Evaluating Impact Using Time-Series Data

Accelerated farmland bird population declines in European countries after their recent EU accession

Agricultural intensification is a major driver of global biodiversity loss. In Europe, intensification progressed over the 20th century and was accelerated by instruments of the EU's Common Agricultural Policy. Central and Eastern European (CEE) countries standing outside the EU until the beginning of the 21st century employed less intensive farming and are considered one of the continent's farmland biodiversity strongholds. Their recent EU accession might be either viewed as a threat to farmland biodiversity due to the availability of funds to increase agricultural production or as an opportunity to implement conservation measures aimed to preserve biodiversity. Here we assessed these possibilities using long-term monitoring data on farmland bird populations in seven CEE countries. We tested whether mean relative abundance and population trends changed after countries' EU accession, and whether such changes also occurred in agricultural management and conservation measures. Both agricultural intensity and spending for agri-environmental and climatic schemes increased when the CEE countries joined the EU. At the same time, farmland bird populations started to decline and their relative abundance was lower after than before EU accession. In addition, increases in fertilizer application were negatively associated with annual changes in relative farmland bird population sizes, indicating a negative impact of intensive agriculture. Taken together, these results indicate that despite the great power of the EU's environmental legislation to improve the population status of species at risk, this does not apply to farmland birds. In their case, the adverse impacts of agricultural intensification most likely overrode the possible benefits of conservation measures. To secure this region as one of the continent's farmland biodiversity strongholds, policy and management actions are urgently needed.

Combined measures in lake restoration - A powerful approach as exemplified from Lake Groote Melanen (the Netherlands)

Controlling lake eutrophication is a challenge. A case-specific diagnostics driven approach is recommended that will guide to a suite of measures most promising in restoration of eutrophic lakes as exemplified by the case of the shallow lake Groote Melanen, The Netherlands. A lake system analysis identified external and internal nutrient load as main reasons for poor water quality and reoccurring cyanobacterial blooms in the lake. Based on this analysis, a package of restoration measures was implemented between January 2015 and May 2016. These measures included fish removal, dredging, capping of peat rich sediment with sand and an active barrier (lanthanum-modified bentonite), diversion of two inlet streams, reconstruction of banks, and planting macrophytes. Dredging and sand capping caused temporarily elevated turbidity and suspended solids concentrations, while addition of the lanthanum-modified clay caused a temporary exceedance of the Dutch La standard for freshwaters. Diversion of inflow streams caused 35 % less water inflow and larger water level fluctuations, but the lake remained water transporting with strongly improved water quality as was revealed by comparing five years pre-intervention water quality data with five years' post-intervention data. Total phosphorus concentration in the water column was reduced by 93 % from 0.47 mg P l-1 before the intervention to 0.03 mg P l-1 after the intervention, total nitrogen by 66 % from 1.27 to 0.21 mg N l-1, total chlorophyll-a by 75 % from 68 to 16 µg l-1, cyanobacteria chlorophyll-a by 88 % from 32 to 4 µg l-1. Turbidity had declined by 58 % from 23.5 FTU to on average 9.9 FTU. No cyanobacteria blooms were recorded over the entire post-intervention monitoring period (2016-2021). Submerged macrophytes increased from complete absence before intervention to around 10 %-15 % coverage after intervention. Repeated fish removal lowered the fish stock to below 100 kg ha-1 with 12 % of bream and carp remaining. Hence, the package of cohesive measures that was based on a thorough diagnosis resulted in rapidly, strongly and enduringly improved water quality. This case provides evidence for the power of combining measures in restoring eutrophic lakes.

Evaluating the effectiveness of mitigation measures in environmental impact assessments: A comprehensive review of development projects in Korea

Rapid urbanization and development projects in Korea have posed significant threats to biodiversity; thus, effective mitigation measures are required to preserve natural habitats. Nevertheless, the factors underlying variations in mitigation measure effectiveness according to the disturbance level and surrounding environmental conditions have not been clarified. This study evaluated the effectiveness of mitigation measures implemented in environmental impact assessments (EIAs) of development projects in Korea, with a focus on their effectiveness with respect to the disturbance level and surrounding environmental conditions. A review of 288 EIA reports from selected projects that implemented all 10 mitigation measures classified according to the Wildlife Conservation Comprehensive Plan was conducted. Using the biodiversity tipping point framework, the effects of mitigation measures on biodiversity were categorized into four levels and analyzed. Analysis of variance and redundancy analysis were then performed to discern the variance in mitigation measure effectiveness in terms of the disturbance level, surrounding environment, and species. The results revealed significant variations in the effectiveness of mitigation measures depending on the surrounding environment and disturbance level. Linear projects exhibited a clear impact on various species as the disturbance level increased, whereas area-based projects did not exhibit such pronounced effects. All species demonstrated a negative relationship with development duration, development area, and distance from urban centers. Notably, avian and amphibian species showed a strong negative correlation with the digital elevation model while reptiles and mammals exhibited a strong positive relationship with pre-development biodiversity and distance from protected areas, respectively. Mitigation measures play a key role in alleviating the adverse effects of development projects; therefore, our findings indicate the need for spatially tailored mitigation plans to augment their effectiveness.

The positive impact of conservation action

Governments recently adopted new global targets to halt and reverse the loss of biodiversity. It is therefore crucial to understand the outcomes of conservation actions. We conducted a global meta-analysis of 186 studies (including 665 trials) that measured biodiversity over time and compared outcomes under conservation action with a suitable counterfactual of no action. We find that in two-thirds of cases, conservation either improved the state of biodiversity or at least slowed declines. Specifically, we find that interventions targeted at species and ecosystems, such as invasive species control, habitat loss reduction and restoration, protected areas, and sustainable management, are highly effective and have large effect sizes. This provides the strongest evidence to date that conservation actions are successful but require transformational scaling up to meet global targets.

Global monitoring for biodiversity: Uncertainty, risk, and power analyses to support trend change detection

Global targets aim to reverse biodiversity declines by 2050 but require knowledge of current trends and future projections under policy intervention. First, given uncertainty in measurement of current trends, we propose a risk framework, considering probability and magnitude of decline. While only 11 of 198 systems analyzed (taxonomic groups by country from the Living Planet Database) showed declining abundance with high certainty, 20% of systems had a 70% chance of strong declines. Society needs to decide acceptable risks of biodiversity loss. Second, we calculated statistical power to detect trend change using ~12,000 populations from 62 systems currently showing strong declines. Current trend uncertainty hinders our ability to assess improvements. Trend change is detectable with high certainty in only 14 systems, even if thousands of populations are sampled, and conservation action reduces net declines to zero immediately, on average. We provide potential solutions to improve monitoring of progress toward biodiversity targets.

Swimmer's itch control: Timely waterfowl brood relocation significantly reduces an avian schistosome population and human cases on recreational lakes

Swimmer's itch (SI) is a dermatitis in humans caused by cercariae of avian and mammalian schistosomes which emerge from infected snails on a daily basis. Mitigation methods for SI have long been sought with little success. Copper sulfate application to the water to kill the snail hosts is the historically employed method, but is localized, temporary, and harmful to many aquatic species. Here, we test an alternative method to control Trichobilharzia stagnicolae, a species well-known to cause SI in northern Michigan and elsewhere in North America. Summer relocation of broods of the only known vertebrate host, common merganser (Mergus merganser), greatly reduced snail infection prevalence the following year on two large, geographically separated lakes in northern Michigan. Subsequent years of host relocation achieved and maintained snail infection prevalence at ~0.05%, more than an order of magnitude lower than pre-intervention. A Before-After-Control-Intervention (BACI) study design using multiple-year snail infection data from two intervention lakes and three control lakes demonstrates that dramatic lake-wide reduction of an avian schistosome can be achieved and is not due to natural fluctuations in the parasite populations. The relevance of reducing snail infection prevalence is demonstrated by a large seven-year data set of SI incidence in swimmers at a high-use beach, which showed a substantial reduction in SI cases in two successive years after relocation began. In addition, data from another Michigan lake where vertebrate-host based intervention occurred in the 1980's are analyzed statistically and show a remarkably similar pattern of reduction in snail infection prevalence. Together, these results demonstrate a highly effective SI mitigation strategy that avoids the use of environmentally suspect chemicals and removes incentive for lethal host removal. Biologically, the results strongly suggest that T. stagnicolae is reliant on the yearly hatch of ducklings to maintain populations at high levels on a lake and that the role of migratory hosts in the spring and fall is much less significant.

African savanna raptors show evidence of widespread population collapse and a growing dependence on protected areas

The conversion of natural habitats to farmland is a major cause of biodiversity loss and poses the greatest extinction risk to birds worldwide. Tropical raptors are of particular concern, being relatively slow-breeding apex predators and scavengers, whose disappearance can trigger extensive cascading effects. Many of Africa's raptors are at considerable risk from habitat conversion, prey-base depletion and persecution, driven principally by human population expansion. Here we describe multiregional trends among 42 African raptor species, 88% of which have declined over a ca. 20-40-yr period, with 69% exceeding the International Union for Conservation of Nature criteria classifying species at risk of extinction. Large raptors had experienced significantly steeper declines than smaller species, and this disparity was more pronounced on unprotected land. Declines were greater in West Africa than elsewhere, and more than twice as severe outside of protected areas (PAs) than within. Worryingly, species suffering the steepest declines had become significantly more dependent on PAs, demonstrating the importance of expanding conservation areas to cover 30% of land by 2030-a key target agreed at the UN Convention on Biological Diversity COP15. Our findings also highlight the significance of a recent African-led proposal to strengthen PA management-initiatives considered fundamental to safeguarding global biodiversity, ecosystem functioning and climate resilience.

Evaluating the impact of private land conservation with synthetic control design

Programs to protect biodiversity on private land are increasingly being used worldwide. To understand the efficacy of such programs, it is important to determine their impact: the difference between the program's outcome and what would have happened without the program. Typically, these programs are evaluated by estimating the average program-level impact, which readily allows comparisons between programs or regions, but masks important heterogeneity in impact across the individual conservation interventions. We used synthetic control design, statistical matching, and time-series data to estimate the impact of individual protected areas over time and combined individual-level impacts to estimate program-level impact with a meta-analytic approach. We applied the method to private protected areas governed by conservation covenants (legally binding on-title agreements to protect biodiversity) in the Goldfields region of Victoria, Australia using woody vegetation cover as our outcome variable. We compared our results with traditional approaches to estimating program-level impact based on a subset of covenants that were the same age. Our results showed an overall program-level impact of a 0.3-0.8% increase in woody vegetation cover per year. However, there was significant heterogeneity in the temporal pattern of impact for individual covenants, ranging from -4 to +7% change in woody vegetation cover per year. Results of our approach were consistent with results based on traditional approaches to estimating program-level impact. Our study provides a transparent and robust workflow to estimate individual and program-level impacts of private protected areas.

Protected areas slow declines unevenly across the tetrapod tree of life

Protected areas (PAs) are the primary strategy for slowing terrestrial biodiversity loss. Although expansion of PA coverage is prioritized under the Convention on Biological Diversity, it remains unknown whether PAs mitigate declines across the tetrapod tree of life and to what extent land cover and climate change modify PA effectiveness1,2. Here we analysed rates of change in abundance of 2,239 terrestrial vertebrate populations across the globe. On average, vertebrate populations declined five times more slowly within PAs (-0.4% per year) than at similar sites lacking protection (-1.8% per year). The mitigating effects of PAs varied both within and across vertebrate classes, with amphibians and birds experiencing the greatest benefits. The benefits of PAs were lower for amphibians in areas with converted land cover and lower for reptiles in areas with rapid climate warming. By contrast, the mitigating impacts of PAs were consistently augmented by effective national governance. This study provides evidence for the effectiveness of PAs as a strategy for slowing tetrapod declines. However, optimizing the growing PA network requires targeted protection of sensitive clades and mitigation of threats beyond PA boundaries. Provided the conditions of targeted protection, adequate governance and well-managed landscapes are met, PAs can serve a critical role in safeguarding tetrapod biodiversity.

A general framework to quantify and compare ecological impacts under temporal dynamics

Biodiversity is diminishing at alarming rates due to multiple anthropogenic drivers. To mitigate these drivers, their impacts must be quantified accurately and comparably across drivers. To enable that, we present a generally applicable framework introducing fundamental principles of ecological impact quantification, including the quantification of interactions between multiple drivers. The framework contrasts biodiversity variables in impacted against those in unimpacted or other reference situations while accounting for their temporal dynamics through modelling. Properly accounting for temporal dynamics reduces biases in impact quantification and comparison. The framework addresses key questions around ecological impacts in global change science, namely, how to compare impacts under temporal dynamics across stressors, how to account for stressor interactions in such comparisons, and how to compare the success of management actions over time.

Mixed effects of a national protected area network on terrestrial and freshwater biodiversity

Protected areas are considered fundamental to counter biodiversity loss. However, evidence for their effectiveness in averting local extinctions remains scarce and taxonomically biased. We employ a robust counterfactual multi-taxon approach to compare occupancy patterns of 638 species, including birds (150), mammals (23), plants (39) and phytoplankton (426) between protected and unprotected sites across four decades in Finland. We find mixed impacts of protected areas, with only a small proportion of species explicitly benefiting from protection-mainly through slower rates of decline inside protected areas. The benefits of protection are enhanced for larger protected areas and are traceable to when the sites were protected, but are mostly unrelated to species conservation status or traits (size, climatic niche and threat status). Our results suggest that the current protected area network can partly contribute to slow down declines in occupancy rates, but alone will not suffice to halt the biodiversity crisis. Efforts aimed at improving coverage, connectivity and management will be key to enhance the effectiveness of protected areas towards bending the curve of biodiversity loss.

Understanding 'it depends' in ecology: a guide to hypothesising, visualising and interpreting statistical interactions

Ecologists routinely use statistical models to detect and explain interactions among ecological drivers, with a goal to evaluate whether an effect of interest changes in sign or magnitude in different contexts. Two fundamental properties of interactions are often overlooked during the process of hypothesising, visualising and interpreting interactions between drivers: the measurement scale - whether a response is analysed on an additive or multiplicative scale, such as a ratio or logarithmic scale; and the symmetry - whether dependencies are considered in both directions. Overlooking these properties can lead to one or more of three inferential errors: misinterpretation of (i) the detection and magnitude (Type-D error), and (ii) the sign of effect modification (Type-S error); and (iii) misidentification of the underlying processes (Type-A error). We illustrate each of these errors with a broad range of ecological questions applied to empirical and simulated data sets. We demonstrate how meta-analysis, a widely used approach that seeks explicitly to characterise context dependence, is especially prone to all three errors. Based on these insights, we propose guidelines to improve hypothesis generation, testing, visualisation and interpretation of interactions in ecology.

Impacts of anthropogenic climate change on tropical montane forests: an appraisal of the evidence

In spite of their small global area and restricted distributions, tropical montane forests (TMFs) are biodiversity hotspots and important ecosystem services providers, but are also highly vulnerable to climate change. To protect and preserve these ecosystems better, it is crucial to inform the design and implementation of conservation policies with the best available scientific evidence, and to identify knowledge gaps and future research needs. We conducted a systematic review and an appraisal of evidence quality to assess the impacts of climate change on TMFs. We identified several skews and shortcomings. Experimental study designs with controls and long-term (≥10 years) data sets provide the most reliable evidence, but were rare and gave an incomplete understanding of climate change impacts on TMFs. Most studies were based on predictive modelling approaches, short-term (<10 years) and cross-sectional study designs. Although these methods provide moderate to circumstantial evidence, they can advance our understanding on climate change effects. Current evidence suggests that increasing temperatures and rising cloud levels have caused distributional shifts (mainly upslope) of montane biota, leading to alterations in biodiversity and ecological functions. Neotropical TMFs were the best studied, thus the knowledge derived there can serve as a proxy for climate change responses in under-studied regions elsewhere. Most studies focused on vascular plants, birds, amphibians and insects, with other taxonomic groups poorly represented. Most ecological studies were conducted at species or community levels, with a marked paucity of genetic studies, limiting understanding of the adaptive capacity of TMF biota. We thus highlight the long-term need to widen the methodological, thematic and geographical scope of studies on TMFs under climate change to address these uncertainties. In the short term, however, in-depth research in well-studied regions and advances in computer modelling approaches offer the most reliable sources of information for expeditious conservation action for these threatened forests.

Evaluating the impact of biodiversity offsetting on native vegetation

Biodiversity offsetting is a globally influential policy mechanism for reconciling trade-offs between development and biodiversity loss. However, there is little robust evidence of its effectiveness. We evaluated the outcomes of a jurisdictional offsetting policy (Victoria, Australia). Offsets under Victoria's Native Vegetation Framework (2002-2013) aimed to prevent loss and degradation of remnant vegetation, and generate gains in vegetation extent and quality. We categorised offsets into those with near-complete baseline woody vegetation cover ("avoided loss", 2702 ha) and with incomplete cover ("regeneration", 501 ha), and evaluated impacts on woody vegetation extent from 2008 to 2018. We used two approaches to estimate the counterfactual. First, we used statistical matching on biophysical covariates: a common approach in conservation impact evaluation, but which risks ignoring potentially important psychosocial confounders. Second, we compared changes in offsets with changes in sites that were not offsets for the study duration but were later enrolled as offsets, to partially account for self-selection bias (where landholders enrolling land may have shared characteristics affecting how they manage land). Matching on biophysical covariates, we estimated that regeneration offsets increased woody vegetation extent by 1.9%-3.6%/year more than non-offset sites (138-180 ha from 2008 to 2018) but this effect weakened with the second approach (0.3%-1.9%/year more than non-offset sites; 19-97 ha from 2008 to 2018) and disappeared when a single outlier land parcel was removed. Neither approach detected any impact of avoided loss offsets. We cannot conclusively demonstrate whether the policy goal of 'net gain' (NG) was achieved because of data limitations. However, given our evidence that the majority of increases in woody vegetation extent were not additional (would have happened without the scheme), a NG outcome seems unlikely. The results highlight the importance of considering self-selection bias in the design and evaluation of regulatory biodiversity offsetting policy, and the challenges of conducting robust impact evaluations of jurisdictional biodiversity offsetting policies.

Prediction and analysis of time series data based on granular computing

The advent of the Big Data era and the rapid development of the Internet of Things have led to a dramatic increase in the amount of data from various time series. How to classify, correlation rule mining and prediction of these large-sample time series data has a crucial role. However, due to the characteristics of high dimensionality, large data volume and transmission lag of sensor data, large sample time series data are affected by multiple factors and have complex characteristics such as multi-scale, non-linearity and burstiness. Traditional time series prediction methods are no longer applicable to the study of large sample time series data. Granular computing has unique advantages in dealing with continuous and complex data, and can compensate for the limitations of traditional support vector machines in dealing with large sample data. Therefore, this paper proposes to combine granular computing theory with support vector machines to achieve large-sample time series data prediction. Firstly, the definition of time series is analyzed, and the basic principles of traditional time series forecasting methods and granular computing are investigated. Secondly, in terms of predicting the trend of data changes, it is proposed to apply the fuzzy granulation algorithm to first convert the sample data into coarser granules. Then, it is combined with a support vector machine to predict the range of change of continuous time series data over a period of time. The results of the simulation experiments show that the proposed model is able to make accurate predictions of the range of data changes in future time periods. Compared with other prediction models, the proposed model reduces the complexity of the samples and improves the prediction accuracy.

Progress in understanding the vulnerability of freshwater ecosystems

The ability to collect and synthesize long-term environmental monitoring data is essential for the effective management of freshwater ecosystems. Progress has been made in assessment and monitoring approaches that have integrated routine monitoring programs into more holistic watershed-scale vulnerability assessments. While the concept of vulnerability assessment is well-defined for ecosystems, complementary and sometimes competing concepts of adaptive management, ecological integrity, and ecological condition complicate the communication of results to a broader audience. Here, we identify progress in freshwater assessments that can contribute to the identification and communication of freshwater vulnerability. We review novel methods that address common challenges associated with: 1) a lack of baseline information, 2) variability associated with a spatial context, and 3) the taxonomic sufficiency of biological indicators used to make inferences about ecological conditions. Innovation in methods and communication are discussed as a means to highlight meaningful cost-effective results that target policy towards heuristic ecosystem-management.

A predictive timeline of wildlife population collapse

Contemporary rates of biodiversity decline emphasize the need for reliable ecological forecasting, but current methods vary in their ability to predict the declines of real-world populations. Acknowledging that stressor effects start at the individual level, and that it is the sum of these individual-level effects that drives populations to collapse, shifts the focus of predictive ecology away from using predominantly abundance data. Doing so opens new opportunities to develop predictive frameworks that utilize increasingly available multi-dimensional data, which have previously been overlooked for ecological forecasting. Here, we propose that stressed populations will exhibit a predictable sequence of observable changes through time: changes in individuals' behaviour will occur as the first sign of increasing stress, followed by changes in fitness-related morphological traits, shifts in the dynamics (for example, birth rates) of populations and finally abundance declines. We discuss how monitoring the sequential appearance of these signals may allow us to discern whether a population is increasingly at risk of collapse, or is adapting in the face of environmental change, providing a conceptual framework to develop new forecasting methods that combine multi-dimensional (for example, behaviour, morphology, life history and abundance) data.

Rare and declining bird species benefit most from designating protected areas for conservation in the UK

There have been recent renewed commitments to increase the extent of protected areas to combat the growing biodiversity crisis but the underpinning evidence for their effectiveness is mixed and causal connections are rarely evaluated. We used data gathered by three large-scale citizen science programmes in the UK to provide the most comprehensive assessment to date of whether national (Sites of Special Scientific Interest) and European (Special Protection Areas/Special Areas of Conservation) designated areas are associated with improved state (occurrence, abundance), change (rates of colonization, persistence and trend in abundance), community structure and, uniquely, demography (productivity) on a national avifauna, while controlling for differences in land cover, elevation and climate. We found positive associations with state that suggest these areas are well targeted and that the greatest benefit accrued to the most conservation-dependent species since positive associations with change were largely restricted to rare and declining species and habitat specialists. We suggest that increased productivity provides a plausible demographic mechanism for positive effects of designation.

Measuring the Impact of Conservation: The Growing Importance of Monitoring Fauna, Flora and Funga

Many stakeholders, from governments to civil society to businesses, lack the data they need to make informed decisions on biodiversity, jeopardising efforts to conserve, restore and sustainably manage nature. Here we review the importance of enhancing biodiversity monitoring, assess the challenges involved and identify potential solutions. Capacity for biodiversity monitoring needs to be enhanced urgently, especially in poorer, high-biodiversity countries where data gaps are disproportionately high. Modern tools and technologies, including remote sensing, bioacoustics and environmental DNA, should be used at larger scales to fill taxonomic and geographic data gaps, especially in the tropics, in marine and freshwater biomes, and for plants, fungi and invertebrates. Stakeholders need to follow best monitoring practices, adopting appropriate indicators and using counterfactual approaches to measure and attribute outcomes and impacts. Data should be made openly and freely available. Companies need to invest in collecting the data required to enhance sustainability in their operations and supply chains. With governments soon to commit to the post-2020 global biodiversity framework, the time is right to make a concerted push on monitoring. However, action at scale is needed now if we are to enhance results-based management adequately to conserve the biodiversity and ecosystem services we all depend on.

Inferring causal impacts of extreme water-level drawdowns on lake water clarity using long-term monitoring data

Although long-term ecosystem monitoring provides essential knowledge for practicing ecosystem management, analyses of the causal effects of ecological impacts from large-scale observational data are still in an early stage of development. We used causal impact analysis (CIA)-a synthetic control method that enables estimation of causal impacts from unrepeated, long-term observational data-to evaluate the causal impacts of extreme water-level drawdowns during summer on subsequent water quality. We used more than 100 years of transparency and water level monitoring data from Lake Biwa, Japan. The results of the CIA showed that the most extreme drawdown in recorded history, which occurred in 1994, had a significant positive effect on transparency (a maximum increase of 1.75 m on average over the following year) in the north basin of the lake. The extreme drawdown in 1939 was also shown to be a trigger for an increase in transparency in the north basin, whereas that in 1984 had no significant effects on transparency. In the south basin, contrary to the pattern in the north basin, the extreme drawdown had a significant negative effect on transparency shortly after the extreme drawdown. These different impacts of the extreme drawdowns were considered to be affected by the timing and magnitude of the extreme drawdowns and the depths of the basins. Our approach of inferring the causal impacts of past events on ecosystems will be helpful in implementing water-level management for ecosystem management and improving water quality in lakes.

Feeding behavior innovation increases foraging efficiency in the Amur falcon but may be a threat to Asian particolored bats

Behavioral innovations are rare and infrequent in the natural world, but they are pivotal for animals to respond to environmental changes. The ecological benefits of these innovations remain unknown, especially in wild populations. Here, two foraging strategies and three eating behaviors of the Amur falcon (Falco amurensis) were observed during predation on Asian particolored bats (Vespertilio sinensis) across 3 years. We demonstrated that an eating behavioral innovation in F. amurensis increased the foraging efficiency of V. sinensis more than twofold during 3 consecutive years. This showed that changes in feeding behavior by a bird strongly influenced the rate of energy intake. Since predation on bats by falcons mainly occurred during the lactation and post-lactation of bats, this may have a certain level of negative effect on the bat population.

Metagenomics to characterize sediment microbial biodiversity associated with fishing exposure within the Stellwagen Bank National Marine Sanctuary

Microbes in marine sediments constitute a large percentage of the global marine ecosystem and function to maintain a healthy food web. In continental shelf habitats such as the Gulf of Maine (GoM), relatively little is known of the microbial community abundance, biodiversity, and natural product potential. This report is the first to provide a time-series assessment (2017–2020) of the sediment microbial structure in areas open and closed to fishing within the Stellwagen Bank National Marine Sanctuary (SBNMS). A whole metagenome sequencing (WMS) approach was used to characterize the sediment microbial community. Taxonomic abundance was calculated across seven geographic sites with 14 individual sediment samples collected during the summer and fall seasons. Bioinformatics analyses identified more than 5900 different species across multiple years. Non-metric multidimensional scaling methods and generalized linear models demonstrated that species richness was inversely associated with fishing exposure levels and varied by year. Additionally, the discovery of 12 unique biosynthetic gene clusters (BGCs) collected across sites confirmed the potential for medically relevant natural product discovery in the SBNMS. This study provides a practical assessment of how fishing exposure and temporal trends may affect microbial community structure in a coastal marine sanctuary.

Linking key human-environment theories to inform the sustainability of coral reefs

Effective solutions to the ongoing "coral reef crisis" will remain limited until the underlying drivers of coral reef degradation are better understood. Here, we conduct a global-scale study of how four key metrics of ecosystem states and processes on coral reefs (top predator presence, reef fish biomass, trait diversity, and parrotfish scraping potential) are explained by 11 indicators based on key human-environment theories from the social sciences. Our global analysis of >1,500 reefs reveals three key findings. First, the proximity of the nearest market has the strongest and most consistent relationships with these ecosystem metrics. This finding is in keeping with a body of terrestrial research on how market accessibility shapes agricultural practices, but the integration of these concepts in marine systems is nascent. Second, our global study shows that resource conditions tend to display a n-shaped relationship with socioeconomic development. Specifically, the probabilities of encountering a top predator, fish biomass, and fish trait diversity were highest where human development was moderate but lower where development was either high or low. This finding contrasts with previous regional-scale research demonstrating an environmental Kuznets curve hypothesis (which predicts a U-shaped relationship between socioeconomic development and resource conditions). Third, together, our ecosystem metrics are best explained by the integration of different human-environment theories. Our best model includes the interactions between indicators from different theoretical perspectives, revealing how marine reserves can have different outcomes depending on how far they are from markets and human settlements, as well as the size of the surrounding human population.

Protected areas have a mixed impact on waterbirds, but management helps

International policy is focused on increasing the proportion of the Earth's surface that is protected for nature^1,2. Although studies show that protected areas prevent habitat loss^3-6, there is a lack of evidence for their effect on species' populations: existing studies are at local scale or use simple designs that lack appropriate controls^7-13. Here we explore how 1,506 protected areas have affected the trajectories of 27,055 waterbird populations across the globe using a robust before-after control-intervention study design, which compares protected and unprotected populations in the years before and after protection. We show that the simpler study designs typically used to assess protected area effectiveness (before-after or control-intervention) incorrectly estimate effects for 37-50% of populations-for instance misclassifying positively impacted populations as negatively impacted, and vice versa. Using our robust study design, we find that protected areas have a mixed impact on waterbirds, with a strong signal that areas managed for waterbirds or their habitat are more likely to benefit populations, and a weak signal that larger areas are more beneficial than smaller ones. Calls to conserve 30% of the Earth's surface by 2030 are gathering pace¹⁴, but we show that protection alone does not guarantee good biodiversity outcomes. As countries gather to agree the new Global Biodiversity Framework, targets must focus on creating and supporting well-managed protected and conserved areas that measurably benefit populations.

Causal assumptions and causal inference in ecological experiments

Causal inferences from experimental data are often justified based on treatment randomization. However, inferring causality from data also requires complementary causal assumptions, which have been formalized by scholars of causality but not widely discussed in ecology. While ecologists have recognized challenges to inferring causal relationships in experiments and developed solutions, they lack a general framework to identify and address them. We review four assumptions required to infer causality from experiments and provide design-based and statistically based solutions for when these assumptions are violated. We conclude that there is no clear demarcation between experimental and non-experimental designs. This insight can help ecologists design better experiments and remove barriers between experimental and observational scholarship in ecology.

Random population fluctuations bias the Living Planet Index

The Living Planet Index (LPI) is a standardized indicator for tracking population trends through time. Due to its ability to aggregate many time series in a single metric, the LPI has been proposed as an indicator for the Convention on Biological Diversity's post-2020 Global Biodiversity Strategy. However, here we show that random population fluctuations introduce biases when calculating the LPI. By combining simulated and empirical data, we show how random fluctuations lead to a declining LPI even when overall population trends are stable and imprecise estimates of the LPI when populations increase or decrease nonlinearly. We applied randomization null models that demonstrate how random fluctuations exaggerate declines in the global LPI by 9.6%. Our results confirm substantial declines in the LPI but highlight sources of uncertainty in quantitative estimates. Randomization null models are useful for presenting uncertainty around indicators of progress towards international biodiversity targets.

Raptor research during the COVID-19 pandemic provides invaluable opportunities for conservation biology

Research is underway to examine how a wide range of animal species have responded to reduced levels of human activity during the COVID-19 pandemic. In this perspective article, we argue that raptors (i.e., the orders Accipitriformes, Cariamiformes, Cathartiformes, Falconiformes, and Strigiformes) are particularly well-suited for investigating potential 'anthropause' effects: they are sensitive to environmental perturbation, affected by various human activities, and include many locally and globally threatened species. Lockdowns likely alter extrinsic factors that normally limit raptor populations. These environmental changes are in turn expected to influence - mediated by behavioral and physiological responses - the intrinsic (demographic) factors that ultimately determine raptor population levels and distributions. Using this population-limitation framework, we identify a range of research opportunities and conservation challenges that have arisen during the pandemic, related to changes in human disturbance, light and noise pollution, collision risk, road-kill availability, supplementary feeding, and persecution levels. Importantly, raptors attract intense research interest, with many professional and amateur researchers running long-term monitoring programs, often incorporating community-science components, advanced tracking technology and field-methodological approaches that allow flexible timing, enabling continued data collection before, during, and after COVID-19 lockdowns. To facilitate and coordinate global collaboration, we are hereby launching the 'Global Anthropause Raptor Research Network' (GARRN). We invite the international raptor research community to join this inclusive and diverse group, to tackle ambitious analyses across geographic regions, ecosystems, species, and gradients of lockdown perturbation. Under the most tragic of circumstances, the COVID-19 anthropause has afforded an invaluable opportunity to significantly boost global raptor conservation.

Impacts of invasive quagga mussels (Dreissena rostriformis bugensis) on reservoir water quality, as revealed by progressive-change BACIPS analysis

Invasive quagga mussels (Dreissena rostriformis bugensis) are an emerging threat to the functioning and management of freshwater ecosystems. Quagga mussels were first recorded in the UK in 2014 and have subsequently established at high densities in a number of major reservoirs. Through implementing a Progressive-Change BACIPS (Before-After-Control-Impact Paired Series) analysis, we found that the following trends were observed following quagga mussel establishment: reduced diatom and cyanobacteria abundances; increased soluble reactive phosphorus and reactive silica concentrations; and reduced abundances of Aphanizomenon sp., a potentially toxic cyanobacterium. We also found reservoirs with established quagga mussel populations experienced slightly increased overall chlorophyll a concentration but no changes in turbidity or Microcystis sp. abundance, which are often considered common indicators of dreissenid invasion. Our results show that Progressive-Change BACIPS analysis is a powerful tool which can be used to interrogate industry standard long-term datasets of water quality metrics in order to identify and quantify the impacts of invasive species when the approximate timeframe of species arrival is known. We also demonstrate that quagga mussels may have had significant effects on reservoir ecosystems which, primarily through their impacts on phytoplankton communities, may have implications for reservoir management.