Mary I. O’Connor’s research while affiliated with University of British Columbia and other places

Indigenous-driven and community-partnered research projects seeking to develop salient, legitimate, and credible knowledge bases for environmental decision-making require a multiple knowledge systems approach. When involving partners in addition to communities, diverging perspectives and priorities may arise, making the pathways to engaging in principled research while generating actionable knowledge unclear to disciplinarily-trained natural science researchers. Here, we share insights from the Eeyou Coastal Habitat Comprehensive Research Project (CHCRP), an interdisciplinary, Cree-driven community-academic partnership. This project brought together Cree community members, regional organizations, industry (Hydro-Québec), and academics from seven universities across Canada to address the unprecedented loss of seagrass Zostera marina (eelgrass), the concurrent decline in migratory Canada geese and its impact on fall goose harvest activities in Eeyou Istchee. After describing the history and context of the project, we discuss the challenges, complexities, and benefits of the collaborative approach balancing saliency, legitimacy, and credibility of the knowledge produced. We suggest the paper may be of use to researchers and partners seeking to engage in principled and actionable research related to environmental change including impacts of past development.

We present a perspective on how the Eeyou (James Bay Cree) from Eeyou Istchee (Eastern James Bay, Québec) understand the transformation of their traditional fall goose hunt system as a consequence of social and environmental changes across marine and terrestrial ecosystems with drivers operating at the local, regional and continental scales. Eeyou land users from the Chisasibi and Wemindji First Nations report that their traditional fall goose hunt underwent a “turning point” during the early 2000s. Not only did the abundance of Canadian geese reach a historical low, but their feeding and migratory behavior became unpredictable. Eeyou land users associate such abrupt changes with the massive eelgrass die-off of the late 1990s, the onset of the effects of climate change on coastal habitats experienced since the 1970s, and agricultural development along geese flyways. This manuscript is an outcome of the Eeyou Knowledge component of the Coastal Habitat Comprehensive Research Project (2016–2022) and followed a community-based case study approach that included 28 semi-structured interviews and 14 mapping interviews with Eeyou research contributors. The findings presented here underscore the capacity of Indigenous knowledge to make sense of the multifaceted impacts of environmental change across various dimensions and layers of their social-ecological system, including management strategies and values.

Information processing is increasingly recognized as a fundamental component of life in variable environments, including the evolved use of environmental cues, biomolecular networks, and social learning. Despite this, ecology lacks a quantitative framework for understanding how population, community, and ecosystem dynamics depend on information processing. Here, we review the rationale and evidence for ‘fitness value of information’ (FVOI), and synthesize theoretical work in ecology, information theory, and probability behind this general mathematical framework. The FVOI quantifies how species' per capita population growth rates can depend on the use of information in their environment. FVOI is a breakthrough approach to linking information processing and ecological and evolutionary outcomes in a changing environment, addressing longstanding questions about how information mediates the effects of environmental change and species interactions.

Despite the key role of biotic interactions in structuring ecological communities, their influence is often overlooked in predictions of how communities respond to environmental change. Here, we present an experiment that tests hypotheses based on metacommunity theory about how abiotic responses, biotic interactions, and dispersal jointly determine the response of ecological communities to environmental perturbations. We established experimental zooplankton metacommunities across spatial temperature gradients, connected by three levels of dispersal, that experienced natural temporal variation in ambient temperature. Prior to a mid-summer heatwave, community composition varied across the spatial temperature gradients. The heatwave homogenized the metacommunities and when conditions cooled, communities diverged into multiple compositional states that were not associated with temperature. These states appear to have been driven by biotic interactions that prevented the reestablishment of the pre-heatwave thermal compositional gradients. This highlights how biotic interactions can prevent metacommunities from tracking temperature changes via dispersal-facilitated species sorting.

Over the last few decades, there has been an increasing recognition for seagrasses' contribution to the functioning of nearshore ecosystems and climate change mitigation. Nevertheless, seagrass ecosystems have been deteriorating globally at an accelerating rate during recent decades. In 2017, research into the condition of eelgrass (Zostera marina) along the eastern coast of James Bay, Canada, was initiated in response to reports of eelgrass decline by the Cree First Nations of Eeyou Istchee. As part of this research, we compiled and analyzed two decades of eelgrass cover data and three decades of eelgrass monitoring data (biomass and density) to detect changes and assess possible environmental drivers. We detected a major decline in eelgrass condition between 1995 and 1999, which encompassed the entire east coast of James Bay. Surveys conducted in 2019 and 2020 indicated limited changes post decline, e.g., low eelgrass cover (<25%), low aboveground biomass, smaller shoots than before 1995, and marginally low densities persisted at most sites. Overall, the synthesized datasets show a 40 % loss of eelgrass meadows with > 50% cover in eastern James Bay since 1995, representing the largest scale eelgrass decline documented in eastern Canada since the massive die-off event that occurred in the 1930s along the North Atlantic coast. Using biomass data collected since 1982, but geographically limited to the sector of the coast near the regulated La Grande River, generalized additive modeling revealed eelgrass meadows are affected by local sea surface temperature, early ice breakup and higher summer freshwater discharge. Our results caution against assuming subarctic seagrass ecosystems have avoided recent global declines or will benefit from ongoing climate warming.

Parasitism is expected to change in a warmer future, but whether warming leads to substantial increases in parasitism remains unclear. Understanding how warming effects on parasitism in individual hosts (e.g. parasite load) translate to effects on population‐level parasitism (e.g. prevalence, R0) remains a major knowledge gap. We conducted a literature review and identified 24 host–parasite systems that had information on the temperature dependence of parasitism at both individual host and host population levels: 13 vector‐borne systems and 11 environmentally transmitted systems. We found a strong positive correlation between the thermal optima of individual‐ and population‐level parasitism, although several of the environmentally transmitted systems exhibited thermal optima >5°C apart between individual and population levels. Parasitism thermal optima were close to vector performance thermal optima in vector‐borne systems but not hosts in environmentally transmitted systems, suggesting these thermal mismatches may be more common in certain types of host–parasite systems. We also adapted and simulated simple models for both types of transmission modes and found the same pattern across the two modes: thermal optima were more strongly correlated across scales when there were more traits linking individual‐ to population‐level processes. Generally, our results suggest that information on the temperature dependence, and specifically the thermal optimum, at either the individual or population level should provide a useful—although not quantitatively exact—baseline for predicting temperature dependence at the other level, especially in vector‐borne parasite systems. Environmentally transmitted parasitism may operate by a different set of rules, in which temperature dependence is decoupled in some systems, requiring the need for trait‐based studies of temperature dependence at individual and population levels.

Parasitism – the interaction between a parasite and its host – is expected to change in a warmer future, but the direction and magnitude of this change is uncertain. One challenge is understanding whether warming effects will be similar on individual hosts (e.g., parasite burden) compared to on population-level parasitism (e.g., prevalence, R 0 ). Examining thirteen empirical systems, we found a strong positive relationship between the thermal optima of individual- and population-level parasitism. We also found that parasitism thermal optima were close to host performance thermal optima in mosquito – parasite systems but not in non-mosquito – parasite systems. A simple mechanistic model showed how population-level parasitism thermal optima can be similar to individual-level parasitism thermal optima even under conditions where parasite transmission has a considerably higher thermal optimum. These results provide a key step towards finding general rules for how warming temperatures should affect parasitism in individuals, populations, and ecosystems.