Trends in research approaches and gender in plant ecology dissertations over four decades.

Dissertations are a foundational scientific product; they are the formative product that early-career scientists create and share original knowledge. The methodological approaches used in dissertations vary with the research field. In plant ecology, these approaches include observations, experiments (field or controlled environment), literature reviews, theoretical approaches, or analyses of existing data (including "big data"). Recently, concerns have been raised about the rise of "big data" studies and the loss of observational and field-based studies in ecology, but such trends have not been formally quantified. Therefore, we examined how the emphasis on each of these categories has changed over time and whether male and female authors differ in the methods employed. We found remarkable temporal consistency, with observational studies being dominant over the entire time span examined. There was an increase in the number of approaches employed per dissertation, with increases in analyses of databases and theoretical studies adding to rather than replacing traditional methodologies (like observations and field experiments). The representation of women increased over time. There were some differences in the approaches taken by men and women, which requires further investigation.

Managing forests for competing goals.

Tree plantations face difficult trade-offs between production and ecological goals.

Preferred reporting items for systematic reviews and meta-analyses in ecology and evolutionary biology: a PRISMA extension.

Since the early 1990s, ecologists and evolutionary biologists have aggregated primary research using meta-analytic methods to understand ecological and evolutionary phenomena. Meta-analyses can resolve long-standing disputes, dispel spurious claims, and generate new research questions. At their worst, however, meta-analysis publications are wolves in sheep's clothing: subjective with biased conclusions, hidden under coats of objective authority. Conclusions can be rendered unreliable by inappropriate statistical methods, problems with the methods used to select primary research, or problems within the primary research itself. Because of these risks, meta-analyses are increasingly conducted as part of systematic reviews, which use structured, transparent, and reproducible methods to collate and summarise evidence. For readers to determine whether the conclusions from a systematic review or meta-analysis should be trusted - and to be able to build upon the review - authors need to report what they did, why they did it, and what they found. Complete, transparent, and reproducible reporting is measured by 'reporting quality'. To assess perceptions and standards of reporting quality of systematic reviews and meta-analyses published in ecology and evolutionary biology, we surveyed 208 researchers with relevant experience (as authors, reviewers, or editors), and conducted detailed evaluations of 102 systematic review and meta-analysis papers published between 2010 and 2019. Reporting quality was far below optimal and approximately normally distributed. Measured reporting quality was lower than what the community perceived, particularly for the systematic review methods required to measure trustworthiness. The minority of assessed papers that referenced a guideline (~16%) showed substantially higher reporting quality than average, and surveyed researchers showed interest in using a reporting guideline to improve reporting quality. The leading guideline for improving reporting quality of systematic reviews is the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement. Here we unveil an extension of PRISMA to serve the meta-analysis community in ecology and evolutionary biology: PRISMA-EcoEvo (version 1.0). PRISMA-EcoEvo is a checklist of 27 main items that, when applicable, should be reported in systematic review and meta-analysis publications summarising primary research in ecology and evolutionary biology. In this explanation and elaboration document, we provide guidance for authors, reviewers, and editors, with explanations for each item on the checklist, including supplementary examples from published papers. Authors can consult this PRISMA-EcoEvo guideline both in the planning and writing stages of a systematic review and meta-analysis, to increase reporting quality of submitted manuscripts. Reviewers and editors can use the checklist to assess reporting quality in the manuscripts they review. Overall, PRISMA-EcoEvo is a resource for the ecology and evolutionary biology community to facilitate transparent and comprehensively reported systematic reviews and meta-analyses.

Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth.

As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth's surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth's albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth's climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth's surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity.

Consequences of multiple imputation of missing standard deviations and sample sizes in meta-analysis.

Meta-analyses often encounter studies with incompletely reported variance measures (e.g., standard deviation values) or sample sizes, both needed to conduct weighted meta-analyses. Here, we first present a systematic literature survey on the frequency and treatment of missing data in published ecological meta-analyses showing that the majority of meta-analyses encountered incompletely reported studies. We then simulated meta-analysis data sets to investigate the performance of 14 options to treat or impute missing SDs and/or SSs. Performance was thereby assessed using results from fully informed weighted analyses on (hypothetically) complete data sets. We show that the omission of incompletely reported studies is not a viable solution. Unweighted and sample size-based variance approximation can yield unbiased grand means if effect sizes are independent of their corresponding SDs and SSs. The performance of different imputation methods depends on the structure of the meta-analysis data set, especially in the case of correlated effect sizes and standard deviations or sample sizes. In a best-case scenario, which assumes that SDs and/or SSs are both missing at random and are unrelated to effect sizes, our simulations show that the imputation of up to 90% of missing data still yields grand means and confidence intervals that are similar to those obtained with fully informed weighted analyses. We conclude that multiple imputation of missing variance measures and sample sizes could help overcome the problem of incompletely reported primary studies, not only in the field of ecological meta-analyses. Still, caution must be exercised in consideration of potential correlations and pattern of missingness.

Author Correction: Reproducibility of animal research in light of biological variation.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Reproducibility of animal research in light of biological variation.

Context-dependent biological variation presents a unique challenge to the reproducibility of results in experimental animal research, because organisms' responses to experimental treatments can vary with both genotype and environmental conditions. In March 2019, experts in animal biology, experimental design and statistics convened in Blonay, Switzerland, to discuss strategies addressing this challenge. In contrast to the current gold standard of rigorous standardization in experimental animal research, we recommend the use of systematic heterogenization of study samples and conditions by actively incorporating biological variation into study design through diversifying study samples and conditions. Here we provide the scientific rationale for this approach in the hope that researchers, regulators, funders and editors can embrace this paradigm shift. We also present a road map towards better practices in view of improving the reproducibility of animal research.

Evolutionary history predicts high-impact invasions by herbivorous insects.

A long-standing goal of invasion biology is to identify factors driving highly variable impacts of non-native species. Although hypotheses exist that emphasize the role of evolutionary history (e.g., enemy release hypothesis & defense-free space hypothesis), predicting the impact of non-native herbivorous insects has eluded scientists for over a century.Using a census of all 58 non-native conifer-specialist insects in North America, we quantified the contribution of over 25 factors that could affect the impact they have on their novel hosts, including insect traits (fecundity, voltinism, native range, etc.), host traits (shade tolerance, growth rate, wood density, etc.), and evolutionary relationships (between native and novel hosts and insects).We discovered that divergence times between native and novel hosts, the shade and drought tolerance of the novel host, and the presence of a coevolved congener on a shared host, were more predictive of impact than the traits of the invading insect. These factors built upon each other to strengthen our ability to predict the risk of a non-native insect becoming invasive. This research is the first to empirically support historically assumed hypotheses about the importance of evolutionary history as a major driver of impact of non-native herbivorous insects.Our novel, integrated model predicts whether a non-native insect not yet present in North America will have a one in 6.5 to a one in 2,858 chance of causing widespread mortality of a conifer species if established (R 2 = 0.91) Synthesis and applications. With this advancement, the risk to other conifer host species and regions can be assessed, and regulatory and pest management efforts can be more efficiently prioritized.

Conventional land-use intensification reduces species richness and increases production: A global meta-analysis.

Most current research on land-use intensification addresses its potential to either threaten biodiversity or to boost agricultural production. However, little is known about the simultaneous effects of intensification on biodiversity and yield. To determine the responses of species richness and yield to conventional intensification, we conducted a global meta-analysis synthesizing 115 studies which collected data for both variables at the same locations. We extracted 449 cases that cover a variety of areas used for agricultural (crops, fodder) and silvicultural (wood) production. We found that, across all production systems and species groups, conventional intensification is successful in increasing yield (grand mean + 20.3%), but it also results in a loss of species richness (-8.9%). However, analysis of sub-groups revealed inconsistent results. For example, small intensification steps within low intensity systems did not affect yield or species richness. Within high-intensity systems species losses were non-significant but yield gains were substantial (+15.2%). Conventional intensification within medium intensity systems revealed the highest yield increase (+84.9%) and showed the largest loss in species richness (-22.9%). Production systems differed in their magnitude of richness response, with insignificant changes in silvicultural systems and substantial losses in crop systems (-21.2%). In addition, this meta-analysis identifies a lack of studies that collect robust biodiversity (i.e. beyond species richness) and yield data at the same sites and that provide quantitative information on land-use intensity. Our findings suggest that, in many cases, conventional land-use intensification drives a trade-off between species richness and production. However, species richness losses were often not significantly different from zero, suggesting even conventional intensification can result in yield increases without coming at the expense of biodiversity loss. These results should guide future research to close existing research gaps and to understand the circumstances required to achieve such win-win or win-no-harm situations in conventional agriculture.

Correlation of native and exotic species richness: a global meta-analysis finds no invasion paradox across scales.

Support for the "biotic resistance hypothesis," that species-rich communities are more successful at resisting invasion by exotic species than are species-poor communities, has long been debated. It has been argued that native-exotic richness relationships (NERR) are negative at small spatial scales and positive at large scales, but evidence for the role of spatial scale on NERR has been contradictory. However, no formal quantitative synthesis has previously examined whether NERR is scale-dependent across multiple studies, and previous studies on NERR have not distinguished spatial grain and extent, which may drive very different ecological processes. We used a global systematic review and hierarchical mixed-effects meta-analysis to provide a comprehensive quantitative assessment of the patterns of NERR over a range of spatial grain sizes and spatial extents, based on 204 individual cases of observational (non-experimental) NERRs from 101 publications. We show that NERR was indeed highly scale dependent across studies and increased with the log of grain size. However, mean NERR was not negative at any grain size, although there was high heterogeneity at small grain sizes. We found no clear patterns of NERR across different spatial extents, suggesting that extent plays a less important role in determining NERR than does grain, although there was a complex interaction between extent and grain size. Almost all studies on NERR were conducted in North America, western Europe, and a few other regions, with little information on tropical or Arctic regions. We did find that NERR increased northward in temperate regions and also varied with longitude. We discuss possible explanations for the patterns we found, and caution that our results do not show that invasive species are benign or have no negative consequences for biodiversity preservation. This study represents the first global quantitative analysis of scale-based NERR, and casts doubt on the existence of an "invasion paradox" of negative NERR at small scales and positive correlations at large scales in non-experimental studies.

Empowering peer reviewers with a checklist to improve transparency.

Peer review is widely considered fundamental to maintaining the rigour of science, but it often fails to ensure transparency and reduce bias in published papers, and this systematically weakens the quality of published inferences. In part, this is because many reviewers are unaware of important questions to ask with respect to the soundness of the design and analyses, and the presentation of the methods and results; also some reviewers may expect others to be responsible for these tasks. We therefore present a reviewers' checklist of ten questions that address these critical components. Checklists are commonly used by practitioners of other complex tasks, and we see great potential for the wider adoption of checklists for peer review, especially to reduce bias and facilitate transparency in published papers. We expect that such checklists will be well received by many reviewers.

Meta-analysis and the science of research synthesis.

Meta-analysis is the quantitative, scientific synthesis of research results. Since the term and modern approaches to research synthesis were first introduced in the 1970s, meta-analysis has had a revolutionary effect in many scientific fields, helping to establish evidence-based practice and to resolve seemingly contradictory research outcomes. At the same time, its implementation has engendered criticism and controversy, in some cases general and others specific to particular disciplines. Here we take the opportunity provided by the recent fortieth anniversary of meta-analysis to reflect on the accomplishments, limitations, recent advances and directions for future developments in the field of research synthesis.

Potentially dangerous consequences for biodiversity of solar geoengineering implementation and termination.

Solar geoengineering is receiving increased policy attention as a potential tool to offset climate warming. While climate responses to geoengineering have been studied in detail, the potential biodiversity consequences are largely unknown. To avoid extinction, species must either adapt or move to track shifting climates. Here, we assess the effects of the rapid implementation, continuation and sudden termination of geoengineering on climate velocities-the speeds and directions that species would need to move to track changes in climate. Compared to a moderate climate change scenario (RCP4.5), rapid geoengineering implementation reduces temperature velocities towards zero in terrestrial biodiversity hotspots. In contrast, sudden termination increases both ocean and land temperature velocities to unprecedented speeds (global medians >10 km yr-1) that are more than double the temperature velocities for recent and future climate change in global biodiversity hotspots. Furthermore, as climate velocities more than double in speed, rapid climate fragmentation occurs in biomes such as temperate grasslands and forests where temperature and precipitation velocity vectors diverge spatially by >90°. Rapid geoengineering termination would significantly increase the threats to biodiversity from climate change.

Scale-dependent portfolio effects explain growth inflation and volatility reduction in landscape demography.

Population demography is central to fundamental ecology and for predicting range shifts, decline of threatened species, and spread of invasive organisms. There is a mismatch between most demographic work, carried out on few populations and at local scales, and the need to predict dynamics at landscape and regional scales. Inspired by concepts from landscape ecology and Markowitz's portfolio theory, we develop a landscape portfolio platform to quantify and predict the behavior of multiple populations, scaling up the expectation and variance of the dynamics of an ensemble of populations. We illustrate this framework using a 35-y time series on gypsy moth populations. We demonstrate the demography accumulation curve in which the collective growth of the ensemble depends on the number of local populations included, highlighting a minimum but adequate number of populations for both regional-scale persistence and cross-scale inference. The attainable set of landscape portfolios further suggests tools for regional population management for both threatened and invasive species.

Transparency in Ecology and Evolution: Real Problems, Real Solutions.

To make progress scientists need to know what other researchers have found and how they found it. However, transparency is often insufficient across much of ecology and evolution. Researchers often fail to report results and methods in detail sufficient to permit interpretation and meta-analysis, and many results go entirely unreported. Further, these unreported results are often a biased subset. Thus the conclusions we can draw from the published literature are themselves often biased and sometimes might be entirely incorrect. Fortunately there is a movement across empirical disciplines, and now within ecology and evolution, to shape editorial policies to better promote transparency. This can be done by either requiring more disclosure by scientists or by developing incentives to encourage disclosure.

Meta-analysis and meta-regression of transcriptomic responses to water stress in Arabidopsis.

The large amounts of transcriptome data available for Arabidopsis thaliana make a compelling case for the need to generalize results across studies and extract the most robust and meaningful information possible from them. The results of various studies seeking to identify water stress-responsive genes only partially overlap. The aim of this work was to combine transcriptomic studies in a systematic way that identifies commonalities in response, taking into account variation among studies due to batch effects as well as sampling variation, while also identifying the effect of study-specific variables, such as the method of applying water stress, and the part of the plant the mRNA was extracted from. We used meta-analysis, the quantitative synthesis of independent research results, to summarize expression responses to water stress across studies, and meta-regression to model the contribution of covariates that may affect gene expression. We found that some genes with small but consistent differential responses become evident only when results are synthesized across experiments, and are missed in individual studies. We also identified genes with expression responses that are attributable to use of different plant parts and alternative methods for inducing water stress. Our results indicate that meta-analysis and meta-regression provide a powerful approach for identifying a robust gene set that is less sensitive to idiosyncratic results and for quantifying study characteristics that result in contrasting gene expression responses across studies. Combining meta-analysis with individual analyses may contribute to a richer understanding of the biology of water stress responses, and may prove valuable in other gene expression studies.

Landscape Demography: Population Change and its Drivers Across Spatial Scales.

Demographic studies of plants and animals have a rich history and literature in ecology, and are important for both fundamental and applied ecology and conservation biology. Almost all demographic work has focused on intensive studies in which births, deaths, growth of individuals, and related measures are quantified in a single population or a few populations. This has been for practical reasons due to the high demands of labor required for this work, and because the questions addressed in these studies have been asked at the level of individual populations, with implicit assumptions about generalizing from the results. We introduce the concept of landscape demography, the study of the demographic properties of populations and their drivers at multiple spatial scales, and of how the relationships among populations and their drivers at any one scale influence demographic outcomes at other scales. We explore the ways in which considering the dynamics of ensembles of populations at different spatial scales can advance progress in thinking about ecological issues of high current interest such as biological invasions, range expansions and contractions due to climate change, and the decline of threatened species, as well as fundamental ecological and evolutionary questions.

Harmonizing Biodiversity Conservation and Productivity in the Context of Increasing Demands on Landscapes.

Biodiversity conservation and agricultural production are often seen as mutually exclusive objectives. Strategies for reconciling them are intensely debated. We argue that harmonization between biodiversity conservation and crop production can be improved by increasing our understanding of the underlying relationships between them. We provide a general conceptual framework that links biodiversity and agricultural production through the separate relationships between land use and biodiversity and between land use and production. Hypothesized relationships are derived by synthesizing existing empirical and theoretical ecological knowledge. The framework suggests nonlinear relationships caused by the multifaceted impacts of land use (composition, configuration, and intensity). We propose solutions for overcoming the apparently dichotomous aims of maximizing either biodiversity conservation or agricultural production and suggest new hypotheses that emerge from our proposed framework.