1. 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.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: (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.3. 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 | 2743

Although increasing efforts are being made to restore tropical forests, little information is available regarding the time scales required for carbon and plant biodiversity to recover to the values associated with undisturbed forests. To address this knowledge gap, we carried out a meta-analysis comparing data from more than 600 secondary tropical forest sites with nearby undisturbed reference forests. Above-ground biomass approached equivalence to reference values within 80 years since last disturbance, whereas below-ground biomass took longer to recover. Soil carbon content showed little relationship with time since disturbance. Tree species richness recovered after about 50 years. By contrast, epiphyte richness did not reach equivalence to undisturbed forests. The proportion of undisturbed forest trees and epiphyte species found in secondary forests was low and changed little over time. Our results indicate that carbon pools and biodiversity show different recovery rates under passive, secondary succession and that colonization by undisturbed forest plant species is slow. Initiatives such as the Convention on Biological Diversity and REDDþ should therefore encourage active management to help to achieve their aims of restoring both carbon and biodiversity in tropical forests.

Forest restoration is being scaled-up globally to deliver critical ecosystem services and biodiversity benefits, yet we lack rigorous comparison of co-benefit delivery across different restoration approaches. In a global synthesis, we use 25,950 matched data pairs from 264 studies in 53 countries to assess how delivery of climate, soil, water, and wood production services as well as biodiversity compares across a range of tree plantations and native forests. Carbon storage, water provisioning, and especially soil erosion control and biodiversity benefits are all delivered better by native forests, with compositionally simpler, younger plantations in drier regions performing particularly poorly. However, plantations exhibit an advantage in wood production. These results underscore important trade-offs among environmental and production goals that policymakers must navigate in meeting forest restoration commitments.

a b s t r a c tOver 400 million hectares of tropical forest are currently designated as logging concessions. This practice is an important source of timber, but there are concerns about its long-term sustainability and impacts on biodiversity and carbon storage. However, logging impacts vary widely, making generalisation and, consequently, policy implementation, difficult. Recent syntheses of animal biodiversity have indicated that differences in logging intensity -the volume of wood removed ha À1 -might help to explain some of these disparities. In addition, it has widely been assumed that reduced impact logging (RIL) might minimise some of the negative effects of logging; though in practice, this has rarely been tested. To test the hypothesis that RIL reduces negative impacts of selective logging once intensity is controlled for, we used meta-analyses of selective logging impact studies, focusing specifically on (1) residual tree damage, (2) aboveground biomass and (3) tree species richness. Our results indicate that RIL appears to reduce residual tree damage when compared to conventional methods. However, changes in aboveground biomass were negatively related to logging intensity. Any effect of RIL, independent of logging intensity, was difficult to discern since it was carried out at relatively low intensities. Tree richness appeared to increase at low intensities but decreased at higher intensities and any effect of RIL was difficult to detect. Our results tentatively support the hypothesis that RIL reduces the negative impacts of logging on tree damage, but do not support suggestions that RIL reduces loss of aboveground biomass or tree species richness. However, this lack of support may be a result of the relative paucity of data on the topic. Based on our results, we suggest that better evidence is needed to assess the differences between the impacts of RIL and conventional logging. Studies that consider plot-level differences in logging intensity are required to fill this knowledge gap. In addition, there must be clarification of whether RIL is an inherently low intensity practice so that this can be factored into management.

Efforts to tackle the current biodiversity crisis need to be as efficient and effective as possible given chronic underfunding. 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 used the Conservation Evidence database to assess the state of the global literature that tests conservation actions for amphibians and birds. For the studies in the database, we investigated their spatial and taxonomic extent and distribution across biomes, effectiveness metrics, and study designs. Studies were heavily concentrated in Western Europe and North America for birds and particularly for amphibians, and temperate forest and grassland biomes were highly represented relative to their percentage of land coverage. Studies that used the most reliable study designs—before‐after control‐impact and randomized controlled trials—were the most geographically restricted and scarce in the evidence base. There were negative spatial relationships between the numbers of studies and the numbers of threatened and data‐deficient species worldwide. Taxonomic biases and gaps were apparent for amphibians and birds—some entire orders were absent from the evidence base—whereas others were poorly represented relative to the proportion of threatened species they contained. Metrics used to evaluate effectiveness of conservation actions were often inconsistent between studies, potentially making them less directly comparable and evidence synthesis more difficult. Testing conservation actions on threatened species outside Western Europe, North America, and Australasia should be prioritized. Standardizing metrics and improving the rigor of study designs used to test conservation actions would also improve the quality of the evidence base for synthesis and decision‐making.

Purpose To retrospectively determine the incidence of nephrogenic systemic fibrosis (NSF) in patients on dialysis administered either a lower dose high-relaxivity linear gadolinium-chelate, gadobenate dimeglumine (Multi-Hance, MH), compared to a standard dose linear gadolinium chelate, gadodiamide (Omniscan, OM). Materials and Methods This study was Health Insurance Portability and Accountability Act (HIPAA)-compliant and Institutional Review Board (IRB)-approved. As per institution standardized contrast-enhanced magnetic resonance imaging (MRI) protocols, patients on dialysis were imaged using either MH, between 2/2007 to 9/2008, or OM between 10/2003 and 1/2007. Rates of NSF were compared using 95% score-based confidence intervals (CI). The Wilcoxon rank sum test was used to test similarity/difference between contrast doses given to each patient group. Results Overall, 312 patients on dialysis received OM and eight (2.6%) developed NSF (95% CI: 1.30%–4.98%). In all, 784 patients on dialysis received MH at a mean cumulative dose of 0.11 mmol/kg (0.05–0.75 mmol/kg) and no cases of NSF were identified (upper 95% confidence bound of 0.45%). The mean cumulative dose of OM was 0.16 mmol/kg (0.1–0.9 mmol/kg) for all patients and 0.28 mmol/kg (0.1–0.8 mmol/kg) for the patients with NSF. The median OM dose was greater in patients who developed NSF (P = 0.03), and was greater than the median MH dose (P < 0.005). Conclusion NSF incidence in at-risk patients receiving contrast-enhanced MRI can be reduced after changing contrast administration protocols that includes changing the type and dose of contrast agent.

Both active and passive forest restoration schemes are used in degraded landscapes across the world to enhance biodiversity and ecosystem service provision. Restoration is increasingly also being implemented in biodiversity offset schemes as compensation for loss of natural habitat to anthropogenic development. This has raised concerns about the value of replacing old‐growth forest with plantations, motivating research on biodiversity recovery as forest stands age. Functional diversity is now advocated as a key metric for restoration success, yet it has received little analytical attention to date. We conducted a meta‐analysis of 90 studies that measured differences in species richness for functional groups of fungi, lichens, and beetles between old‐growth control and planted or secondary treatment forests in temperate, boreal, and Mediterranean regions. We identified functional‐group–specific relationships in the response of species richness to stand age after forest disturbance. Ectomycorrhizal fungi averaged 90 years for recovery to old‐growth values (between 45 years and unrecoverable at 95% prediction limits), and epiphytic lichens took 180 years to reach 90% of old‐growth values (between 140 years and never for recovery to old‐growth values at 95% prediction limits). Non‐saproxylic beetle richness, in contrast, decreased as stand age of broadleaved forests increased. The slow recovery by some functional groups essential to ecosystem functioning makes old‐growth forest an effectively irreplaceable biodiversity resource that should be exempt from biodiversity offsetting initiatives.

Biodiversity studies are sensitive to well‐recognised temporal and spatial scale dependencies. Cross‐study syntheses may inflate these influences by collating studies that vary widely in the numbers and sizes of sampling plots. Here we evaluate sources of inaccuracy and imprecision in study‐level and cross‐study estimates of biodiversity differences, caused by within‐study grain and sample sizes, biodiversity measure, and choice of effect‐size metric. Samples from simulated communities of old‐growth and secondary forests demonstrated influences of all these parameters on the accuracy and precision of cross‐study effect sizes. In cross‐study synthesis by formal meta‐analysis, the metric of log response ratio applied to measures of species richness yielded better accuracy than the commonly used Hedges' g metric on species density, which dangerously combined higher precision with persistent bias. Full‐data analyses of the raw plot‐scale data using multilevel models were also susceptible to scale‐dependent bias. We demonstrate the challenge of detecting scale dependence in cross‐study synthesis, due to ubiquitous covariation between replication, variance and plot size. We propose solutions for diagnosing and minimising bias. We urge that empirical studies publish raw data to allow evaluation of covariation in cross‐study syntheses, and we recommend against using Hedges' g in biodiversity meta‐analyses.