Simple study designs in ecology produce inaccurate estimates of biodiversity responses

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 Randomised Controlled Trials (RCTs)). However, we lack quantitative estimates of how much less accurate simpler study designs are in ecology. Understanding this could help prioritise research and weight studies by their design’s accuracy in meta-analysis and evidence assessment. 2. 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: (i) the true effect fell within the 95% Confidence Intervals of effect size estimates, and (ii) each design correctly estimated the true effect’s direction and magnitude. We also considered how sample size affected their performance. 3. We demonstrated that BACI designs performed: 1.3-1.8 times better than RCTs; 2.9-4.2 times vs BA; 3.2-4.6 times vs CI; and 7.1-10.1 times vs 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. 4. 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

Poor availability of context-specific evidence hampers decision-making in conservation

Evidence-based conservation relies on reliable 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 few locally conducted studies were found in Western sub-Saharan Africa, Russia, South East Asia, and Eastern South America. Globally there were extremely low densities of studies per intervention - fewer than one study within 2000 km 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 reliable 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 reliable study designs and standardized metrics, and methodological advances to analyze patchy evidence bases

bmotif: A package for motif analyses of bipartite networks

1. 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. 2. 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. 3. 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. 4. 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.Cambridge Faculty of Mathematics Bridgwater Summer Research Fund/CMP bursary fun

Evaluating impact using time-series data

This is the final version. Available on open access from Elsevier via the DOI in this recordHumanity’s impact on the environment is increasing, as are strategies to conserve biodiversity, but a lack of understanding about how interventions affect ecological and conservation outcomes hampers decision-making. Time-series are often used to assess impacts, but ecologists tend to compare average values from before to after an impact; overlooking the potential for the intervention to elicit a change in trend. Without methods that allow for a range of responses, erroneous conclusions can be drawn. This is especially so for large, multi-time-series datasets which are increasingly available. Drawing on literature in other disciplines and pioneering work in ecology, we present a standardised framework to robustly assesses how interventions, like natural disasters or conservation policies, affect ecological time series.Royal Commission 1851Cambridge Trust Poynton ScholarshipCambridge Department of Zoology J.S. Gardiner StudentshipCambridge Philosophical SocietyAustralian Research Council (ARC)University of QueenslandEuropean Union Horizon 2020Villum FondenArcadiaLeverhulme Trus

Policy windows for the environment: Tips for improving the uptake of scientific knowledge

© 2017 The Authors. 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.European Union Seventh Framework Programme EU Biodiversity Observation Network (No. 308454); Fondation Wiener Anspach, Belgium; Scriven fellowship; Natural Environment Research Council Cambridge Earth System Science NERC DTP [NE/L002507/1]; Natural Environment Research Council Industrial CASE studentship [NE/M010287/1]; Austrian Science Fund (FWF); Arcadia

Policy windows for the environment: Tips for improving the uptake of scientific knowledge

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.(1) EU’s Seventh Framework Programme within the EU Biodiversity Observation Network (No. 308454) (2) Post-doctoral fellowship from Fondation Wiener Anspach, Belgium and the Scriven fellowship, (3) Cambridge Earth System Science NERC DTP [NE/L002507/1], (4) Austrian Science Fund (FWF), (5) Arcadia

Associations of exercise-induced hormone profiles and gains in strength and hypertrophy in a large cohort after weight training

The purpose of this study was to investigate associations between acute exercise-induced hormone responses and adaptations to high intensity resistance training in a large cohort (n = 56) of young men. Acute post-exercise serum growth hormone (GH), free testosterone (fT), insulin-like growth factor (IGF-1) and cortisol responses were determined following an acute intense leg resistance exercise routine at the midpoint of a 12-week resistance exercise training study. Acute hormonal responses were correlated with gains in lean body mass (LBM), muscle fibre cross-sectional area (CSA) and leg press strength. There were no significant correlations between the exercise-induced elevations (area under the curve—AUC) of GH, fT and IGF-1 and gains in LBM or leg press strength. Significant correlations were found for cortisol, usually assumed to be a hormone indicative of catabolic drive, AUC with change in LBM (r = 0.29, P < 0.05) and type II fibre CSA (r = 0.35, P < 0.01) as well as GH AUC and gain in fibre area (type I: r = 0.36, P = 0.006; type II: r = 0.28, P = 0.04, but not lean mass). No correlations with strength were observed. We report that the acute exercise-induced systemic hormonal responses of cortisol and GH are weakly correlated with resistance training-induced changes in fibre CSA and LBM (cortisol only), but not with changes in strength

Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

Denying reciprocity

When individuals receive benefits as a result of the burdens assumed by other people, they are expected to make a return in similar form. To do otherwise is considered as a failure to treat those other people with appropriate respect. It is this which justifies the expectation that individuals share in the labour that is necessary to preserve just institutions and productive practices that characterise complex schemes of social cooperation. In this paper, I argue that where benefits do not meet thresholds specifying the expected function and efficacy of those benefits, this does not simply issue in a ‘downward adjustment’ in the work expectations and reciprocal demands that are made of people. Rather, it legitimates refusal to engage in productive labour even where limited benefits are still being received. Other costs and obligations emerge that contribute to the creation of disruptive political, economic and social associations. These not only replace the demands of reciprocity but actively target and disrupt the practices and exchanges that give form to reciprocity

Negative phenotypic and genetic associations between copulation duration and longevity in male seed beetles

Reproduction can be costly and is predicted to trade-off against other characters. However, while these trade-offs are well documented for females, there has been less focus on aspects of male reproduction. Furthermore, those studies that have looked at males typically only investigate phenotypic associations, with the underlying genetics often ignored. Here, we report on phenotypic and genetic trade-offs in male reproductive effort in the seed beetle, Callosobruchus maculatus. We find that the duration of a male's first copulation is negatively associated with subsequent male survival, phenotypically and genetically. Our results are consistent with life-history theory and suggest that like females, males trade-off reproductive effort against longevity