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Several recent papers have highlighted best practices, defined metadata standards and proposed checklists for reproducibility of species distribution models (SDMs). A new paper by Zurell et al. (2020) formalizes, extends and implements many of these ideas in a standardized protocol for reporting SDMs called ODMAP (Overview, Data, Model, Assessment, Prediction). ODMAP has the potential to revolutionize species distribution modeling, not through the development of new methods, but rather by providing a long overdue system to document, communicate and reproduce methods. ODMAP could lead to improved basic and applied science outcomes by increasing comprehension and transparency, and by guiding implementation of best practices. However, the impact that ODMAP has on SDMs depends in large part on the extent to which journals, reviewers and funding agencies encourage its use and whether mentors introduce it to the next generation of biodiversity scientists. Important next steps include formalizing mechanisms for the broader research community to participate in future development of ODMAP and related standards for best practices in biodiversity modeling. [ABSTRACT FROM AUTHOR]

Improving technology and increasing affordability mean that camera trapping—the use of remotely triggered cameras to photograph wildlife—is becoming an increasingly common tool in the monitoring and conservation of wild populations. Each camera trap study generates a vast amount of data, which need to be processed and labeled before analysis. Traditionally, processing camera trap data has been performed manually by entering data into a spreadsheet. This is time‐consuming, prone to human error, and data management may be inconsistent between projects, hindering collaboration. Recently, several programs have become available to facilitate and quicken data processing. Here, we review available software and assess their ability to better standardize camera trap data management and facilitate data sharing and collaboration. To identify available software for camera trap data management, we used internet searches and contacted researchers and practitioners working on large camera trap projects, as well as software developers. We tested all available programs against a range of software characteristics in addition to their ability to record a suite of important data variables extracted from images. We identified and reviewed 12 available programs for the management of camera trap data. These ranged from simple software assisting with the extraction of metadata from an image, through to comprehensive programs that facilitate data entry and analysis. Many of the programs tested were developed for use on specific studies and so do not cover all possible software or data collection requirements that different projects may have. We highlight the importance of a standardized software solution for camera trap data management. This approach would allow all possible data to be collected, enabling researchers to share data and contribute to other studies, as well as facilitating multi‐project comparisons. By standardizing camera trap data collection and management in this way, future studies would be better placed to guide conservation policy on a global level. The use of camera traps in ecology and conservation is increasingly common, and studies using camera traps can generate masses of data. These data are often handled and stored differently, hindering comparison and collaboration. We reviewed 12 camera trap data management programs and advise that that a universal approach to managing, storing, and analzsing camera trap data will facilitate collaborations and the sharing of data and will be beneficial to global conservation. [ABSTRACT FROM AUTHOR]

Abstract: DNA‐based techniques are increasingly used for measuring the biodiversity (species presence, identity, abundance and community composition) of terrestrial and aquatic ecosystems. While there are numerous reviews of molecular methods and bioinformatic steps, there has been little consideration of the methods used to collect samples upon which these later steps are based. This represents a critical knowledge gap, as methodologically sound field sampling is the foundation for subsequent analyses. We reviewed field sampling methods used for metabarcoding studies of both terrestrial and freshwater ecosystem biodiversity over a nearly three‐year period (n = 75). We found that 95% (n = 71) of these studies used subjective sampling methods and inappropriate field methods and/or failed to provide critical methodological information. It would be possible for researchers to replicate only 5% of the metabarcoding studies in our sample, a poorer level of reproducibility than for ecological studies in general. Our findings suggest greater attention to field sampling methods, and reporting is necessary in eDNA‐based studies of biodiversity to ensure robust outcomes and future reproducibility. Methods must be fully and accurately reported, and protocols developed that minimize subjectivity. Standardization of sampling protocols would be one way to help to improve reproducibility and have additional benefits in allowing compilation and comparison of data from across studies. [ABSTRACT FROM AUTHOR]