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1.  Using a Data-Constrained Model of Home Range Establishment to Predict Abundance in Spatially Heterogeneous Habitats 
PLoS ONE  2012;7(7):e40599.
Mechanistic modelling approaches that explicitly translate from individual-scale resource selection to the distribution and abundance of a larger population may be better suited to predicting responses to spatially heterogeneous habitat alteration than commonly-used regression models. We developed an individual-based model of home range establishment that, given a mapped distribution of local habitat values, estimates species abundance by simulating the number and position of viable home ranges that can be maintained across a spatially heterogeneous area. We estimated parameters for this model from data on red-backed vole (Myodes gapperi) abundances in 31 boreal forest sites in Ontario, Canada. The home range model had considerably more support from these data than both non-spatial regression models based on the same original habitat variables and a mean-abundance null model. It had nearly equivalent support to a non-spatial regression model that, like the home range model, scaled an aggregate measure of habitat value from local associations with habitat resources. The home range and habitat-value regression models gave similar predictions for vole abundance under simulations of light- and moderate-intensity partial forest harvesting, but the home range model predicted lower abundances than the regression model under high-intensity disturbance. Empirical regression-based approaches for predicting species abundance may overlook processes that affect habitat use by individuals, and often extrapolate poorly to novel habitat conditions. Mechanistic home range models that can be parameterized against abundance data from different habitats permit appropriate scaling from individual- to population-level habitat relationships, and can potentially provide better insights into responses to disturbance.
PMCID: PMC3398050  PMID: 22815772
2.  How Stand Productivity Results from Size- and Competition-Dependent Growth and Mortality 
PLoS ONE  2011;6(12):e28660.
A better understanding of the relationship between stand structure and productivity is required for the development of: a) scalable models that can accurately predict growth and yield dynamics for the world's forests; and b) stand management regimes that maximize wood and/or timber yield, while maintaining structural and species diversity.
We develop a cohort-based canopy competition model (“CAIN”), parameterized with inventory data from Ontario, Canada, to examine the relationship between stand structure and productivity. Tree growth, mortality and recruitment are quantified as functions of diameter and asymmetric competition, using a competition index (CAIh) defined as the total projected area of tree crowns at a given tree's mid-crown height. Stand growth, mortality, and yield are simulated for inventoried stands, and also for hypothetical stands differing in total volume and tree size distribution.
For a given diameter, tree growth decreases as CAIh increases, whereas the probability of mortality increases. For a given CAIh, diameter growth exhibits a humped pattern with respect to diameter, whereas mortality exhibits a U-shaped pattern reflecting senescence of large trees. For a fixed size distribution, stand growth increases asymptotically with total density, whereas mortality increases monotonically. Thus, net productivity peaks at an intermediate volume of 100–150 m3/ha, and approaches zero at 250 m3/ha. However, for a fixed stand volume, mortality due to senescence decreases if the proportion of large trees decreases as overall density increases. This size-related reduction in mortality offsets the density-related increase in mortality, resulting in a 40% increase in yield.
Size-related variation in growth and mortality exerts a profound influence on the relationship between stand structure and productivity. Dense stands dominated by small trees yield more wood than stands dominated by fewer large trees, because the relative growth rate of small trees is higher, and because they are less likely to die.
PMCID: PMC3236764  PMID: 22174861
3.  Spatial ecology of mating success in a sexually polymorphic plant 
The spatial context of reproduction is of crucial importance to plants because of their sessile habit. Since pollen and seed dispersal is often restricted, mating success is likely to depend on the quantity and quality of mates in local neighbourhoods. Here we use neighbourhood models to investigate the spatial ecology of pollination and mating in Narcissus assoanus, a sexually polymorphic plant with two mating morphs that differ in style length. By mapping individuals in eight populations from southwestern France, we investigated the influence of the density and morph identity of plants at different spatial scales on variation in female fertility. By using inferences on the expected patterns of pollen transfer based on floral morphology, we were able to predict the quantitative relations between local morph ratios and variation in fertility. Our analyses revealed differences in the spatial clustering of morphs and in their response to plant density and morph identity within local neighbourhoods. Mating success in N. assoanus was characterized by both density- and frequency-dependent processes, a condition that may be a general feature of the spatial ecology of plant mating.
PMCID: PMC1560212  PMID: 16615203
mating success; neighbourhood model; style-morph ratios; sexual polymorphism; spatial pattern

Results 1-3 (3)