We are excited to announce a new publication in the journal Ecosystems titled Snowpack, Tree Size, and Ecological Legacies Promote Seedling Establishment in Tree Islands at the Treeline. Congratulations to Ecofisher Owen Fitzpatrick and co-authors M. Blade, L. A. Fishback, G. P. Kershaw, J. Muffly & S. D. Mamet on their latest publication!
Click here to access the article.
Abstract
At a global scale, mean air or soil temperatures appear to be drivers of treeline position. However, at finer scales, seed availability and microsite conditions may limit the germination, establishment, and growth of tree seedlings—and therefore the position of treeline. Tree islands are features of many treelines, and they can alter microsite conditions by producing seed, providing shelter, and redistributing snow. Near Churchill, Manitoba, Canada, tree islands have higher seedling establishment than nearby forest and treeline sites and could be hot spots for treeline expansion. However, seedling establishment and tree recruitment events may be stochastic, making predictions based on the relationship between seedling counts and microsite conditions difficult. We asked whether current tree island seedling establishment can be predicted by (1) historical recruitment and/or (2) tree and snowpack characteristics. To answer these questions, we measured tree island tree characteristics and monitored seedling establishment and snowpack in five tree islands at latitudinal treeline near Churchill, Manitoba. We fit hierarchical, generalized linear mixed effect models to assess the influence of our hypothesized predictors. We found that tree recruitment in the past was strongly positively associated with current seedling density. Mean basal area and age of trees were also positively associated with seedling density, whereas tree density was negatively associated with seedling density. We found weak positive effects of snowpack snow water equivalent. Our results provide evidence for positive feedbacks within tree islands and suggest useful factors to include in models for predicting future treeline change.