic diversity of an endemic species, Scirpus mariqueter, and evaluated the effects of abiotic versus biotic feedbacks on the performance of a global invader, Spartina alterniflora. We found that invader performance on live soils decreased non-additively with genotypic diversity of the native plant that trained the soils, but this reversed when soils were sterilized to eliminate feedbacks through soil biota. The influence of soil biota on the feedback was primarily associated with increased levels of microbial biomass and fungal diversity in soils trained by multiple-genotype populations. Our findings highlight the importance of plant-soil feedbacks mediating the positive relationship between genotypic diversity and invasion resistance.

When Do Traits Tell More Than Species about a Metacommunity? A Synthesis across Ecosystems and Scales.

AbstractLinking species traits with the variation in species assemblages across habitats has often proved useful for developing a more mechanistic understanding of species distributions in metacommunities. However, summarizing the rich tapestry of a species in all of its nuance with a few key ecological traits can also lead to an abstraction that provides less predictability than when using taxonomy alone. As a further complication, taxonomic and functional diversities can be inequitably compared, either by integrating taxonomic-level information into the calculation of how functional aspects of communities vary or by detecting spurious trait-environment relationships. To remedy this, we here synthesize analyses of 80 datasets on different taxa, ecosystems, and spatial scales that include information on abundance or presence/absence of species across sites with variable environmental conditions and the species' traits. By developing analyses that treat functional and taxonomic diversity equitably, we ask when functional diversity helps to explain metacommunity structure. We found that patterns of functional diversity explained metacommunity structure and response to environmental variation in only 25% of the datasets using a multitrait approach but up to 59% using a single-trait approach. Nevertheless, an average of only 19% (interquartile range = 0%-29%) of the traits showed a significant signal across environmental gradients. Species-level traits, as typically collected and analyzed through functional diversity patterns, often do not bring predictive advantages over what the taxonomic information already holds. While our assessment of a limited advantage of using traits to explain variation in species assemblages was largely true across ecosystems, traits played a more useful role in explaining variation when many traits were used and when trait constructs were more related to species' status, life history, and mobility. We propose future research directions to make trait-based approaches and data more helpful for inference in metacommunity ecology.

Climate-associated variation in the drivers of benthic macroinvertebrate species-area relationships across shallow freshwater lakes.

The island species-area relationship (ISAR) describes how species richness increases with increasing area of a given island or island-like habitat, such as freshwater lakes. While the ISAR is one of the most common phenomena observed in ecology, there is variation in both the form of the relationship and its underlying mechanisms. We compiled a global data set of benthic macroinvertebrates from 524 shallow freshwater lakes, ranging from 1 to 293,300 ha in area. We used individual-based rarefaction to determine the degree to which ISAR was influenced by mechanisms other than passive sampling (larger islands passively sample more individuals from the regional pool and, therefore, have more species than smaller islands), which would bias results away from expected relationships between rarefied species richness (and other measures that capture relative abundances) and lake area. We also examined how climate may alter the shape of the ISARs. We found that both rarefied species richness (the number of species standardized by area or number of individuals) and a measure of evenness emphasizing common species exhibit shallow slopes in relationships with lake area, suggesting that the expected ISARs in these lakes most likely result from passive sampling. While there was considerable variation among ISARs across the investigated lakes, we found an overall positive rarefied ISAR for lakes in warm (i.e. tropical/subtropical) regions (n = 195), and in contrast, an overall negative rarefied ISAR in cool (i.e. north temperate) lakes (n = 329). This suggested that mechanisms beyond passive sampling (e.g. colonization-extinction dynamics and/or heterogeneity) were more likely to operate in warm lakes. One possible reason for this difference is that the area-dependent intensity of fish predation, which can lead to flatter ISARs, is weaker in warmer relative to cooler lakes. Our study illustrates the importance of understanding both the pattern and potential processes underlying the ISARs of freshwater lakes in different climatic regions. Furthermore, it provides a baseline for understanding how further changes to the ecosystem (i.e. in lake area or climate) might influence biodiversity patterns.

Linking changes in species composition and biomass in a globally distributed grassland experiment.

Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.

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.

Dissecting macroecological and macroevolutionary patterns of forest biodiversity across the Hawaiian archipelago.

Biodiversity patterns emerge as a consequence of evolutionary and ecological processes. Their relative importance is frequently tested on model ecosystems such as oceanic islands that vary in both. However, the coarse-scale data typically used in biogeographic studies have limited inferential power to separate the effects of historical biogeographic factors (e.g., island age) from the effects of ecological ones (e.g., island area and habitat heterogeneity). Here, we describe local-scale biodiversity patterns of woody plants using a database of more than 500 forest plots from across the Hawaiian archipelago, where these volcanic islands differ in age by several million years. We show that, after controlling for factors such as island area and heterogeneity, the oldest islands (Kaua'i and O'ahu) have greater native species diversity per unit area than younger islands (Maui and Hawai'i), indicating an important role for macroevolutionary processes in driving not just whole-island differences in species diversity, but also local community assembly. Further, we find that older islands have a greater number of rare species that are more spatially clumped (i.e., higher within-island ß-diversity) than younger islands. When we included alien species in our analyses, we found that the signal of macroevolutionary processes via island age was diluted. Our approach allows a more explicit test of the question of how macroevolutionary factors shape not just regional-scale biodiversity, but also local-scale community assembly patterns and processes in a model archipelago ecosystem, and it can be applied to disentangle biodiversity drivers in other systems.

General statistical scaling laws for stability in ecological systems.

Ecological stability refers to a family of concepts used to describe how systems of interacting species vary through time and respond to disturbances. Because observed ecological stability depends on sampling scales and environmental context, it is notoriously difficult to compare measurements across sites and systems. Here, we apply stochastic dynamical systems theory to derive general statistical scaling relationships across time, space, and ecological level of organisation for three fundamental stability aspects: resilience, resistance, and invariance. These relationships can be calibrated using random or representative samples measured at individual scales, and projected to predict average stability at other scales across a wide range of contexts. Moreover deviations between observed vs. extrapolated scaling relationships can reveal information about unobserved heterogeneity across time, space, or species. We anticipate that these methods will be useful for cross-study synthesis of stability data, extrapolating measurements to unobserved scales, and identifying underlying causes and consequences of heterogeneity.

Species loss due to nutrient addition increases with spatial scale in global grasslands.

The effects of altered nutrient supplies and herbivore density on species diversity vary with spatial scale, because coexistence mechanisms are scale dependent. This scale dependence may alter the shape of the species-area relationship (SAR), which can be described by changes in species richness (S) as a power function of the sample area (A): S = cAz , where c and z are constants. We analysed the effects of experimental manipulations of nutrient supply and herbivore density on species richness across a range of scales (0.01-75 m2 ) at 30 grasslands in 10 countries. We found that nutrient addition reduced the number of species that could co-occur locally, indicated by the SAR intercepts (log c), but did not affect the SAR slopes (z). As a result, proportional species loss due to nutrient enrichment was largely unchanged across sampling scales, whereas total species loss increased over threefold across our range of sampling scales.

Effects of site-selection bias on estimates of biodiversity change.

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300-400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of -0.1 to -0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.

Efectos del Sesgo en la Selección de Sitio sobre las Estimaciones del Cambio en la Biodiversidad Resumen Las estimaciones del cambio en la biodiversidad son esenciales para el manejo y la conservación de los ecosistemas. Las estimaciones precisas dependen de la selección de sitios representativos pero su monitoreo con frecuencia se enfoca en los sitios de interés especial. En su mayoría se desconoce cómo influyen tales sesgos en la selección de sitios sobre las estimaciones del cambio en la biodiversidad. El sesgo en la selección de sitios ocurre potencialmente en cuatro fuentes principales de datos sobre biodiversidad, disminuyendo en probabilidad cuando los datos vienen de la ciencia ciudadana, museos, el monitoreo de los parques nacionales y la investigación académica. Definimos al sesgo en la selección de sitios como la preferencia por sitios que están densamente poblados (es decir, sesgo por abundancia) o que son ricos en especies (es decir, sesgo por riqueza). Simulamos el cambio en la biodiversidad en un paisaje virtual y le dimos seguimiento a la biodiversidad observada en un sitio muestreado. El sitio fue seleccionado al azar o con un sesgo en la selección de sitio. Usamos un modelo simple basado en los individuos y resuelto espacialmente para predecir el movimiento o la dispersión de los individuos dentro y fuera del sitio de muestreo elegido. El sesgo en la selección de sitio exageró las estimaciones de la pérdida de la biodiversidad en los sitios seleccionados con un sesgo en promedio de 300-400% en comparación con sitios seleccionados al azar. Con base en nuestras simulaciones, el sesgo en la selección de sitio derivó en que las tendencias positivas se estimaran como tendencias negativas: se estimó que el incremento en la riqueza fue de 0.1 en sitios seleccionados al azar, mientras que en los sitios seleccionados con un sesgo mostraron un cambio en la riqueza de −0.1 a −0.2 en promedio. Así, el sesgo en la selección de sitio puede indicar erróneamente la existencia de disminuciones en la biodiversidad. Variamos el diseño del muestreo y las características de las especies y encontramos que los sesgos en la selección de sitio estaban más consolidados en las series de tiempo corto, para los granos pequeños, organismos con una baja habilidad de dispersión, grandes patrimonios genéticos de especies regionales y una agregación espacial fuerte. Con base en estos resultados, para lograr minimizar el sesgo en la selección de sitio, recomendamos usar esquemas sistemáticos de selección de sitio; maximizar el área de muestreo; calcular las medidas de biodiversidad acumulativamente en los lotes; y usar las medidas de biodiversidad que son menos sensibles a las especies raras, como el número efectivo de especies. Se necesita tener conciencia sobre el impacto potencial del sesgo en la selección de sitio para el monitoreo de la biodiversidad, el diseño de nuevos estudios sobre el cambio en la biodiversidad y la interpretación de los datos existentes.

A process-based metacommunity framework linking local and regional scale community ecology.

The metacommunity concept has the potential to integrate local and regional dynamics within a general community ecology framework. To this end, the concept must move beyond the discrete archetypes that have largely defined it (e.g. neutral vs. species sorting) and better incorporate local scale species interactions and coexistence mechanisms. Here, we present a fundamental reconception of the framework that explicitly links local coexistence theory to the spatial processes inherent to metacommunity theory, allowing for a continuous range of competitive community dynamics. These dynamics emerge from the three underlying processes that shape ecological communities: (1) density-independent responses to abiotic conditions, (2) density-dependent biotic interactions and (3) dispersal. Stochasticity is incorporated in the demographic realisation of each of these processes. We formalise this framework using a simulation model that explores a wide range of competitive metacommunity dynamics by varying the strength of the underlying processes. Using this model and framework, we show how existing theories, including the traditional metacommunity archetypes, are linked by this common set of processes. We then use the model to generate new hypotheses about how the three processes combine to interactively shape diversity, functioning and stability within metacommunities.

Reducing dispersal limitation via seed addition increases species richness but not above-ground biomass.

Seed dispersal limitation, which can be exacerbated by a number of anthropogenic causes, can result in local communities having fewer species than they might potentially support, representing a potential diversity deficit. The link between processes that shape natural variation in diversity, such as dispersal limitation, and the consequent effects on productivity is less well known. Here, we synthesised data from 12 seed addition experiments in grassland communities to examine the influence of reducing seed dispersal limitation (from 1 to 60 species added across experiments) on species richness and productivity. For every 10 species of seed added, we found that species richness increased by about two species. However, the increase in species richness by overcoming seed limitation did not lead to a concomitant increase in above-ground biomass production. This highlights the need to consider the relationship between biodiversity and ecosystem functioning in a pluralistic way that considers both the processes that shape diversity and productivity simultaneously in naturally assembled communities.

We need more realistic climate change experiments for understanding ecosystems of the future.

Experiments that alter local climate and measure community- and ecosystem-level responses are an important tool for understanding how future ecosystems will respond to climate change. Here, we synthesized data from 76 studies that manipulated climate and measured plant community responses, and found that most climate change experiments do not correspond to model-projected climate scenarios for their respective regions. This mismatch constrains our ability to predict responses of plant biodiversity and ecosystem functions to climate change, and we conclude with suggestions for a way forward. See also the Commentary on this article by Muller et al., 26, e4-e5 and De Boeck et al.,26, e6-e7.

Understanding plant communities of the future requires filling knowledge gaps.

In their response to our letter, De Boek et al. (2019) and Muller, Ballhausen, Lakovic, and Rillig (2019) argue that our conclusion that we need more realistic climate change experiments is too "gloomy" and that we need a plurality of experiments including extremes and multifactorial approaches. We agree that a diversity of experimental approaches is required in order to anticipate the consequences for plant communities of alternative future environmental conditions. However, we argue that "realistic" experiments are underrepresented in the portfolio of previous experiments, and are urgently needed to understand how species communities of the future will look like and how they will function. This article is a response to Muller et al., 26, e4-e5 and De Boeck et al., 26, e6-e7.

Habitat loss over six decades accelerates regional and local biodiversity loss via changing landscape connectance.

When habitats are lost, species are lost in the region as a result of the sampling process. However, it is less clear what happens to biodiversity in the habitats that remain. Some have argued that the main influence of habitat loss on biodiversity is simply due to the total amount of habitat being reduced, while others have argued that fragmentation leads to fewer species per site because of altered spatial connectance among extant habitats. Here, we use a unique data set on invertebrate species in ponds spanning six decades of habitat loss to show that both regional and local species richness declined, indicating that species loss is compounded by habitat loss via connectivity loss, and not a result of a sampling process or changes in local environmental conditions. Overall, our work provides some of the clearest evidence to date from a longitudinal study that habitat loss translates into species loss, even within the remaining habitats.

Spatial scale modulates the inference of metacommunity assembly processes.

The abundance and distribution of species across the landscape depend on the interaction between local, spatial, and stochastic processes. However, empirical syntheses relating these processes to spatiotemporal patterns of structure in metacommunities remain elusive. One important reason for this lack of synthesis is that the relative importance of the core assembly processes (dispersal, selection, and drift) critically depends on the spatial grain and extent over which communities are studied. To illustrate this, we simulated different aspects of community assembly on heterogeneous landscapes, including the strength of response to environmental heterogeneity (inherent to niche theory) vs. dispersal and stochastic drift (inherent to neutral theory). We show that increasing spatial extent leads to increasing importance of niche selection, whereas increasing spatial grain leads to decreasing importance of niche selection. The strength of these scaling effects depended on environment configuration, dispersal capacity, and niche breadth. By mapping the variation observed from the scaling effects in simulations, we could recreate the entire range of variation observed within and among empirical studies. This means that variation in the relative importance of assembly processes among empirical studies is largely scale dependent and cannot be directly compared. The scaling coefficient of the relative contribution of assembly processes, however, can be interpreted as a scale-integrative estimate to compare assembly processes across different regions and ecosystems. This emphasizes the necessity to consider spatial scaling as an explicit component of studies intended to infer the importance of community assembly processes.

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

Because biodiversity is multidimensional and scale-dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale-dependence matters for empirical studies, and (2) if it does matter, how exactly we should quantify biodiversity change. To address the first question, we analysed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity - species richness - was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale-dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi-dimensional and multi-scale perspective informs the responses of biodiversity to ecological drivers.

Lifting the veil: richness measurements fail to detect systematic biodiversity change over three decades.

While there is widespread recognition of human involvement in biodiversity loss globally, at smaller spatial extents, the effects are less clear. One reason is that local effects are obscured by the use of summary biodiversity variables, such as species richness, that provide only limited insight into complex biodiversity change. Here, we use 30 yr of invertebrate data from a metacommunity of 10 streams in Wales, UK, combined with regional surveys, to examine temporal changes in multiple biodiversity measures at local, metacommunity, and regional scales. There was no change in taxonomic or functional α-diversity and spatial ß-diversity metrics at any scale over the 30-yr time series, suggesting a relative stasis in the system and no evidence for on-going homogenization. However, temporal changes in mean species composition were evident. Two independent approaches to estimate species niche breadth showed that compositional changes were associated with a systematic decline in mean community specialization. Estimates of species-specific local extinction and immigration probabilities suggested that this decline was linked to lower recolonization rates of specialists, rather than greater local extinction rates. Our results reveal the need for caution in implying stasis from patterns in α-diversity and spatial ß-diversity measures that might mask non-random biodiversity changes over time. We also show how different but complementary approaches to estimate niche breadth and functional distinctness of species can reveal long-term trends in community homogenization likely to be important to conservation and ecosystem function.