The conservation of biodiversity requires various forms of evidence to ensure effective outcomes. In this study, we provide an updated assessment of the state of evidence-based decision-making in Canada’s protected areas organizations by examining practitioner perceptions of: ( i) the value and use of various forms of evidence, ( ii) the availability of evidence to support decisions, and ( iii) the extent to which various institutional and behavioural barriers influence the use of evidence. Our results compare national surveys conducted in 2019 and 2013, revealing a significant and concerning decline in the use of all forms of evidence. We found significant declines in the use of peer-reviewed literature, local knowledge, and Indigenous knowledge. Our results correspondingly demonstrate a host of systemic barriers to the effective use of evidence, including a lack of trust, how to deal with uncertainty, and limited training. These challenges persist at a time when the quantity of information is greater than ever, and recognition of the value of Indigenous knowledge is relatively high (and increasing). Leadership is required to cultivate more relevant evidence, to embed scientists and Indigenous Knowledge-Holders in conservation organizations, to (re)establishing knowledge sharing forums, and to establish accountability and reporting measures to support efforts aimed at effectively achieving Canada’s biodiversity conservation goals.

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Hunting can influence the abundance and distribution of animals and act as a source of conflict among recreational user groups. Thus, land managers benefit from tools that can generate information about when and where hunting occurs.We used passive acoustic monitoring to examine spatiotemporal patterns of hunting-related gunshots at 91 locations in a protected area in Alberta, Canada. We compared 2 methods for detecting gunshots from recordings: a recognizer that used complex pattern recognition and an energy detector that detected loud sounds regardless of their acoustic features.The recognizer primarily detected faint sounds, and multiple observers showed low levels of agreement (37%) with respect to whether sounds were gunshots or not, suggesting it produced ambiguous data. The recognizer also missed many loud, clear gunshots for unknown reasons. The energy detector, in contrast, detected loud sounds upon which observers showed near-unanimous agreement (99%) on their identity. Gunshots missed by the energy detector could be because they were too quiet (i.e., too far away to be detected).Thus, despite detecting fewer gunshots overall, the energy detector produced higher quality data that were easier to interpret. We analyzed 249 gunshots detected with the energy detector, and found that hunting was concentrated near vehicle access points and peaked on Saturdays, and that

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