While it is recognized that language can pose a barrier to the transfer of scientific knowledge, the convergence on English as the global language of science may suggest that this problem has been resolved. However, our survey searching Google Scholar in 16 languages revealed that 35.6% of 75,513 scientific documents on biodiversity conservation published in 2014 were not in English. Ignoring such non-English knowledge can cause biases in our understanding of study systems. Furthermore, as publication in English has become prevalent, scientific knowledge is often unavailable in local languages. This hinders its use by field practitioners and policy makers for local environmental issues; 54% of protected area directors in Spain identified languages as a barrier. We urge scientific communities to make a more concerted effort to tackle this problem and propose potential approaches both for compiling non-English scientific knowledge effectively and for enhancing the multilingualization of new and existing knowledge available only in English for the users of such knowledge.

Decision support tools, usually considered to be software-based, may be an important part of the quest for evidence-based decision-making in agriculture to improve productivity and environmental outputs. These tools can lead users through clear steps and suggest optimal decision paths or may act more as information sources to improve the evidence base for decisions. Yet, despite their availability in a wide range of formats, studies in several countries have shown uptake to be disappointingly low. This paper uses a mixed methods approach to investigate the factors affecting the uptake and use of decision support tools by farmers and advisers in the UK. Through a combination of qualitative interviews and quantitative surveys, we found that fifteen factors are influential in convincing farmers and advisers to use decision support tools, which include usability, cost-effectiveness, performance, relevance to user, and compatibility with compliance demands. This study finds a plethora of agricultural decision support tools in operation in the UK, yet, like other studies, shows that their uptake is low. A better understanding of the fifteen factors identified should lead to more effective design and delivery of tools in the future

Shifts in species' distribution and abundance in response to climate change have been well documented, but the underpinning processes are still poorly understood. We present the results of a systematic literature review and meta-analysis investigating the frequency and importance of different mechanisms by which climate has impacted natural populations. Most studies were from temperate latitudes of North America and Europe; almost half investigated bird populations. We found significantly greater support for indirect, biotic mechanisms than direct, abiotic mechanisms as mediators of the impact of climate on populations. In addition, biotic effects tended to have greater support than abiotic factors in studies of species from higher trophic levels. For primary consumers, the impact of climate was equally mediated by biotic and abiotic mechanisms, whereas for higher level consumers the mechanisms were most frequently biotic, such as predation or food availability. Biotic mechanisms were more frequently supported in studies that reported a directional trend in climate than in studies with no such climatic change, although sample sizes for this comparison were small. We call for more mechanistic studies of climate change impacts on populations, particularly in tropical systems.

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

Citizen science has a long history in the ecological sciences and has made substantial contributions to science, education, and society. Developments in information technology during the last few decades have created new opportunities for citizen science to engage ever larger audiences of volunteers to help address some of ecology's most pressing issues, such as global environmental change. Using online tools, volunteers can find projects that match their interests and learn the skills and protocols required to develop questions, collect data, submit data, and help process and analyze data online. Citizen science has become increasingly important for its ability to engage large numbers of volunteers to generate observations at scales or resolutions unattainable by individual researchers. As a coupled natural and human approach, citizen science can also help researchers access local knowledge and implement conservation projects that might be impossible otherwise. In Japan, however, the value of citizen science to science and society is still underappreciated. Here we present case studies of citizen science in Japan, the United States, and the United Kingdom, and describe how citizen science is used to tackle key questions in ecology and conservation, including spatial and macro-ecology, management of threatened and invasive species, and monitoring of biodiversity. We also discuss the importance of data quality, volunteer recruitment, program evaluation, and the integration of science and human systems in citizen science projects. Finally, we outline some of the primary challenges facing citizen science and its future.

Global biodiversity conservation is seriously challenged by gaps and heterogeneity in the geographical coverage of existing information. Nevertheless, the key barriers to the collection and compilation of biodiversity information at a global scale have yet to be identified. We show that wealth, language, geographical location and security each play an important role in explaining spatial variations in data availability in four different types of biodiversity databases. The number of records per square kilometre is high in countries with high per capita gross domestic product (GDP), high proportion of English speakers and high security levels, and those located close to the country hosting the database; but these are not necessarily countries with high biodiversity. These factors are considered to affect data availability by impeding either the activities of scientific research or active international communications. Our results demonstrate that efforts to solve environmental problems at a global scale will gain significantly by focusing scientific education, communication, research and collaboration in low-GDP countries with fewer English speakers and located far from Western countries that host the global databases; countries that have experienced conflict may also benefit. Findings of this study may be broadly applicable to other fields that require the compilation of scientific knowledge at a global level.

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How we manage farming and food systems to meet rising demand is pivotal to the future of biodiversity. Extensive field data suggest impacts on wild populations would be greatly reduced through boosting yields on existing farmland so as to spare remaining natural habitats. High-yield farming raises other concerns because expressed per unit area it can generate high levels of externalities such as greenhouse gas (GHG) emissions and nutrient losses. However, such metrics underestimate the overall impacts of lower-yield systems, so here we develop a framework that instead compares externality and land costs per unit production. Applying this to diverse datasets describing the externalities of four major farm sectors reveals that, rather than involving tradeoffs, the externality and land costs of alternative production systems can co-vary positively: per