Changes in water quality related to permafrost thaw may significantly impact zooplankton in small Arctic lakes.

Rising temperatures are leading to permafrost thaw over vast areas of the northern hemisphere. In the Canadian Arctic, permafrost degradation is causing significant changes in surface water quality due to the release of solutes that can alter conductivity, water clarity, and nutrient levels. For this study, we examined how changes in water quality associated with permafrost thaw might impact zooplankton, a group of organisms that play an important role in the food web of Arctic lakes. We conducted a biological and water quality survey of 37 lakes in the Mackenzie Delta region of Canada's Northwest Territories. We then used this data set to develop models linking variation in the abundance, diversity, and evenness of zooplankton communities to physicochemical, biological, and spatial variables. Subsequently, we used these models to predict how zooplankton communities might respond as water quality is altered by permafrost thaw. Our models explained 47%, 68%, and 69% of the variation in zooplankton abundance, diversity, and evenness, respectively. Importantly, the most parsimonious models always included variables affected by permafrost thaw, such as calcium and conductivity. Predictions based on our models suggest significant increases in zooplankton abundance (1.6-3.6 fold) and decreases in diversity (1.2-1.7 fold) and evenness (1.1-1.4 fold) in response to water quality changes associated with permafrost thaw. These changes are in line with those described for significant perturbations such as eutrophication, acidification, and the introduction of exotic species such as the spiny water flea (Bythotrephes). Given their important role in aquatic food webs, we expect these changes in zooplankton communities will have ramifications for organisms at higher (fish) and lower (phytoplankton) trophic positions in Arctic lakes.

Foresight science in conservation: Tools, barriers, and mainstreaming opportunities.

Foresight science is a systematic approach to generate future predictions for planning and management by drawing upon analytical and predictive tools to understand the past and present, while providing insights about the future. To illustrate the application of foresight science in conservation, we present three case studies: identification of emerging risks to conservation, conservation of at-risk species, and aid in the development of management strategies for multiple stressors. We highlight barriers to mainstreaming foresight science in conservation including knowledge accessibility/organization, communication across diverse stakeholders/decision makers, and organizational capacity. Finally, we investigate opportunities for mainstreaming foresight science including continued advocacy to showcase its application, incorporating emerging technologies (i.e., artificial intelligence) to increase capacity/decrease costs, and increasing education/training in foresight science via specialized courses and curricula for trainees and practicing professionals. We argue that failure to mainstream foresight science will hinder the ability to achieve future conservation objectives in the Anthropocene.