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.

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.

Estimation of functional diversity and species traits from ecological monitoring data.

The twin crises of climate change and biodiversity loss define a strong need for functional diversity monitoring. While the availability of high-quality ecological monitoring data is increasing, the quantification of functional diversity so far requires the identification of species traits, for which data are harder to obtain. However, the traits that are relevant for the ecological function of a species also shape its performance in the environment and hence, should be reflected indirectly in its spatiotemporal distribution. Thus, it may be possible to reconstruct these traits from a sufficiently extensive monitoring dataset. Here, we use diffusion maps, a deterministic and de facto parameter-free analysis method, to reconstruct a proxy representation of the species' traits directly from monitoring data and use it to estimate functional diversity. We demonstrate this approach with both simulated data and real-world phytoplankton monitoring data from the Baltic Sea. We anticipate that wider application of this approach to existing data could greatly advance the analysis of changes in functional biodiversity.

Elemental and biochemical nutrient limitation of zooplankton: A meta-analysis.

Primary consumers in aquatic ecosystems are frequently limited by the quality of their food, often expressed as phytoplankton elemental and biochemical composition. However, the effects of these food quality indicators vary across studies, and we lack an integrated understanding of how elemental (e.g. nitrogen, phosphorus) and biochemical (e.g. fatty acid, sterol) limitations interactively influence aquatic food webs. Here, we present the results of a meta-analysis using >100 experimental studies, confirming that limitation by N, P, fatty acids, and sterols all have significant negative effects on zooplankton performance. However, effects varied by grazer response (growth vs. reproduction), specific manipulation, and across taxa. While P limitation had greater effects on zooplankton growth than fatty acids overall, P and fatty acid limitation had equal effects on reproduction. Furthermore, we show that: nutrient co-limitation in zooplankton is strong; effects of essential fatty acid limitation depend on P availability; indirect effects induced by P limitation exceed direct effects of mineral P limitation; and effects of nutrient amendments using laboratory phytoplankton isolates exceed those using natural field communities. Our meta-analysis reconciles contrasting views about the role of various food quality indicators, and their interactions, for zooplankton performance, and provides a mechanistic understanding of trophic transfer in aquatic environments.

Failures to disagree are essential for environmental science to effectively influence policy development.

While environmental science, and ecology in particular, is working to provide better understanding to base sustainable decisions on, the way scientific understanding is developed can at times be detrimental to this cause. Locked-in debates are often unnecessarily polarised and can compromise any common goals of the opposing camps. The present paper is inspired by a resolved debate from an unrelated field of psychology where Nobel laureate David Kahneman and Garry Klein turned what seemed to be a locked-in debate into a constructive process for their fields. The present paper is also motivated by previous discourses regarding the role of thresholds in natural systems for management and governance, but its scope of analysis targets the scientific process within complex social-ecological systems in general. We identified four features of environmental science that appear to predispose for locked-in debates: (1) The strongly context-dependent behaviour of ecological systems. (2) The dominant role of single hypothesis testing. (3) The high prominence given to theory demonstration compared investigation. (4) The effect of urgent demands to inform and steer policy. This fertile ground is further cultivated by human psychological aspects as well as the structure of funding and publication systems.

Low statistical power and overestimated anthropogenic impacts, exacerbated by publication bias, dominate field studies in global change biology.

Field studies are essential to reliably quantify ecological responses to global change because they are exposed to realistic climate manipulations. Yet such studies are limited in replicates, resulting in less power and, therefore, potentially unreliable effect estimates. Furthermore, while manipulative field experiments are assumed to be more powerful than non-manipulative observations, it has rarely been scrutinized using extensive data. Here, using 3847 field experiments that were designed to estimate the effect of environmental stressors on ecosystems, we systematically quantified their statistical power and magnitude (Type M) and sign (Type S) errors. Our investigations focused upon the reliability of field experiments to assess the effect of stressors on both ecosystem's response magnitude and variability. When controlling for publication bias, single experiments were underpowered to detect response magnitude (median power: 18%-38% depending on effect sizes). Single experiments also had much lower power to detect response variability (6%-12% depending on effect sizes) than response magnitude. Such underpowered studies could exaggerate estimates of response magnitude by 2-3 times (Type M errors) and variability by 4-10 times. Type S errors were comparatively rare. These observations indicate that low power, coupled with publication bias, inflates the estimates of anthropogenic impacts. Importantly, we found that meta-analyses largely mitigated the issues of low power and exaggerated effect size estimates. Rather surprisingly, manipulative experiments and non-manipulative observations had very similar results in terms of their power, Type M and S errors. Therefore, the previous assumption about the superiority of manipulative experiments in terms of power is overstated. These results call for highly powered field studies to reliably inform theory building and policymaking, via more collaboration and team science, and large-scale ecosystem facilities. Future studies also require transparent reporting and open science practices to approach reproducible and reliable empirical work and evidence synthesis.

Functionally reversible impacts of disturbances on lake food webs linked to spatial and seasonal dependencies.

Increasing human impact on the environment is causing drastic changes in disturbance regimes and how they prevail over time. Of increasing relevance is to further our understanding on biological responses to pulse disturbances (short duration) and how they interact with other ongoing press disturbances (constantly present). Because the temporal and spatial contexts of single experiments often limit our ability to generalize results across space and time, we conducted a modularized mesocosm experiment replicated in space (five lakes along a latitudinal gradient in Scandinavia) and time (two seasons, spring and summer) to generate general predictions on how the functioning and composition of multitrophic plankton communities (zoo-, phyto- and bacterioplankton) respond to pulse disturbances acting either in isolation or combined with press disturbances. As pulse disturbance, we used short-term changes in fish presence, and as press disturbance, we addressed the ongoing reduction in light availability caused by increased cloudiness and lake browning in many boreal and subarctic lakes. First, our results show that the top-down pulse disturbance had the strongest effects on both functioning and composition of the three trophic levels across sites and seasons, with signs for interactive impacts with the bottom-up press disturbance on phytoplankton communities. Second, community composition responses to disturbances were highly divergent between lakes and seasons: temporal accumulated community turnover of the same trophic level either increased (destabilization) or decreased (stabilization) in response to the disturbances compared to control conditions. Third, we found functional recovery from the pulse disturbances to be frequent at the end of most experiments. In a broader context, these results demonstrate that top-down, pulse disturbances, either alone or with additional constant stress upon primary producers caused by bottom-up disturbances, can induce profound but often functionally reversible changes across multiple trophic levels, which are strongly linked to spatial and temporal context dependencies. Furthermore, the identified dichotomy of disturbance effects on the turnover in community composition demonstrates the potential of disturbances to either stabilize or destabilize biodiversity patterns over time across a wide range of environmental conditions.

The impact of climate warming on species diversity across scales: Lessons from experimental meta-ecosystems.

Aim: The aim was to evaluate the effects of climate warming on biodiversity across spatial scales (i.e., α-, ß- and γ-diversity) and the effects of patch openness and experimental context on diversity responses. Location: Global. Time period: 1995-2017. Major taxa studied: Fungi, invertebrates, phytoplankton, plants, seaweed, soil microbes and zooplankton. Methods: We compiled data from warming experiments and conducted a meta-analysis to evaluate the effects of warming on different components of diversity (such as species richness and equivalent numbers) at different spatial scales (α-, ß- and γ-diversity, partitioning ß-diversity into species turnover and nestedness components). We also investigated how these effects were modulated by system openness, defined as the possibility of replicates being colonized by new species, and experimental context (duration, mean temperature change and ecosystem type). Results: Experimental warming did not affect local species richness (α-diversity) but decreased effective numbers of species by affecting species dominance. Warming increased species spatial turnover (ß-diversity), although no significant changes were detected at the regional scale (γ-diversity). Site openness and experimental context did not significantly affect our results, despite significant heterogeneity in the effect sizes of α- and ß-diversity. Main conclusions: Our meta-analysis shows that the effects of warming on biodiversity are scale dependent. The local and regional inventory diversity remain unaltered, whereas species composition across temperature gradients and the patterns of species dominance change with temperature, creating novel communities that might be harder to predict.

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.

Cross-continental analysis of coastal biodiversity change.

Whereas the anthropogenic impact on marine biodiversity is undebated, the quantification and prediction of this change are not trivial. Simple traditional measures of biodiversity (e.g. richness, diversity indices) do not capture the magnitude and direction of changes in species or functional composition. In this paper, we apply recently developed methods for measuring biodiversity turnover to time-series data of four broad taxonomic groups from two coastal regions: the southern North Sea (Germany) and the South African coast. Both areas share geomorphological features and ecosystem types, allowing for a critical assessment of the most informative metrics of biodiversity change across organism groups. We found little evidence for directional trends in univariate metrics of diversity for either the effective number of taxa or the amount of richness change. However, turnover in composition was high (on average nearly 30% of identities when addressing presence or absence of species) and even higher when taking the relative dominance of species into account. This turnover accumulated over time at similar rates across regions and organism groups. We conclude that biodiversity metrics responsive to turnover provide a more accurate reflection of community change relative to conventional metrics (absolute richness or relative abundance) and are spatially broadly applicable. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.

Integrative research perspectives on marine conservation.

Whereas the conservation and management of biodiversity has become a key issue in environmental sciences and policy in general, the conservation of marine biodiversity faces additional challenges such as the challenges of accessing field sites (e.g. polar, deep sea), knowledge gaps regarding biodiversity trends, high mobility of many organisms in fluid environments, and ecosystem-specific obstacles to stakeholder engagement and governance. This issue comprises contributions from a diverse international group of scientists in a benchmarking volume for a common research agenda on marine conservation. We begin by addressing information gaps on marine biodiversity trends through novel approaches and technologies, then linking such information to ecosystem functioning through a focus on traits. We then leverage the knowledge of these relationships to inform theory aiming at predicting the future composition and functioning of marine communities. Finally, we elucidate the linkages between marine ecosystems and human societies by examining economic, management and governance approaches that contribute to effective marine conservation in practice. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.

Thresholds for ecological responses to global change do not emerge from empirical data.

To understand ecosystem responses to anthropogenic global change, a prevailing framework is the definition of threshold levels of pressure, above which response magnitudes and their variances increase disproportionately. However, we lack systematic quantitative evidence as to whether empirical data allow definition of such thresholds. Here, we summarize 36 meta-analyses measuring more than 4,600 global change impacts on natural communities. We find that threshold transgressions were rarely detectable, either within or across meta-analyses. Instead, ecological responses were characterized mostly by progressively increasing magnitude and variance when pressure increased. Sensitivity analyses with modelled data revealed that minor variances in the response are sufficient to preclude the detection of thresholds from data, even if they are present. The simulations reinforced our contention that global change biology needs to abandon the general expectation that system properties allow defining thresholds as a way to manage nature under global change. Rather, highly variable responses, even under weak pressures, suggest that 'safe-operating spaces' are unlikely to be quantifiable.

Krill vs salps: dominance shift from krill to salps is associated with higher dissolved N:P ratios.

Pronounced atmospheric and oceanic warming along the West Antarctic Peninsula (WAP) has resulted in abundance shifts in populations of Antarctic krill and Salpa thompsoni determined by changes in the timing of sea-ice advance, the duration of sea-ice cover and food availability. Krill and salps represent the most important macrozooplankton grazers at the WAP, but differ profoundly in their feeding biology, population dynamics and stoichiometry of excretion products with potential consequences for the relative availability of dissolved nitrogen and phosphorus. Alternation of the dissolved nutrient pool due to shifts in krill and salp densities have been hypothesized but never explicitly tested by using observational data. We therefore used the Palmer LTER dataset in order to investigate whether the dominance of either grazer is related with the observed dissolved nitrogen:phosphorus (N:P) ratios at the WAP. Across the whole sampling grid, the dominance of salps over krill was significantly correlated to higher concentrations of both N and P as well as a higher N:P ratios. Using actual long-term data, our study shows for the first time that changes in key grazer dominance may have consequences for the dynamics of dissolved nitrogen and phosphorus at the WAP.

Meta-analysis on pulse disturbances reveals differences in functional and compositional recovery across ecosystems.

Most ecosystems are affected by anthropogenic or natural pulse disturbances, which alter the community composition and functioning for a limited period of time. Whether and how quickly communities recover from such pulses is central to our understanding of biodiversity dynamics and ecosystem organisation, but also to nature conservation and management. Here, we present a meta-analysis of 508 (semi-)natural field experiments globally distributed across marine, terrestrial and freshwater ecosystems. We found recovery to be significant yet incomplete. At the end of the experiments, disturbed treatments resembled controls again when considering abundance (94%), biomass (82%), and univariate diversity measures (88%). Most disturbed treatments did not further depart from control after the pulse, indicating that few studies showed novel trajectories induced by the pulse. Only multivariate community composition on average showed little recovery: disturbed species composition remained dissimilar to the control throughout most experiments. Still, when experiments revealed a higher compositional stability, they tended to also show higher functional stability. Recovery was more complete when systems had high resistance, whereas resilience and resistance were negatively correlated. The overall results were highly consistent across studies, but significant differences between ecosystems and organism groups appeared. Future research on disturbances should aim to understand these differences, but also fill obvious gaps in the empirical assessments for regions (especially the tropics), ecosystems and organisms. In summary, we provide general evidence that (semi-)natural communities can recover from pulse disturbances, but compositional aspects are more vulnerable to long-lasting effects of pulse disturbance than the emergent functions associated to them.

Scale Both Confounds and Informs Characterization of Species Coexistence in Empirical Systems.

Identifying stable coexistence in empirical systems is notoriously difficult. Here, we show how spatiotemporal structure and complex system dynamics can confound two commonly used stability metrics in empirical contexts: response to perturbation and invasion rate when rare. We use these metrics to characterize stable coexistence across a range of spatial and temporal scales for five simulated models in which the ability of species to coexist in the long term is known a priori and for an empirical old field successional time series. We term the resulting multivariate distribution of metrics a "stability fingerprint." In accordance with a wide range of classic and recent studies, our results demonstrate that no combination of empirically tractable metrics or measurements is guaranteed to "correctly" characterize coexistence. However, we also find that heuristic information from the stability fingerprint can be used to broadly characterize dynamic behavior and identify circumstances under which particular combinations of species are likely to persist. Moreover, stability fingerprints appear to be particularly well suited for matching potential theoretical models to observed dynamics. These findings suggest that it may be prudent to shift the focus of empirical stability analysis away from quantifying single measures of stability and toward more heuristic, multivariate characterizations of community dynamics.

Phytoplankton community responses to temperature fluctuations under different nutrient concentrations and stoichiometry.

Nutrient availability and temperature are important drivers of phytoplankton growth and stoichiometry. However, the interactive effects of nutrients and temperature on phytoplankton have been analyzed mostly by addressing changes in average temperature, whereas recent evidence suggests an important role of temperature fluctuations. In a laboratory experiment, we grew a natural phytoplankton community under fluctuating and constant temperature regimes across 25 combinations of nitrogen (N) and phosphorus (P) supply. Temperature fluctuations decreased phytoplankton growth rate (rmax ), as predicted by nonlinear averaging along the temperature-growth relationship. rmax increased with increasing P supply, and a significant temperature × P × N interaction reflected that the shape of the thermal reaction norm depended on nutrients. By contrast, phytoplankton carrying capacity increased with N supply and in fluctuating rather than constant temperature. Higher phytoplankton N:P ratios under constant temperature showed that temperature regimes affected cellular nutrient incorporation. Minor differences in species diversity and composition existed. Our results suggest that temperature variability interacts with nutrient supply to affect phytoplankton physiology and stoichiometry at the community level.

Biodiversity-ecosystem functioning relationships in fish communities: biomass is related to evenness and the environment, not to species richness.

The relationship between biodiversity and ecosystem functioning (BEF) is a topic of considerable interest to scientists and managers because a better understanding of its underlying mechanisms may help us mitigate the consequences of biodiversity loss on ecosystems. Our current knowledge of BEF relies heavily on theoretical and experimental studies, typically conducted on a narrow range of spatio-temporal scales, environmental conditions, and trophic levels. Hence, whether a relationship holds in the natural environment is poorly understood, especially in exploited marine ecosystems. Using large-scale observations of marine fish communities, we applied a structural equation modelling framework to investigate the existence and significance of BEF relationships across northwestern European seas. We find that ecosystem functioning, here represented by spatial patterns in total fish biomass, is unrelated to species richness-the most commonly used diversity metric in BEF studies. Instead, community evenness, differences in species composition, and abiotic variables are significant drivers. In particular, we find that high fish biomass is associated with fish assemblages dominated by a few generalist species of a high trophic level, who are able to exploit both the benthic and pelagic energy pathway. Our study provides a better understanding of the mechanisms behind marine ecosystem functioning and allows for the integration of biodiversity into management considerations.