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To identify functional connectivity patterns, we used a biophysical model to simulate larval dispersal, and then prioritized highly-connected patches using a reserve selection algorithm.
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We used a reserve-selection algorithm that minimized the total number of peatlands to include within networks.
Here we propose a reserve selection methodology which optimizes conservation given both a budget constraint and land market feedbacks by using a combination of econometric models along with stochastic dynamic programming.
Using an iterative reserve-selection procedure, we identify a core system of five botanical reserves within the Park.
We demonstrate the utility of the framework using several reserve selection methods including simple rules of thumb and more sophisticated tools such as Marxan and Zonation.
Consideration of uncertainty involves modifications to the typical objective functions used in reserve selection.
These classes were separated as individual layers in ArcGIS (version 9.3) and subsequently used in reserve selection software (ResNet; Sarkar et al. 2009) that aimed at representing each class at a set target to prioritize areas for conservation based on genetic and morphological variation.
We used reserve selection algorithms to determine whether collections of existing individual protected areas in Canada were efficient and/or effective in terms of representing the diversity of disturbance-sensitive mammals in Canada in comparison to (1) an optimal network of reserves, and (2) sites selected at random.
We then used reserve selection software to prioritize areas for conservation based on intraspecific variation or species-level diversity.
Accurate prediction of ovarian response is now possible by using an ovarian reserve test (ORT) [ 6].
We will use a selection in our reporting.
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