Long-Term Monitoring in Ecology and Evolution: Establishing a Sound Baseline to Help Inform our Future

Ecology and evolution research first originated from efforts to track changes in plant and animal populations through time. However, in recent years long-term monitoring has largely fallen out of favour in the scientific community, partly because it can be perceived as being less sophisticated, less rigorous, and less question-driven than more contemporary approaches. Funding to support long-term monitoring tends to be difficult to obtain, monitoring usually yields insights according to timelines that exceed graduate student degrees or grant cycles, and manuscripts supported by monitoring are often viewed poorly by reviewers and editors and thus succumb to the ‘file drawer’ problem or are published in low-impact journals. However, in many cases long-term monitoring may provide our only diary of past conditions and therefore can serve as an invaluable baseline for tracking or forecasting future change. Monitoring remains at the core of environmental impact assessment and may be required as a condition for development project approval. New technologies and approaches may revolutionize long-term monitoring by automating data collection, providing novel measurements, and reducing potential subjectivity and uncertainty in data interpretation, but validation and calibration of new methods is a non-glamorous but essential endeavour. Accordingly, long-term monitoring should be re-imagined as a necessary aspect of contemporary ecology and evolution and thus given deserved attention. To achieve this goal, efforts should focus on developing, testing and standardizing monitoring approaches to ensure that programs are designed to collect reliable data both efficiently and in a manner that is amenable to robust analysis and interpretation.  In addition, the research community needs to secure storage and open access of collected data for future use, and peer-reviewed journals should be more accepting of sound, descriptive work.

This Research Topic will serve as a clearing house for new perspectives and emerging directions in long-term monitoring in ecology and evolution. We believe that many existing datasets have yet to be fully exploited for new insights into past and present patterns of global change, including from citizen science programs, harvest statistics, biological control programs, and environmental impact assessments. New techniques like eDNA measurement, non-invasive genetic sampling, and remotely-activated trail cameras and acoustic recording units can provide long-term data both consistently and efficiently, but sampling design and statistical treatment need to be optimized and validated. New technologies like meta-barcoding and high-throughput sequencing hold the potential to inform on patterns as far reaching as community structure and gene activity, but robust sampling must begin now to support future insight into changes to biodiversity or evolutionary processes. Ultimately, this special section will assess the current state of long-term monitoring in ecology and evolution and identify best practices to support a robust approach into the future. A secondary goal is to raise the profile of long-term monitoring and establish a broad community of researchers and practitioners who will champion its needs and relevance.

We encourage submissions that broadly address long-term monitoring in ecology and evolution, including the themes identified in the ‘goal’ section. We invite a mixture of empirical papers, review articles, and perspective pieces and are looking for contributions from researchers, environmental professionals, data analysts, and modelers. Articles can cover topics ranging from observed patterns and processes, new monitoring techniques, study design and analytical considerations, and forecasting future trends. Perspective pieces that address gaps in long-term monitoring and future needs and directions are especially encouraged. Likewise, papers that convincingly assign causal links between response and predictor variables from long-term monitoring datasets are sought. Importantly, empirical submissions should be question-driven and manuscripts simply documenting trends or having weak inference must clearly illustrate how the work contributes to novel insight or will provide vital background information in understanding ecological processes. All articles should touch on broader implications of the research such as its relevance to tracking environmental change, ecological forecasting, or implications to best practices or policy decisions. Inquiries about topic suitability can be directed to Dennis Murray (dennismurray@trentu.ca), Jenilee Gobin (jenileegobin@trentu.ca), Karin Hårding (karin.harding@bioenv.gu.se) and Charles Krebs (krebs@zoology.ubc.ca).