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The Arctic tundra has a relatively low biodiversity but species living there have unique adaptations and are exposed to unprecedented rates of climate warming. Monitoring changes in Arctic biodiversity and identifying the driving forces is thus a pressing issue. Bylot Island in the Canadian Arctic has one of the longest and most comprehensive monitoring programs of the tundra food web, spanning four decades. We provide a historical overview of ecological studies on Bylot Island, summarize their key scientific contributions, show their impacts, and present the ingredients for the success of the program and the main challenges encountered. Some major contributions include demonstrating the key role of predation in structuring the tundra food web, the importance of exchanges between ecosystems for the persistence of top predators and their cascading effects on trophic interactions, the apparent resistance of the vertebrate biota to climate warming, the need to consider multiple hypotheses to explain northward range expansion of species and the benefits of integrating scientific data and local knowledge into ecological monitoring. The program has produced >250 journal articles and >80 graduate student theses, which generated >7,700 citations in the scientific literature. A high proportion (65%) of the articles had more citations than comparable publications in their field. The longevity and success of the program can be attributed to several factors, including a researcher-driven (i.e. bottom-up) approach to design the monitoring; long-term commitment of a small number of dedicated researchers and the strong participation of graduate students; the adoption of a food web rather than a single species perspective; extensive presence in the field; the combination of several methodological approaches; and the use of multiple spatial scales adapted to research questions of interest. Challenges encountered include funding issues, transfer of expertise over time, limited spatial replication, statistical design and maintaining partnerships. Robust monitoring is essential to provide sound baseline to detect future changes, and lessons learned from our program could improve future monitoring schemes in the Arctic. Paradoxically, we believe that ecological monitoring on Bylot Island has been successful in large part because it was not originally designed as a monitoring program per se.

Seasonal migrants transport energy, nutrients, contaminants, parasites and diseases, while also connecting distant food webs between communities and ecosystems, which contributes to structuring meta-communities and meta-ecosystems. However, we currently lack a framework to characterize the structure of the spatial connections maintained by all migratory species reproducing or wintering in a given community. Here, we use a network approach to represent and characterize migratory pathways at the community level and provide an empirical description of this pattern from a High-Arctic terrestrial community. We define community migration networks as multipartite networks representing different biogeographic regions connected with a focal community through the seasonal movements of its migratory species. We focus on the Bylot Island High-Arctic terrestrial community, a summer breeding ground for several migratory species. We define the non-breeding range of each species using tracking devices, or range maps refined by flyways and habitat types. We show that the migratory species breeding on Bylot Island are found across hundreds of ecoregions on several continents during the non-breeding period and present a low spatial overlap. The migratory species are divided into groups associated with different sets of ecoregions. The non-random structure observed in our empirical community migration network suggests evolutionary and geographic constraints as well as ecological factors act to shape migrations at the community level. Overall, our study provides a simple and generalizable framework as a starting point to better integrate migrations at the community level. Our framework is a far-reaching tool that could be adapted to address the seasonal transport of energy, contaminants, parasites and diseases in ecosystems, as well as trophic interactions in communities with migratory species.

The functional response is at the core of any predator-prey interactions as it establishes the link between trophic levels. The use of inaccurate functional response can profoundly affect the outcomes of population and community models. Yet most functional responses are evaluated using phenomenological models which often fail to discriminate among functional response shapes and cannot identify the proximate mechanisms regulating predator acquisition rates. Using a combination of behavioral, demographic, and experimental data collected over 20 years, we develop a mechanistic model based on species traits and behavior to assess the functional response of a generalist mammalian predator, the arctic fox (Vulpes lagopus), to various tundra prey species (lemmings and the nests of geese, passerines, and sandpipers). Predator acquisition rates derived from the mechanistic model were consistent with field observations. Although acquisition rates slightly decrease at high goose nest and lemming densities, none of our simulations resulted in a saturating response in all prey species. Our results highlight the importance of predator searching components in predator-prey interactions, especially predator speed, while predator acquisition rates were not limited by handling processes. By combining theory with field observations, our study provides support that the predator acquisition rate is not systematically limited at the highest prey densities observed in a natural system. Our study also illustrates how mechanistic models based on empirical estimates of the main components of predation can generate functional response shapes specific to the range of prey densities observed in the wild. Such models are needed to fully untangle proximate drivers of predator-prey population dynamics and to improve our understanding of predator-mediated interactions in natural communities.

The grand ambition of theorists studying ecology and evolution is to discover the logical and mathematical rules driving the world's biodiversity at every level from genetic diversity within species to differences between populations, communities, and ecosystems. This ambition has been difficult to realize in great part because of the complexity of biodiversity. Theoretical work has led to a complex web of theories, each having non-obvious consequences for other theories. Case in point, the recent realization that genetic diversity involves a great deal of temporal and spatial stochasticity forces theoretical population genetics to consider abiotic and biotic factors generally reserved to ecosystem ecology. This interconnectedness may require theoretical scientists to adopt new techniques adapted to reason about large sets of theories. Mathematicians have solved this problem by using formal languages based on logic to manage theorems. However, theories in ecology and evolution are not mathematical theorems, they involve uncertainty. Recent work in Artificial Intelligence in bridging logic and probability theory offers the opportunity to build rich knowledge bases that combine logic's ability to represent complex mathematical ideas with probability theory's ability to model uncertainty. We describe these hybrid languages and explore how they could be used to build a unified knowledge base of theories for ecology and evolution.

Temperature is the most significant environmental gradient at the global scale, impacting the distributions of species and their ecological interactions. It is now established that temperature affects several biological rates and body mass, and can, in turn, alter interaction strength. Latitudinal variation in the strength of interactions has been observed for trophic and competitive interactions and many studies support that biotic interactions are more intense at low latitudes. Nevertheless, the mechanisms underlying the temperature dependence of trophic regulation, the effect of consumers on their preys, remain unclear. The aim of our study is to get better insights on the effects of temperature on trophic regulation. We used a consumer-resource model and considered that organisms' biological rates present a unimodal thermal response and that body mass decreases with temperature. We compared three measures of interaction strength: per capita, per population and net interaction strength. Our results demonstrate that the effect of temperature on interaction strength is contingent upon which species' biological rates are temperature dependent. When all biological rates are temperature dependent, the thermal response of interaction strength is hump-shaped following the scaling of search rate, whilst it is monotonically decreasing when only mortality rates vary with temperature. Finally, we show that temperature can indirectly impact trophic interaction strength through the temperature-size rule. A decrease in organisms' body size due to temperature induces a decrease in per capita and per population interaction strength and tend to decrease net interaction strength, depending on which trophic level follows the temperature-size rule. Our analysis gives an overview of how temperature, through various effects, may impact different measures of interaction strength.

Scientists, policy makers, and journalists are three key, interconnected players involved in prioritizing and implementing solutions to mitigate the consequences of anthropogenic pressures on the environment. The way in which information is framed and expertise is communicated by the media is crucial for political decisions and for the integrated management of environmental issues. Here we present a comparative study of scientific literature and press articles addressing climate change and biodiversity. We extensively scrutinized the scientific literature, research funding, and press articles from the USA, Canada, and United Kingdom addressing climate change and biodiversity issues between 1991 and 2016. We found that media coverage of climate change was up to eight times higher compared to biodiversity. This discrepancy could not be explained by different scientific output between the two issues. Moreover, climate change media coverage was often related to specific events whereas no such indication of a connection was found in the case of biodiversity. An international communication strategy is urgently required to raise public awareness on biodiversity issues. We discussed several initiatives that scientists could undertake to better communicate major discoveries to the public and policy makers.