A combination of wildfires and defoliating insect outbreaks play an important role in the natural successional dynamics of North American boreal mixedwood forests, which, in the long term, change the post‐disturbance composition and structure of forest stands. After stand‐replacing disturbances (mainly wildfires), early successional hardwoods typically dominate the affected areas. Provided enough time following disturbances, the increasing recruitment of mid‐ to late‐successional softwoods as well as the mortality of hardwoods gradually change forest composition from hardwoods to admixtures of hardwood‐conifer species and conifer‐dominated stands in mid and late successional stages, respectively. Such mixedwoods are abundant across the southern Canadian boreal forest. In boreal Canada, mixedwoods are the most structurally heterogeneous forest ecosystems, are highly productive, and form an important source of timber supply. Here we present the EASTERN BOREAL MIXEDWOODS CANADA data set, which documents the changes in composition and structure of stands originating from eight different wildfires representing a chronosequence of 249 yr since fire in eastern Canada. This data set has been used in several different projects to study and model the influence of natural (e.g., insect outbreaks) and anthropogenic disturbances (e.g., harvesting) on the dynamics of post‐fire stands. The data set covers a high range of variability in stand composition and structure, explained by species establishment, dominance, and mixture. It thus constitutes a useful source of information to trace the dynamics of the main boreal tree species of eastern North America, from their establishment to their replacement at different spatial scales (e.g., from stand to landscape level). Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data. We are open to collaborate in developing or co‐authoring relevant research projects based on this data set.

Citizen science (CS) currently refers to the participation of non-scientist volunteers in any discipline of conventional scientific research. Over the last two decades, nature-based CS has flourished due to innovative technology, novel devices, and widespread digital platforms used to collect and classify species occurrence data. For scientists, CS offers a low-cost approach of collecting species occurrence information at large spatial scales that otherwise would be prohibitively expensive. We examined the trends and gaps linked to the use of CS as a source of data for species distribution models (SDMs), in order to propose guidelines and highlight solutions. We conducted a quantitative literature review of 207 peer-reviewed articles to measure how the representation of different taxa, regions, and data types have changed in SDM publications since the 2010s. Our review shows that the number of papers using CS for SDMs has increased at approximately double the rate of the overall number of SDM papers. However, disparities in taxonomic and geographic coverage remain in studies using CS. Western Europe and North America were the regions with the most coverage (73%). Papers on birds (49%) and mammals (19.3%) outnumbered other taxa. Among invertebrates, flying insects including Lepidoptera, Odonata and Hymenoptera received the most attention. Discrepancies between research interest and availability of data were as especially important for amphibians, reptiles and fishes. Compared to studies on animal taxa, papers on plants using CS data remain rare. Although the aims and scope of papers are diverse, species conservation remained the central theme of SDM using CS data. We present examples of the use of CS and highlight recommendations to motivate further research, such as combining multiple data sources and promoting local and traditional knowledge. We hope our findings will strengthen citizen-researchers partnerships to better inform SDMs, especially for less-studied taxa and regions. Researchers stand to benefit from the large quantity of data available from CS sources to improve global predictions of species distributions.

The impact of traditional even-aged forest management on landscape age structure, tree composition, and connectivity has been well documented. Very little, however, is known about the impact on stand structural diversity. This study aims to compare the structural and abiotic characteristics of forest stands disturbed by clearcut logging and by stand-replacing fire in Quebec’s boreal landscapes. We hypothesized that unlike fire, logging specifically targeted stands having a higher economic value, i.e., merchantable volume, leaving altered forest characteristics on post-harvested landscapes. We compared two aerial forest surveys of a 2200 km2 study area, one survey completed before any logging activity (preindustrial survey; 1980s), and the second survey collected >10 years after logging activity (modern survey; 2000s). Forest stands at the time of the preindustrial survey were primary forests. We identified stands as either burned, logged, or left aside after forest management of the area (remaining stands) between the two surveys and compared their structural and abiotic characteristics using logistic regression. The structural and abiotic characteristics of burned and logged stands differed significantly. Relative to the burned stands, logged stands were older, denser, and marked by poorer drainage and a higher proportion of black spruce; therefore post-harvest and post-burn landscapes differed in terms of their structural diversities. Traditional even-aged forest management has significantly altered the boreal forest landscape by targeting specific stands having higher economic value and leaving behind stands of lower economic value. Remaining high economic stands should be protected, and a more balanced approach to harvesting must be used in the context of ecosystem-based management.

Tree neighbourhood modelling has significantly contributed to our understanding of the mechanisms structuring communities. Investigations into the impact of neighbouring crowding on tree performance have generally been conducted at local scales, missing important regional-scale context such as the suitability of the climate for each species. Favourable climates may enhance tree performance, but this may come at the cost of increased neighbourhood crowding and competition negatively impacting survival and growth. Through the synthesis of continental-scale forest inventory and trait datasets from the northeast USA and Puerto Rico we present an analytical approach that elucidates the important interactions between local competitive and regional climatic contexts. Our results show strong asymmetries in competitive interactions and significant niche differences that are dependent on habitat suitability. The strong interaction between local neighbourhood and regional climate highlights the need for models that consider the interaction between these two processes that have been previously ignored.

Biophysical conditions, including climate, environmental stress, and habitat availability, are key drivers of many ecological processes (e.g., community assembly and productivity) and associated ecosystem services (e.g., carbon sequestration and fishery production). Furthermore, anthropogenic impacts such as coastal development and fishing can have drastic effects on the structure and function of marine ecosystems. Scientists need to account for environmental variation and human impacts to accurately model, manage, and conserve marine ecosystems. Although there are many types of environmental data available from global remote sensing and open-source data products, some are inaccessible to potential end-users because they exist as global layers in high temporal and spatial resolutions which require considerable computational power to process. Additionally, coastal locations often suffer from missing data or data quality issues which limit the utility of some global marine products for coastal sites. Herein we present the Marine Socio-Environmental Covariates dataset for the global oceans, which consists of environmental and anthropogenic variables summarized in ecologically relevant ways. The dataset includes four sets of environmental variables related to biophysical conditions (net primary productivity models corrected for shallow-water reflectance, wave energy including sheltered-coastline corrections) and landscape context (coral reef and land cover within varying radii). We also present two sets of anthropogenic variables, human population density (within varying radii) and distance to large population center, which can serve as indicators of local human impacts. We have paired global, summarized layers available for download with an online data querying platform that allows users to extract data for specific point locations with finer control of summary statistics. In creating these global layers and online platform, we hope to make the data accessible to a wide array of end-users with the goal of advancing marine ecosystem studies.

Although amphibians typically exhibit high site fidelity and low dispersal, they do undertake rare, long-distance movements. The factors influencing these events remain poorly understood, partly because amphibian spring movements tend to radiate from breeding sites and the animals are often difficult to locate at other times of the year. In this study, we investigate whether these movement patterns can be reproduced by a parsimonious model where foraging steps follow a heavy-tailed, Lévy alpha-stable distribution and individuals may either return to a previous refuge site or establish a new one. We consider three versions of the return behaviour: (1) a distance-independent probability of return to any previous refuge; (2) constant probability of return to the nearest refuge; or (3) a distance-dependent probability of return to each refuge. Using approximate Bayesian computation, we fit each version of the model to radiotracking data from a population of Fowler’s Toads, which inhabits a linear sand dune habitat on the north shore of Lake Erie in Ontario, Canada. Only the model with distance-independent, random returns provides a good fit of the inter-refuge distance distribution and the number of refuges visited per toad. Our results suggest that while toads occasionally forage over long distances, the establishment of new refuges is not driven by the minimization of energy expenditure.

While a growing proportion of global food consumption is obtained through international trade, there is an ongoing debate on whether this increased reliance on trade benefits or hinders food security, and specifically, the ability of global food systems to absorb shocks due to local or regional losses of production. This paper introduces a model that simulates the short-term response to a food supply shock originating in a single country, which is partly absorbed through decreases in domestic reserves and consumption, and partly transmitted through the adjustment of trade flows. By applying the model to publicly-available data for the cereals commodity group over a 17 year period, we find that differential outcomes of supply shocks simulated through this time period are driven not only by the intensification of trade, but as importantly by changes in the distribution of reserves. Our analysis also identifies countries where trade dependency may accentuate the risk of food shortages from foreign production shocks; such risk could be reduced by increasing domestic reserves or importing food from a diversity of suppliers that possess their own reserves. This simulation-based model provides a framework to study the short-term, nonlinear and out-of-equilibrium response of trade networks to supply shocks, and could be applied to specific scenarios of environmental or economic perturbations.