Effects of cover soil stockpiling on plant community development following reclamation of oil sands sites in Alberta

Stockpiling of cover soil can influence vegetation development following reclamation. Cover soil, comprising the upper 15–30 cm of the surface material on sites scheduled for mining, is commonly salvaged prior to mining and used directly or stockpiled for various lengths of time until it is needed. Salvaging and stockpiling causes physical, chemical, and biological changes in cover soils. In particular, stockpiling reduces the availability and vigor of vegetative propagules and seed, and can lead to increases in the abundance of some weedy species. This study uses data from monitoring plots to assess how stockpiling of cover soil impacts plant community development on reclaimed oil sands mine sites in northern Alberta. Development of plant communities differed distinctly between directly placed and stockpiled cover soil treatments even 18 years after reclamation. Direct placement of cover soil resulted in higher percent cover, species richness, and diversity. Nonmetric multidimensional scaling and multiresponse permutation procedure revealed compositional differentiation between the treatments. Indicator species analysis showed that direct placement treatment was dominated by perennial species while grasses and annual forb species dominated sites where stockpiled soil was used. Results indicate that stockpiling leads to slower vegetation recovery while direct placement of cover soil supports more rapid succession (from ruderal and annual communities to perennial communities). In addition, direct placement may be less costly than stockpiling. However, scheduling of salvage and placement remains a challenge.     

Oribatid mites reveal that competition for resources and trophic structure combine to regulate the assembly of diverse soil animal communities

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Null model analyses of temporal patterns of bird assemblages and their foraging guilds revealed the predominance of positive and random associations

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Pitfalls to avoid in nonlinear perturbation analysis of structured population models

Despite the ubiquity of nonlinear functional relationships in nature we tend to characterize mechanisms in science using more tractable linear functions. In demographic modeling, transfer function analysis is used to calculate the nonlinear response of population growth rate to a theoretical perturbation of one or more matrix elements. This elegant approach is not yet popular in ecology. Inconveniently, using transfer function without care can produce erroneous results without warning. We used a large matrix projection model database to explore the potential pitfalls to be avoided in using transfer function analysis. We asked a fundamental population control question, what matrix element perturbation would be needed to reach a minimum goal of replacement population growth? We then tracked instances in which transfer function yields erroneous output and explored these cases in detail to measure how frequently it occurs. We developed a phylogenetically-corrected mixed effects logistic regression model in a Bayesian framework to test the effect of species traits and the identity of matrix elements on the probability that transfer function yields errors. We found in 16% of cases the transfer function yielded erroneous outcomes. These errors were more likely when perturbing demographic stasis and also for shrubs more than any other life form. Errors in transfer function analysis were often due to perturbing matrix elements beyond their biological limits, even when this is still mathematically correct. To use transfer function analysis properly in demographic modeling and avoid erroneous results, input must be carefully selected to include only a biologically admissible set of perturbations.     

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