There is increasing interest in the effectiveness of protected areas (PAs) for supporting populations of wildlife. While there are a number of association studies showing a relationship between protected areas and abundance or trends in wild species, studies with an appropriate counterfactual (what would have happened in the absence of protection) are rare. We use the world’s largest database on waterbird counts (covering 587 species at 21,989 sites globally) to answer three questions: 1) Do PAs have a positive impact on waterbird population trends relative to a counterfactual (this includes cases where a PA has lessened, but not halted, a population decline)?; 2) are PAs performing successfully by maintaining or increasing populations? and 3) what factors contribute to PA impact and performance? We selected 15,703 waterbird populations (here defined as a site species combination), consisting of 311 species at 870 protected sites, where PA designation occurred at least 5 years after the first survey date, and 5 years before the last. We will use this to compare trends before PA designation to those afterwards. We then matched these sites to unprotected sites with similar covariates in the years before PA designation, resulting in a matching dataset of 6,451 populations pairs consisting of 39 species at 769 pairs of protected and unprotected sites. We will use this to compare trends both before and after PA designation and inside and outside of PAs. Our results will shed light on the impact of PA on hundreds of waterbird species, providing much needed evidence regarding PA effectiveness. As PA performance is a sensitive subject and it is important to develop hypotheses before knowing the results (especially for the relatively complex data analysis used in matching protected and unprotected sites), we present a pre-analysis plan. This will ensure that the final paper’s analyses are hypotheses testing, rather than generating, and avoids the risk of, or perception of, data dredging.

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of an ecological community is supported by its underlying network of species interactions. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, only small subsets of these networks can be monitored. There is therefore an urgent need to establish links between the small snapshots of data conservationists can collect, and the “big picture” conclusions about ecosystem health demanded by policymakers, scientists, and societies. Here, we show that the persistence of small subnetworks (motifs) in isolation—that is, their persistence when considered separately from the larger network of which they are a part—is a reliable probabilistic indicator of the persistence of the network as a whole. Our methods show that it is easier to detect if an ecological community is not persistent than if it is persistent, allowing for rapid detection of extinction risk in endangered systems. Our results also justify the common practice of predicting ecological persistence from incomplete surveys by simulating the population dynamics of sampled subnetworks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies.

Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e. berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-2005 (21 studies), 2006-2010 (40), 2011-2015 (88), and 2016-2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e. proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA).

A ubiquitous pattern in ecological systems is that more abundant species tend to be more generalist; that is, they interact with more species or can occur in wider range of habitats. However, there is no consensus on whether generalism drives abundance (a selection process) or abundance drives generalism (a drift process). As it is difficult to conduct direct experiments to solve this chicken-and-egg dilemma, previous studies have used a causal discovery method based on formal logic and have found that abundance drives generalism. Here, we refine this method by correcting its bias regarding skewed distributions, and employ two other independent causal discovery methods based on nonparametric regression and on information theory, respectively. Contrary to previous work, all three independent methods strongly indicate that generalism drives abundance when applied to datasets on plant-hummingbird communities and reef fishes. Furthermore, we find that selection processes are more important than drift processes in structuring multispecies systems when the environment is variable. Our results showcase the power of the computational causal discovery approach to aid ecological research.

Aim: Mutualistic interactions between plants and animals are fundamental for the maintenance of natural communities and the ecosystem services they provide. However, particularly in human-dominated island ecosystems, introduced species may alter mutualistic interactions. Based on an extensive dataset of plant–frugivore interactions, we mapped and analysed a meta-network across the Caribbean archipelago. Specifically, we searched for subcommunity structure (modularity) and identified the types of species facilitating the integration of introduced species in the Caribbean meta-network. Location: Caribbean archipelago (Lucayan archipelago, Greater Antilles, Lesser Antilles). Methods: We reviewed published scientific literature, unpublished theses and other nonpeer-reviewed sources to compile an extensive dataset of plant–frugivore interactions. We visualized spatial patterns and conducted a modularity analysis of the cross-island meta-network. We also examined which species were most likely to interact with introduced species: (1) endemic, nonendemic native or introduced species, and (2) generalized or specialized species. Results: We reported 3060 records of interactions between 486 plant and 178 frugivore species. The Caribbean meta-network was organized in 13 modules, driven by a combination of functional or taxonomic (modules dominated by certain groups of frugivores) and biogeographical (island-specific modules) mechanisms. Few introduced species or interaction pairs were shared across islands, suggesting little homogenization of the plant–frugivore meta-network at the regional scale. However, we found evidence of “invader complexes,” as introduced frugivores were more likely to interact with introduced plants than expected at random. Moreover, we found generalist species more likely to interact with introduced species than were specialized species. Main conclusions: These results demonstrate that generalist species and “invader complexes” may facilitate the incorporation of introduced species into plant–frugivore communities. Despite the influx of introduced species, the meta-network was structured into modules related to biogeographical and functional or taxonomic affinities. These findings reveal how introduced species become an integral part of mutualistic systems on tropical islands.

International policy is focused on increasing the proportion of the Earth's surface that is protected for nature1,2. Although studies show that protected areas prevent habitat loss3-6, 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 controls7-13. 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.

Climate change is forcing the redistribution of life on Earth at an unprecedented velocity1,2. Migratory birds are thought to help plants to track climate change through long-distance seed dispersal3,4. However, seeds may be consistently dispersed towards cooler or warmer latitudes depending on whether the fruiting period of a plant species coincides with northward or southward migrations. Here we assess the potential of plant communities to keep pace with climate change through long-distance seed dispersal by migratory birds. To do so, we combine phenological and migration information with data on 949 seed-dispersal interactions between 46 bird and 81 plant species from 13 woodland communities across Europe. Most of the plant species (86%) in these communities are dispersed by birds migrating south, whereas only 35% are dispersed by birds migrating north; the latter subset is phylogenetically clustered in lineages that have fruiting periods that overlap with the spring migration. Moreover, the majority of this critical dispersal service northwards is provided by only a few Palaearctic migrant species. The potential of migratory birds to assist a small, non-random sample of plants to track climate change latitudinally is expected to strongly influence the formation of novel plant communities, and thus affect their ecosystem functions and community assembly at higher trophic levels.

© 2020 the Author(s) Published by the Royal Society. All rights reserved. Interactions between species are influenced by different ecological mechanisms, such as morphological matching, phenological overlap and species abundances. How these mechanisms explain interaction frequencies across environmental gradients remains poorly understood. Consequently, we also know little about the mechanisms that drive the geographical patterns in network structure, such as complementary specialization and modularity. Here, we use data on morphologies, phenologies and abundances to explain interaction frequencies between hummingbirds and plants at a large geographical scale. For 24 quantitative networks sampled throughout the Americas, we found that the tendency of species to interact with morphologically matching partners contributed to specialized and modular network structures. Morphological matching best explained interaction frequencies in networks found closer to the equator and in areas with low-temperature seasonality. When comparing the three ecological mechanisms within networks, we found that both morphological matching and phenological overlap generally outperformed abundances in the explanation of interaction frequencies. Together, these findings provide insights into the ecological mechanisms that underlie geographical patterns in resource specialization. Notably, our results highlight morphological constraints on interactions as a potential explanation for increasing resource specialization towards lower latitudes.

© 2020 Conservation science is a crisis-oriented discipline focused on reducing human impacts on nature. To explore how the field has changed over the past two decades, we analyzed 3245 applications for oral presentations submitted to the Student Conference on Conservation Science (SCCS) in Cambridge, UK. SCCS has been running every year since 2000, aims for global representation by providing bursaries to early-career conservationists from lower-income countries, and has never had a thematic focus, beyond conservation in the broadest sense. We found that the majority of projects submitted to SCCS were based on primary biological data collected from local scale field studies in the tropics, contrary to established literature which highlights gaps in tropical research. Our results showed a small increase over time in submissions framed around how nature benefits people as well as a small increase in submissions integrating social science. Our findings suggest that students and early-career conservationists could provide pathways to increase availability of data from the tropics and address well-known biases in the published literature towards wealthier countries. We hope this research will motivate efforts to support student projects, ensuring data and results are published and data made publicly available.

Pollination by wild pollinators is a key ecosystem service threatened by anthropogenic-induced land-use change. The proximity to natural habitat has previously been shown to positively affect pollinator communities and improve crop yield and quality but empirical evidence is limited from most parts of the World. Here, across six farms in Southern Thailand, we investigated the significance of landscape-level effects of natural habitat (proportion of and distance to evergreen forest) on both visitation rate and richness of pollinators as well as fruit set of guava (Psidium guajava L.), a local economically-important crop in the tropics. Overall, the most abundant pollinator was the Asian honey bee Apis cerana (39% of all visits) and different species of stingless bees (37%). We found that pollinator richness was unrelated to the proportion and distance to evergreen forest, however, the proportion of forest within a 1, 5 and 10 km radius had a significant positive impact on visitation rate of wild pollinators. Still, neither the various forest parameters nor pollinator visitation rate showed a significant impact on fruit set of guava, perhaps because guava self-pollinates. This illustrates that landscape-level degradation of natural habitat may negatively impact pollinator communities without diminishing the crop yield of the farmers.

AbstractIndirect interactions are central to ecological and evolutionary dynamics in pollination communities, yet we have little understanding about the processes determining patterns of indirect interactions, such as those between pollinators through shared flowering plants. Instead, research has concentrated on the processes responsible for direct interactions and whole-network structures. This is partly due to a lack of appropriate tools for characterising indirect interaction structures, because traditional network metrics discard much of this information. The recent development of tools for counting motifs (subnetworks depicting interactions between a small number of species) in bipartite networks enable detailed analysis of indirect interaction patterns. Here we generate plant-hummingbird pollination networks based on three major assembly processes – neutral effects (species interacting in proportion to abundance), morphological matching and phenological overlap – and evaluate the motifs associated with each one. We find that different processes produce networks with significantly different patterns of indirect interactions. Neutral effects tend to produce densely-connected motifs, with short indirect interaction chains, and motifs where many specialists interact indirectly through a single generalist. Conversely, niche-based processes (morphology and phenology) produced motifs with a core of interacting generalists, supported by peripheral specialists. These results have important implications for understanding the processes determining indirect interaction structures.

Scientific knowledge is considered to be an important factor (alongside others) in environmental policy-making. However, the opportunity for environmentalists to influence policy can often occur within short, discrete time windows. Therefore, a piece of research may have a negligible or transformative policy influence depending on when it is presented. These ‘policy windows’ are sometimes predictable, such as those dealing with conventions or legislation with a defined renewal period, but are often hard to anticipate. We describe four ways that environmentalists can respond to policy windows and increase the likelihood of knowledge uptake: 1) foresee (and create) emergent windows, 2) respond quickly to opening windows, 3) frame research in line with appropriate windows, and 4) persevere in closed windows. These categories are closely linked; efforts to enhance the incorporation of scientific knowledge into policy need to harness mechanisms within each. We illustrate the main points with reference to nature conservation, but the principles apply widely.

AbstractEvidence-based conservation relies on robust and relevant evidence. Practitioners often prefer locally relevant studies whose results are more likely to be transferable to the context of planned conservation interventions. To quantify the availability of relevant evidence for amphibian and bird conservation we reviewed Conservation Evidence, a database of quantitative tests of conservation interventions. Studies were geographically clustered and found at extremely low densities - fewer than one study was present within a 2,000 km radius of a given location. The availability of relevant evidence was extremely low when we restricted studies to those studying biomes or taxonomic orders containing high percentages of threatened species, compared to the most frequently studied biomes and taxonomic orders. Further constraining the evidence by study design showed that only 17-20% of amphibian and bird studies used robust designs. Our results highlight the paucity of evidence on the effectiveness of conservation interventions, and the disparity in evidence for local contexts that are frequently studied and those where conservation needs are greatest. Addressing the serious global shortfall in context-specific evidence requires a step change in the frequency of testing conservation interventions, greater use of robust study designs and standardized metrics, and methodological advances to analyze patchy evidence bases.

AbstractNestedness is a widespread pattern in mutualistic networks that has high ecological and evolutionary importance due to its role in enhancing species persistence and community stability. Nestedness measures tend to be correlated with fundamental properties of networks, such as size and connectance, and so nestedness values must be normalised to enable fair comparisons between different ecological communities. Current approaches, such as using null-corrected nestedness values andz-scores, suffer from extensive statistical issues. Thus a new approach called NODFcwas recently proposed, where nestedness is expressed relative to network size, connectance and the maximum nestedness that could be achieved in a particular network. While this approach is demonstrably effective in overcoming the issues of collinearity with basic network properties, it is computationally intensive to calculate, and current approaches are too slow to be practical for many types of analysis, or for analysing large networks.We developed three highly-optimised algorithms, based on greedy, hillclimbing and simulated annealing approaches, for calculation of NODFc, spread along a speed-quality continuum. Users thus have the choice between a fast algorithm with a less accurate estimate, a slower algorithm with a more accurate estimate, and an intermediate option.We outline the package, and its implementation, as well as provide comparative performance benchmarking and two example analyses. We show thatmaxnodfenables speed increases of hundreds of times faster than existing approaches, with large networks seeing the biggest improvements. For example, for a large network with 3000 links, computation time was reduced from 50 minutes using the fastest existing algorithm to 11 seconds usingmaxnodf.maxnodfmakes correctly-normalised nestedness measures feasible for complex analyses of even large networks. Analyses that would previously take weeks to complete can now be finished in hours or even seconds. Given evidence that correctly normalising nestedness values can significantly change the conclusions of ecological studies, we believe this package will usher in necessary widespread use of appropriate comparative nestedness statistics.

Abstract


Bipartite networks are widely used to represent a diverse range of species interactions, such as pollination, herbivory, parasitism and seed dispersal. The structure of these networks is usually characterised by calculating one or more indices that capture different aspects of network architecture. While these indices capture useful properties of networks, they are relatively insensitive to changes in network structure. Consequently, variation in ecologically‐important interactions can be missed. Network motifs are a way to characterise network structure that is substantially more sensitive to changes in pairwise interactions and is gaining in popularity. However, there is no software available in R, the most popular programming language among ecologists, for conducting motif analyses in bipartite networks. Similarly, no mathematical formalisation of bipartite motifs has been developed.

Here we introduce bmotif: a package for motif analyses of bipartite networks. Our code is primarily an r package, but we also provide matlab and Python code of the core functionality. The software is based on a mathematical framework where, for the first time, we derive formal expressions for motif frequencies and the frequencies with which species occur in different positions within motifs. This framework means that analyses with bmotif are fast, making motif methods compatible with the permutational approaches often used in network studies, such as null model analyses.

We describe the package and demonstrate how it can be used to conduct ecological analyses, using two examples of plant–pollinator networks. We first use motifs to examine the assembly and disassembly of an Arctic plant–pollinator community and then use them to compare the roles of native and introduced plant species in an unrestored site in Mauritius.

bmotif will enable motif analyses of a wide range of bipartite ecological networks, allowing future research to characterise these complex networks without discarding important meso‐scale structural detail.

Abundant pollinators are often more generalised than rare pollinators. This could be because abundant species have more chance encounters with potential interaction partners. On the other hand, generalised species could have a competitive advantage over specialists, leading to higher abundance. Determining the direction of the abundance–generalisation relationship is therefore a ‘chicken-and-egg’ dilemma. Here we determine the direction of the relationship between abundance and generalisation in plant–hummingbird pollination networks across the Americas. We find evidence that hummingbird pollinators are generalised because they are abundant, and little evidence that hummingbirds are abundant because they are generalised. Additionally, most patterns of species-level abundance and generalisation were well explained by a null model that assumed interaction neutrality (interaction probabilities defined by species relative abundances). These results suggest that neutral processes play a key role in driving broad patterns of generalisation in animal pollinators across large spatial scales.

In the version of this Article originally published, ammonia and NO emissions (and associated N deposition), nitrate leaching, and the CO2 emitted during urea hydrolysis following application to land were all accidentally omitted in the comparison of the greenhouse gas impacts of using ammonium nitrate and urea to produce wheat grain.

Improving the use of scientific evidence in conservation policy has been a long-standing focus of the conservation community. A plethora of studies have examined conservation science-policy interfaces, including a recent global survey of scientists, policy-makers, and practitioners. This identified a list of top barriers and solutions to evidence use, which have considerable overlap with those identified by other studies conducted over the last few decades. The three top barriers – (i) that conservation is not a political priority, (ii) that there is poor engagement between scientists and decision-makers, and (iii) that conservation problems are complex and uncertain – have often been highlighted in the literature as significant constraints on the use of scientific evidence in conservation policy. There is also repeated identification of the solutions to these barriers. In this perspective, we consider three reasons for this: (1) the barriers are insurmountable, (2) the frequently-proposed solutions are poor, (3) there are implementation challenges to putting solutions into practice. We argue that implementation challenges are most likely to be preventing the solutions being put into practice and that the research agenda for conservation science-policy interfaces needs to move away from identifying barriers and solutions, and towards a detailed investigation of how to overcome these implementation challenges.

There is a correction in the acknowledgements of the manuscript 'Trait evolution, resource specialization and vulnerability to plant extinctions among Antillean hummingbirds'. Proc. R. Soc. B 285, 20172754. http://dx.doi.org/10.1098/rspb.2017.2754.

Computational thinking is the integration of algorithms, software, and data, tosolve general questions in a field. Computation ecology has the potential totransform the way ecologists think about the integration of data and models. Asthe practice is gaining prominence as a way to conduct ecological research, itis important to reflect on what its agenda could be, and how it fits within thebroader landscape of ecological research. In this contribution, we suggest areasin which empirical ecologists, modellers, and the emerging community ofcomputational ecologists could engage in a constructive dialogue to build on oneanother's expertise; specifically, about the need to make predictions frommodels actionable, about the best standards to represent ecological data, andabout the proper ways to credit data collection and data reuse. We discuss howtraining can be amended to improve computational literacy.

Abstract


Cultural ecosystem services are undeniably important, yet are typically neglected in land management decisions due to a suite of intractable challenges: they are highly complex, localised, and inextricably associated with landscape features. However, to incorporate the ecosystem services framework into land management, decision‐makers need the tools to disentangle the effects of land use from other factors. This is a major challenge for ecosystem services research.

Forestry is a widespread land use that has considerable potential to deliver a broad range of ecosystem services, although this requires careful management planning. Additionally, modern production forestry is undergoing a period of rapid change in the face of a plethora of challenges, such as climate change and disease. To increase cultural ecosystem services delivery from forests, managers need tools to understand the implications of different management options.

In this paper, we directly test how land use affects cultural ecosystem services. We use a new approach that recognises the underlying complexity of cultural ecosystem services but produces easily interpretable results that are locally relevant and directly applicable to land management. By combining participatory geographic information systems (GIS) and a novel site matching technique, we relate cultural values explicitly to land management, while accounting for the influence of landscape features.

Applying this new method to a major UK forest site, we conducted a large survey to gather participatory GIS data points. We showed that land management significantly affected cultural ecosystem service values and were able to make a series of practical forest management recommendations. Notably, a greater diversity of tree species would improve cultural value, and open space is important within the forest landscape.

This approach is highly flexible and can be applied to any type of landscape. It allows cultural ecosystem services to be fully integrated into land management decisions to formulate the best management strategy to maximise ecosystem service delivery.

A plain language summary is available for this article.

There is increasing interest in the effectiveness of protected areas (PAs) for supporting populations of wildlife. While there are a number of association studies showing a relationship between protected areas and abundance or trends in wild species, studies with an appropriate counterfactual (what would have happened in the absence of protection) are rare. We use the world’s largest database on waterbird counts (covering 587 species at 21,989 sites globally) to answer three questions: 1) Do PAs have a positive impact on waterbird population trends relative to a counterfactual (this includes cases where a PA has lessened, but not halted, a population decline)?; 2) are PAs performing successfully by maintaining or increasing populations? and 3) what factors contribute to PA impact and performance? We selected 15,703 waterbird populations (here defined as a site species combination), consisting of 311 species at 870 protected sites, where PA designation occurred at least 5 years after the first survey date, and 5 years before the last. We will use this to compare trends before PA designation to those afterwards. We then matched these sites to unprotected sites with similar covariates in the years before PA designation, resulting in a matching dataset of 6,451 populations pairs consisting of 39 species at 769 pairs of protected and unprotected sites. We will use this to compare trends both before and after PA designation and inside and outside of PAs. Our results will shed light on the impact of PA on hundreds of waterbird species, providing much needed evidence regarding PA effectiveness. As PA performance is a sensitive subject and it is important to develop hypotheses before knowing the results (especially for the relatively complex data analysis used in matching protected and unprotected sites), we present a pre-analysis plan. This will ensure that the final paper’s analyses are hypotheses testing, rather than generating, and avoids the risk of, or perception of, data dredging.

AbstractEcologists use a wide range of study designs to estimate the impact of interventions or threats but there are no quantitative comparisons of their accuracy. For example, while it is accepted that simpler designs, such as After (sampling sites post-impact without a control), Before-After (BA) and Control-Impact (CI), are less robust than Randomised Controlled Trials (RCT) and Before-After Control-Impact (BACI) designs, it is not known how much less accurate they are.We simulate a step-change response of a population to an environmental impact using empirically-derived estimates of the major parameters. We use five ecological study designs to estimate the effect of this impact and evaluate each one by determining the percentage of simulations in which they accurately estimate the direction and magnitude of the environmental impact. We also simulate different numbers of replicates and assess several accuracy thresholds.We demonstrate that BACI designs could be 1.1-1.5 times more accurate than RCTs, 2.9-4.1 times more accurate than BA, 3.8-5.6 times more accurate than CI, and 6.8-10.8 times more accurate than After designs, when estimating to within ±30% of the true effect (depending on the sample size). We also found that increasing sample size substantially increases the accuracy of BACI designs but only increases the precision of simpler designs around a biased estimate; only by using more robust designs can accuracy increase. Modestly increasing replication of both control and impact sites also increased the accuracy of BACI designs more than substantially increasing replicates in just one of these groups.We argue that investment into using more robust designs in ecology, where possible, is extremely worthwhile given the inaccuracy of simpler designs, even when using large sample sizes. Based on our results we propose a weighting system that quantitatively ranks the accuracy of studies based on their study design and the number of replicates used. We hope these ‘accuracy weights’ enable researchers to better account for study design in evidence synthesis when assessing the reliability of a range of studies using a variety of designs.

Abstract


Monitoring the impacts of anthropogenic threats and interventions to mitigate these threats is key to understanding how to best conserve biodiversity. Ecologists use many different study designs to monitor such impacts. Simpler designs lacking controls (e.g. Before–After (BA) and After) or pre‐impact data (e.g. Control–Impact (CI)) are considered to be less robust than more complex designs (e.g. Before–After Control‐Impact (BACI) or Randomized Controlled Trials (RCTs)). However, we lack quantitative estimates of how much less accurate simpler study designs are in ecology. Understanding this could help prioritize research and weight studies by their design's accuracy in meta‐analysis and evidence assessment.

We compared how accurately five study designs estimated the true effect of a simulated environmental impact that caused a step‐change response in a population's density. We derived empirical estimates of several simulation parameters from 47 ecological datasets to ensure our simulations were realistic. We measured design performance by determining the percentage of simulations where: (a) the true effect fell within the 95% Confidence Intervals of effect size estimates, and (b) each design correctly estimated the true effect's direction and magnitude. We also considered how sample size affected their performance.

We demonstrated that BACI designs performed: 1.3–1.8 times better than RCTs; 2.9–4.2 times versus BA; 3.2–4.6 times versus CI; and 7.1–10.1 times versus After designs (depending on sample size), when correctly estimating true effect's direction and magnitude to within ±30%. Although BACI designs suffered from low power at small sample sizes, they outperformed other designs for almost all performance measures. Increasing sample size improved BACI design accuracy, but only increased the precision of simpler designs around biased estimates.

Synthesis and applications. We suggest that more investment in more robust designs is needed in ecology since inferences from simpler designs, even with large sample sizes may be misleading. Facilitating this requires longer‐term funding and stronger research–practice partnerships. We also propose ‘accuracy weights’ and demonstrate how they can weight studies in three recent meta‐analyses by accounting for study design and sample size. We hope these help decision‐makers and meta‐analysts better account for study design when assessing evidence.

AbstractConservation efforts to tackle the current biodiversity crisis need to be as efficient and effective as possible. To inform decision-makers of the most effective conservation actions, it is important to identify biases and gaps in the conservation literature to prioritize future evidence generation. We assessed the state of this global literature base using the Conservation Evidence database, a comprehensive collection of quantitative tests of conservation actions (interventions) from the published literature. For amphibians and birds, we investigated the nature of Conservation Evidence spatially and taxonomically, as well as by biome, effectiveness metrics, and study design. Studies were heavily concentrated in Western Europe and North America for birds and particularly amphibians. Studies that used the most robust study designs - Before-After Control-Impact and Randomized Controlled Trials - were also the most geographically restricted. Furthermore, there was no relationship between the number of studies in each 1×1 degree grid cell and the number of species, threatened species or data-deficient species. Taxonomic biases and gaps were apparent for amphibians and birds - some orders were absent from the evidence base and others were poorly represented relative to the proportion of threatened species they contained. Temperate forest and grassland biomes were highly represented, which reinforced observed geographic biases. Various metrics were used to evaluate the effectiveness of a given conservation action, potentially making studies less directly comparable and evidence synthesis more difficult. We also found that the least robust study designs were the most commonly used; studies using robust designs were scarce. Future research should prioritize testing conservation actions on threatened species outside of Western Europe and North America. Standardizing metrics and improving the robustness of study designs used to test conservation actions would also improve the quality of the evidence base for synthesis and decision-making.

AbstractSpecies are central to ecology and conservation. However, it is the interactions between species that generate the functions on which ecosystems and humans depend. Despite the importance of interactions, we lack an understanding of the risk that their loss poses to ecological communities. Here, we quantify risk as a function of the vulnerability (likelihood of loss) and importance (contribution to network stability in terms of species coexistence) of 4330 mutualistic interactions from 41 empirical pollination and seed dispersal networks across six continents. Remarkably, we find that more vulnerable interactions are also more important: the interactions that contribute most to network stability are those that are most likely to be lost. Furthermore, most interactions tend to have more similar vulnerability and importance across networks than expected by chance, suggesting that vulnerability and importance may be intrinsic properties of interactions, rather than only a function of ecological context. These results provide a starting point for prioritising interactions for conservation in species interaction networks and, in areas lacking network data, could allow interaction properties to be inferred from taxonomy alone.

AbstractAbundant pollinators are often more generalised than rare pollinators. This could be because abundance drives generalisation: neutral effects suggest that more abundant species will be more generalised simply because they have more chance encounters with potential interaction partners. On the other hand, generalisation could drive abundance, as generalised species could have a competitive advantage over specialists, being able to exploit a wider range of resources and gain a more balanced nutrient intake. Determining the direction of the abundance-generalisation relationship is therefore a ‘chicken-and-egg’ dilemma. Here we determine the direction of the relationship between abundance and generalisation in plant-hummingbird pollination networks sampled from a variety of locations across the Americas. For the first time we resolve the direction of the abundance-generalisation relationship using independent data on animal abundance. We find evidence that hummingbird pollinators are generalised because they are abundant, and little evidence that hummingbirds are abundant because they are generalised. Additionally, a null model analysis suggests this pattern is due to neutral processes: most patterns of species-level abundance and generalisation were well explained by a null model that assumed interaction neutrality. These results suggest that neutral processes play a key role in driving broad patterns of generalisation in animal pollinators across large spatial scales.DeclarationsFunding – BIS is supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP [NE/L002507/1]. JVB was funded by CERL - Engineer Research and Development Center. PKM was funded by the São Paulo Research Foundation (FAPESP grant #2015/21457-4). PAC was funded by the David Lack studentship from the British Ornithologists’ Union and Wolfson College, University of Oxford. CL was funded by the ESDEPED-UAT grant. MAM acknowledges the Consejo Nacional para Investigaciones Científicas y Tecnológicas (Costa Rica), German Academic Exchange Service and the research funding program ‘LOEWE-Landes-Offensive zur Entwicklung Wissenschaftlichö konomischer Exzellenz’ of Hesse’s Ministry of Higher Education, Research, and the Arts (Germany). ROP was funded by CONACyT (project 258364). MAR was supported by the State of São Paulo Research Foundation (FAPESP) within the BIOTA/FAPESP, the Biodiversity Institute Program (www.biota.org.br) and the ‘Parcelas Permanentes’ project, as well as by Coordenação de Pessoal de Nível Superior (CAPES), Fundo de Apoio ao Ensino e à Pesquisa (FAEP)/Funcamp/Unicamp and the Nature Conservancy (TNC) of Brazil. LCR was supported by CNPq and Capes. MS was funded by CNPq (grant #302781/2016-1). AMMG is supported through a Marie Skłodowska-Curie Individual Fellowship (H2020-MSCA-IF-2016-704409). LVD was supported by the Natural Environment Research Council (grants NE/K015419/1 and NE/N014472/1). AMMG, JS, CR and BD thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution and Climate (grant no. DNRF96). WJS is funded by Arcadia.

Vertebrate pollinators are increasingly threatened worldwide, but little is known about the potential consequences of declining pollinator populations on plants and ecosystems. Here, we present the first global assessment of the importance of vertebrate pollinators in the reproductive success of selected flowering plants. Our meta‐analysis of 126 experiments on animal‐pollinated plants revealed that excluding vertebrate pollinators – but not insect pollinators – reduced fruit and/or seed production by 63% on average. We found bat‐pollinated plants to be more dependent on their respective vertebrate pollinators than bird‐pollinated plants (an average 83% reduction in fruit/seed production when bats were excluded, as compared to a 46% reduction when birds were excluded). Plant dependence on vertebrate pollinators for fruit/seed production was greater in the tropics than at higher latitudes. Given the potential for substantial negative impacts associated with the loss of vertebrate pollinators, there is a clear need for prompt, effective conservation action for threatened flower‐visiting vertebrate species. Additional research on how such changes might affect wider ecosystems is also required.

Indirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about bipartite ecological networks, we show that this shift is supported by analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight differences missed by the current index paradigm that may be ecologically important. We extend this finding to empirical plant–pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need to not rely solely on network‐ and species‐level indices for characterising the structure of bipartite ecological networks.

Abstract


There is growing interest in understanding the functional outcomes of species interactions in ecological networks. For many mutualistic networks, including pollination and seed dispersal networks, interactions are generally sampled by recording animal foraging visits to plants. However, these visits may not reflect actual pollination or seed dispersal events, despite these typically being the ecological processes of interest.

Frugivorous animals can act as seed dispersers, by swallowing entire fruits and dispersing their seeds, or as pulp peckers or seed predators, by pecking fruits to consume pieces of pulp or seeds. These processes have opposing consequences for plant reproductive success. Therefore, equating visitation with seed dispersal could lead to biased inferences about the ecology, evolution and conservation of seed dispersal mutualisms.

Here, we use natural history information on the functional outcomes of pairwise bird–plant interactions to examine changes in the structure of seven European plant–frugivore visitation networks after non‐mutualistic interactions (pulp pecking and seed predation) have been removed. Following existing knowledge of the contrasting structures of mutualistic and antagonistic networks, we hypothesized a number of changes following interaction removal, such as increased nestedness and lower specialization.

Non‐mutualistic interactions with pulp peckers and seed predators occurred in all seven networks, accounting for 21%–48% of all interactions and 6%–24% of total interaction frequency. When non‐mutualistic interactions were removed, there were significant increases in network‐level metrics such as connectance and nestedness, while robustness decreased. These changes were generally small, homogenous and driven by decreases in network size. Conversely, changes in species‐level metrics were more variable and sometimes large, with significant decreases in plant degree, interaction frequency, specialization and resilience to animal extinctions and significant increases in frugivore species strength.

Visitation data can overestimate the actual frequency of seed dispersal services in plant–frugivore networks. We show here that incorporating natural history information on the functions of species interactions can bring us closer to understanding the processes and functions operating in ecological communities. Our categorical approach lays the foundation for future work quantifying functional interaction outcomes along a mutualism–antagonism continuum, as documented in other frugivore faunas.

In 2008, a group of conservation scientists compiled a list of 100 priority questions for the conservation of the world's biodiversity. However, now almost a decade later, no one has yet published a study gauging how much progress has been made in addressing these 100 high-priority questions in the peer-reviewed literature. We took a first step toward reexamining the 100 questions to identify key knowledge gaps that remain. Through a combination of a questionnaire and a literature review, we evaluated each question on the basis of 2 criteria: relevance and effort. We defined highly relevant questions as those that - if answered - would have the greatest impact on global biodiversity conservation and quantified effort based on the number of review publications addressing a particular question, which we used as a proxy for research effort. Using this approach, we identified a set of questions that, despite being perceived as highly relevant, have been the focus of relatively few review publications over the past 10 years. These questions covered a broad range of topics but predominantly tackled 3 major themes: conservation and management of freshwater ecosystems, role of societal structures in shaping interactions between people and the environment, and impacts of conservation interventions. We believe these questions represent important knowledge gaps that have received insufficient attention and may need to be prioritized in future research.

Conservation policy decisions can suffer from a lack of evidence, hindering effective decision-making. In nature conservation, studies investigating why policy is often not evidence-informed have tended to focus on Western democracies, with relatively small samples. To understand global variation and challenges better, we established a global survey aimed at identifying top barriers and solutions to the use of conservation science in policy. This obtained the views of 758 people in policy, practice, and research positions from 68 countries across six languages. Here we show that, contrary to popular belief, there is agreement between groups about how to incorporate conservation science into policy, and there is thus room for optimism. Barriers related to the low priority of conservation were considered to be important, while mainstreaming conservation was proposed as a key solution. Therefore, priorities should focus on convincing the public of the importance of conservation as an issue, which will then influence policy-makers to adopt pro-environmental long-term policies.

Species traits are thought to predict feeding specialization and the vulnerability of a species to extinctions of interaction partners, but the context in which a species evolved and currently inhabits may also matter. Notably, the predictive power of traits may require that traits evolved to fit interaction partners. Furthermore, local abiotic and biotic conditions may be important. On islands, for instance, specialized and vulnerable species are predicted to be found mainly in mountains, whereas species in lowlands should be generalized and less vulnerable. We evaluated these predictions for hummingbirds and their nectar-food plants on Antillean islands. Our results suggest that the rates of hummingbird trait divergence were higher among ancestral mainland forms before the colonization of the Antilles. In correspondence with the limited trait evolution that occurred within the Antilles, local abiotic and biotic conditions—not species traits—correlate with hummingbird resource specialization and the vulnerability of hummingbirds to extinctions of their floral resources. Specifically, hummingbirds were more specialized and vulnerable in conditions with high topographical complexity, high rainfall, low temperatures and high floral resource richness, which characterize the Antillean Mountains. These findings show that resource specialization and species vulnerability to extinctions of interaction partners are highly context-dependent.

AbstractIndirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about networks, we show that this shift is supported by quantitative analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight ecologically important differences missed by the current index paradigm. We extend this finding to empirical plant-pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need for a new paradigm for bipartite ecological networks: one incorporating indirect interactions.

AbstractBipartite networks are widely-used to represent a diverse range of species interactions, such as pollination, herbivory, parasitism and seed dispersal. The structure of these networks is usually characterised by calculating one or more metrics that capture different aspects of network architecture. While these metrics capture useful properties of networks, they only consider structure at the scale of the whole network (the macro-scale) or individual species (the micro-scale). ‘Meso-scale’ structure between these scales is usually ignored, despite representing ecologically-important interactions. Network motifs are a framework for capturing this meso-scale structure and are gaining in popularity. However, there is no software available in R, the most popular programming language among ecologists, for conducting motif analyses in bipartite networks. Similarly, no mathematical formalisation of bipartite motifs has been developed.Here we introduce bmotif: a package for counting motifs, and species positions within motifs, in bipartite networks. Our code is primarily an R package, but we also provide MATLAB and Python code of the core functionality. The software is based on a mathematical framework where, for the first time, we derive formal expressions for motif frequencies and the frequencies with which species occur in different positions within motifs. This framework means that analyses with bmotif are fast, making motif methods compatible with the permutational approaches often used in network studies, such as null model analyses.We describe the package and demonstrate how it can be used to conduct ecological analyses, using two examples of plant-pollinator networks. We first use motifs to examine the assembly and disassembly of an Arctic plant-pollinator community, and then use them to compare the roles of native and introduced plant species in an unrestored site in Mauritius.bmotif will enable motif analyses of a wide range of bipartite ecological networks, allowing future research to characterise these complex networks without discarding important meso-scale structural detail.

The PREDICTS project-Projecting Responses of Ecological Diversity in Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

Crossing “safe” limits for biodiversity lossThe planetary boundaries framework attempts to set limits for biodiversity loss within which ecological function is relatively unaffected. Newboldet al.present a quantitative global analysis of the extent to which the proposed planetary boundary has been crossed (see the Perspective by Oliver). Using over 2 million records for nearly 40,000 terrestrial species, they modeled the response of biodiversity to land use and related pressures and then estimated, at a spatial resolution of ∼1 km2, the extent and spatial patterns of changes in local biodiversity. Across 65% of the terrestrial surface, land use and related pressures have caused biotic intactness to decline beyond 10%, the proposed “safe” planetary boundary. Changes have been most pronounced in grassland biomes and biodiversity hotspots.Science, this issue p.288; see also p.220