Moving to 3D: relationships between coral planar area, surface area and volume.

Coral reefs are a valuable and vulnerable marine ecosystem. The structure of coral reefs influences their health and ability to fulfill ecosystem functions and services. However, monitoring reef corals largely relies on 1D or 2D estimates of coral cover and abundance that overlook change in ecologically significant aspects of the reefs because they do not incorporate vertical or volumetric information. This study explores the relationship between 2D and 3D metrics of coral size. We show that surface area and volume scale consistently with planar area, albeit with morphotype specific conversion parameters. We use a photogrammetric approach using open-source software to estimate the ability of photogrammetry to provide measurement estimates of corals in 3D. Technological developments have made photogrammetry a valid and practical technique for studying coral reefs. We anticipate that these techniques for moving coral research from 2D into 3D will facilitate answering ecological questions by incorporating the 3rd dimension into monitoring

Assessing diverse evidence to improve conservation decision-making

Meeting the urgent need to protect and restore ecosystems requires effective decision‐making through wisely considering a range of evidence. However, weighing and assessing evidence to make complex decisions is challenging, particularly when evidence is of diverse types, subjects, and sources, and varies greatly in its quality and relevance. To tackle these challenges, we present the Balance Evidence Assessment Method (BEAM), an intuitive way to weigh and assess the evidence relating to the core assumptions underpinning the planning and implementation of conservation projects, strategies, and actions. Our method directly tackles the question of how to bring together diverse evidence whilst assessing its relevance, reliability, and strength of support for a given assumption, which can be mapped, for example to a Theory of Change. We consider how simple principles and safeguards in applying this method could help to respectfully, and equitably, include more local forms of knowledge when assessing assumptions, such as by ensuring diverse groups of individuals contribute and assess evidence. The method can be flexibly applied within existing decision‐making tools, platforms, and frameworks whenever assumptions (i.e., claims and hypotheses) are made. This method could greatly facilitate and improve the weighing of diverse evidence to make decisions in a range of situations, from local projects to global policy platforms

Dynamic meta-analysis: a method of using global evidence for local decision making

Background Meta-analysis is often used to make generalisations across all available evidence at the global scale. But how can these global generalisations be used for evidence-based decision making at the local scale, if the global evidence is not perceived to be relevant to local decisions? We show how an interactive method of meta-analysis—dynamic meta-analysis—can be used to assess the local relevance of global evidence. Results We developed Metadataset (www.metadataset.com) as a proof-of-concept for dynamic meta-analysis. Using Metadataset, we show how evidence can be filtered and weighted, and results can be recalculated, using dynamic methods of subgroup analysis, meta-regression, and recalibration. With an example from agroecology, we show how dynamic meta-analysis could lead to different conclusions for different subsets of the global evidence. Dynamic meta-analysis could also lead to a rebalancing of power and responsibility in evidence synthesis, since evidence users would be able to make decisions that are typically made by systematic reviewers—decisions about which studies to include (e.g. critical appraisal) and how to handle missing or poorly reported data (e.g. sensitivity analysis). Conclusions In this study, we show how dynamic meta-analysis can meet an important challenge in evidence-based decision making—the challenge of using global evidence for local decisions. We suggest that dynamic meta-analysis can be used for subject-wide evidence synthesis in several scientific disciplines, including agroecology and conservation biology. Future studies should develop standardised classification systems for the metadata that are used to filter and weight the evidence. Future studies should also develop standardised software packages, so that researchers can efficiently publish dynamic versions of their meta-analyses and keep them up-to-date as living systematic reviews. Metadataset is a proof-of-concept for this type of software, and it is open source. Future studies should improve the user experience, scale the software architecture, agree on standards for data and metadata storage and processing, and develop protocols for responsible evidence use

A systematic map of cassava farming practices and their agricultural and environmental impacts using new ontologies: Agri‐ontologies 1.0

Cassava is consumed by 800 million people and is a staple crop in Africa. Its production may increase under climate change due to its high drought tolerance. We produced a systematic map of scientific studies about cassava farming practices, with the aim of identifying knowledge gaps and clusters. Our secondary aim was to develop a classification system for [1] farming interventions and [2] agricultural, economic and environmental outcomes. Standardised classification systems facilitate data reuse, including for evidence synthesis, and promote research efficiency. Following our published protocol, we searched eight publication databases using the search string ‘cassava OR mandioca OR manihot OR manioc OR yuca’ in December 2017. We screened 36,580 records and included publications that measured the impact of cassava farming practices on agricultural, economic or environmental outcomes, including yield, soil, water, wildlife and labour. We classified the resultant 1599 publications by interventions, outcomes, location, study year and study design. We assessed coding consistency using Kappa scores. We found regional knowledge clusters (Nigeria, Columbia and Brazil accounted for 45.5% of country occurrences) and gaps (e.g. the Democratic Republic of Congo). There were knowledge clusters for interventions testing cultivar type, fertiliser use and diversifying crop rotations and outcomes related to crop production (e.g. yield/biomass). We found knowledge gaps for environmental interventions and outcomes (e.g. 5% of studies measured pollutants or wildlife). In terms of study design, reporting standards were poor (e.g. 24% of studies did not report start dates), average study duration was 2 years, and average publication delays were 4 years. The Kappa scores indicated that we successfully developed consistent ontologies (named Agri-ontologies 1.0). The map and ontologies are available online: https://www.metadataset.com/. This systematic map of cassava farming practices can direct researchers and funders to knowledge gaps that need addressing, and reviewers to knowledge clusters for synthesis. Better research practices should be promoted within cassava research, as poor reporting standards, short study durations and long publication delays result in an ineffective research environment. This systematic map provides an evidence base for cassava production and the ontologies (Agri-ontologies 1.0) can be applied to other systems to facilitate more efficient and effective synthesis

Reducing publication delay to improve the efficiency and impact of conservation science.

Evidence-based decision-making is most effective with comprehensive access to scientific studies. If studies face significant publication delays or barriers, the useful information they contain may not reach decision-makers in a timely manner. This represents a potential problem for mission-oriented disciplines where access to the latest data is required to ensure effective actions are undertaken. We sought to analyse the severity of publication delay in conservation science-a field that requires urgent action to prevent the loss of biodiversity. We used the Conservation Evidence database to assess the length of publication delay (time from finishing data collection to publication) in the literature that tests the effectiveness of conservation interventions. From 7,447 peer-reviewed and non-peer-reviewed studies of conservation interventions published over eleven decades, we find that the raw mean publication delay was 3.2 years (±2SD = 0.1) and varied by conservation subject. A significantly shorter delay was observed for studies focused on Bee Conservation, Sustainable Aquaculture, Management of Captive Animals, Amphibian Conservation, and Control of Freshwater Invasive Species (Estimated Marginal Mean range from 1.4-1.9 years). Publication delay was significantly shorter for the non-peer-reviewed literature (Estimated Marginal Mean delay of 1.9 years ± 0.2) compared to the peer-reviewed literature (i.e., scientific journals; Estimated Marginal Mean delay of 3.0 years ± 0.1). We found publication delay has significantly increased over time (an increase of ~1.2 years from 1912 (1.4 years ± 0.2) to 2020 (2.6 years ± 0.1)), but this change was much weaker and non-significant post-2000s; we found no evidence for any decline. There was also no evidence that studies on more threatened species were subject to a shorter delay-indeed, the contrary was true for mammals, and to a lesser extent for birds. We suggest a range of possible ways in which scientists, funders, publishers, and practitioners can work together to reduce delays at each stage of the publication process

Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences

Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs.Fil: Christie, Alec P.. University of Cambridge; Reino UnidoFil: Abecasis, David. Universidad de Algarve. Centro de Ciencias del Mar; PortugalFil: Adjeroud, Mehdi. Université de Perpignan; Francia. Institut de Recherche Pour Le Developpement; FranciaFil: Alonso, Juan Carlos. Consejo Superior de Investigaciones Científicas. Museo Nacional de Ciencias Naturales; EspañaFil: Amano, Tatsuya. University of Queensland; AustraliaFil: Anton, Alvaro. Universidad del País Vasco. Facultad de Educación de Bilbao; EspañaFil: Baldigo, Barry P.. United States Geological Survey; Estados UnidosFil: Barrientos, Rafael. Universidad Complutense de Madrid; EspañaFil: Bicknell, Jake E.. University of Kent; Reino UnidoFil: Buhl, Deborah A.. United States Geological Survey; Estados UnidosFil: Cebrian, Just. Mississippi State University; Estados UnidosFil: Ceia, Ricardo S.. Universidad de Coimbra; PortugalFil: Cibils Martina, Luciana. Universidad Nacional de Río Cuarto. Facultad de Ciencias Exactas, Fisicoquímicas y Naturales. Departamento de Ciencias Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Clarke, Sarah. Marine Institute; IrlandaFil: Claudet, Joachim. Universite de Paris; Francia. Centre National de la Recherche Scientifique; FranciaFil: Craig, Michael D.. University of Western Australia; Australia. Murdoch University; AustraliaFil: Davoult, Dominique. Sorbonne University; FranciaFil: De Backer, Annelies. Flanders Research Institute for Agriculture, Fisheries and Food; BélgicaFil: Donovan, Mary K.. University of California; Estados Unidos. University of Hawaii at Manoa; Estados UnidosFil: Eddy, Tyler D.. University of South Carolina; Estados Unidos. Memorial University of Newfoundland; Canadá. Victoria University of Wellington; Nueva ZelandaFil: França, Filipe M.. Lancaster University; Reino UnidoFil: Gardner, Jonathan P. A.. Victoria University of Wellington; Nueva ZelandaFil: Harris, Bradley P.. Alaska Pacific University; Estados UnidosFil: Huusko, Ari. Natural Resources Institute Finland; FinlandiaFil: Jones, Ian L.. Memorial University of Newfoundland; CanadáFil: Kelaher, Brendan P.. Southern Cross University; AustraliaFil: Kotiaho, Janne S.. Universidad de Jyvaskyla; FinlandiaFil: López Baucells, Adrià. Universidad de Lisboa; Portugal. Smithsonian Tropical Research Institute; Panamá. Universidad Nacional de Colombia. Instituto de Investigaciones Amazonicas; Colombia. Museo de Ciencias Naturales de Granollers; EspañaFil: Major, Heather L.. University of New Brunswick; CanadáFil: Mäki Petäys, Aki. Voimalohi Oy; Finlandia. University of Oulu; Finlandi

Six years of demography data for 11 reef coral species

Scleractinian corals are colonial animals with a range of life history strategies, making up diverse species assemblages that define coral reefs. We tagged and tracked approximately 30 colonies from each of 11 species during seven trips spanning six years (2009-2015) in order to measure their vital rates and competitive interactions on the reef crest at Trimodal Reef, Lizard Island, Australia. Pairs of species were chosen from five growth forms where one species of the pair was locally rare (R) and the other common (C). The sampled growth forms were massive [Goniastrea pectinata (R) and G. retiformis (C)], digitate [Acropora humilis (R) and A. cf. digitifera (C)], corymbose [A. millepora (R) and A. nasuta (C)], tabular [A. cytherea (R) and A. hyacinthus (C)] and arborescent [A. robusta (R) and A. intermedia (C)]. An extra corymbose species with intermediate abundance, A. spathulata was included when it became apparent that A. millepora was too rare on the reef crest, making the 11 species in total. The tagged colonies were visited each year in the weeks prior to spawning. During visits, two or more observers each took 2-3 photographs of each tagged colony from directly above and on the horizontal plane with a scale plate to track planar area. Dead or missing colonies were recorded and new colonies tagged in order to maintain approximately 30 colonies per species throughout the six years of the study. In addition to tracking tagged corals, 30 fragments were collected from neighboring untagged colonies of each species for counting numbers of eggs per polyp (fecundity); and fragments of untagged colonies were brought into the laboratory where spawned eggs were collected for biomass and energy measurements. We also conducted surveys at the study site to generate size structure data for each species in several of the years. Each tagged colony photograph was digitized by at least two people. Therefore, we could examine sources of error in planar area for both photographers and outliners. Competitive interactions were recorded for a subset of species by measuring the margins of tagged colony outlines interacting with neighboring corals. The study was abruptly ended by Tropical Cyclone Nathan (Category 4) that killed all but nine of the over 300 tagged colonies in early 2015. Nonetheless, these data will be of use to other researchers interested in coral demography and coexistence, functional ecology, and parametrizing population, community and ecosystem models. The data set is not copyright restricted, and users should cite this paper when using the data.Publisher PDFPeer reviewe