Data and information management for the monitoring of biodiversity in Alberta

Abstract

The Alberta Biodiversity Monitoring Institute (ABMI) monitors large-scale responses of biodiversity to environmental change in Alberta, Canada, based on standardized and ongoing data collection. In this case study, we show that such a standardized monitoring system has many data management challenges. In the almost 20 years since the conception of the Institute, we have identified 4 key characteristics that are required for large-scale, long-term biodiversity monitoring programs to be operational: 1) data must be publicly accessible; 2) methods and terminology must be standardized to facilitate consistency around data and information collection, analysis, and reporting; 3) the information system must be flexible so that components can be modified or added without compromising the functionality of the other components or the whole system; and 4) the system must be scalable so that it can support input, storage, and retrieval as data load increases. These characteristics are important to ensure that the products and tools generated from our monitoring program can support management at large spatial scales in the complex socio-ecological system of Alberta. Ó 2015 The Wildlife Society.

Improving taxonomic resolution in large‐scale freshwater biodiversity monitoring: an example using wetlands and Odonata

“…The Alberta Biodiversity Monitoring Institute (ABMI) tracks biodiversity distributions and trends throughout Alberta (Sólymos et al ., ), focusing on several taxonomic groups including aquatic macroinvertebrates (http://www.abmi.ca). The field programme centres on a systematically spaced (20‐km) point grid (Fig.…”

“…Long‐term, large‐scale monitoring has become integral to biodiversity conservation in the Anthropocene (Lindenmayer & Likens, ; Burton et al ., ; Schmeller et al ., ). Major initiatives and programmes (eg, Canadian Aquatic Biomonitoring Network, Long‐Term Ecological Research Program, South African National Biodiversity Assessment, UK Breeding Bird Survey) vary in objectives and scope but share the mission to assess the distributions and trends of many species or taxonomic groups over large areas (eg, regions) through an extended period of time (Yoccoz et al ., ; Nichols & Williams, ; Nielsen et al ., ; Haughland et al ., ; Sólymos et al ., ).…”

Systematic data management

“…that discuss the challenges of running long-term and large-scale research programs (Applegate 2015, Hunt et al 2015, Sólymos et al 2015, and Sutter et al 2015. However, the conceptual nature and comprehensive scope of these articles precludes them as a simple introduction to the topic.…”

The importance of data management in wildlife conservation

“…The second case study discusses data management challenges for a large‐scale biodiversity monitoring program in Alberta, Canada (Sólymos et al ), using strategies that are not uncommon to those of many monitoring programs. The third case study—data management for the Boreal Avian Modeling project (Barker et al )—presents an example of successful reuse of data collected by others to obtain insights not available from the original data.…”