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 Conservation Priority Maps In addition to distribution maps for individual species, we have combined predicitions for species that have high conservation priority or ecological similarity. The methods used to generate each composite score are given below. These maps provide tools for identifying areas of high bird conservation priority. The maps differ from one another in the emphasis placed on different categories of birds. Like the individual species maps, these have been divided into 8525 cells of 4 km x 4 km. The color code for each cell depends on a "score" calculated according to one of the methods below. These scores are combinations of the probabilities of each species occurring in a cell, multiplied by a weighting factor. Different weighting factors give different scores and, consequently, different map patterns. This method tends to emphasize species that have restricted distributions within the study area, but does not take into account global distributions or independent assessments of conservation status. The calculation involves four steps: 1. Calculate a ratio that is equal to the [predicted probability of presence for species i in cell j] divided by the [median predicted probability of presence for species i across all map cells]. This ratio indicates the degree to which a cell is likely to contain a given species compared to the overall likelihood of species predicted presence in the entire map. The median is used as the denominator instead of the mean because the distributions of predicted probabilities were skewed for most species. From a conceptual standpoint, we can think that cells with ratios =1.0 to represent places that are not of great conservation priority for species. By omitting these ratio values from the subsequent computation of the score, cells having greater predicted probability than the median for a species represent a threshold of usefulness for the identification of priority areas. Species that are common tend to have median predicted probabilities that are high, and the ratio for these species tends to be low. Use of this ratio therefore tends to give more weight to rarer species in cells where these species are predicted to occur. 2. Compute the natural logarithm of the ratio. This is necessary because there is a large range in the values of the ratio. A few species exhibit very large values of the ratio for some cells because of low median predicted probabilities. Palm Warbler stands out as the species with the maximum ratio (38), while most species had maximum ratios below 10. If we didn't dampen the influence of this species, the resulting map of conservation scores would have looked a lot like the Palm Warbler map. The logarithm of the ratio was not computed for ratios =1.0. Instead, these values were manually set to zero. 3. Calculate the mean of the natural logarithm of the ratios across all species for each cell. For this step we include species with ratios =1.0 so that the mean log_ratio for each map cell is based upon the same number of species in the denominator. If logarithm had been calculated for ratios <1, the log_ratio would have been negative in several cases. It didn't seem that negative values (low ratios) should be able to subtract from the conservation value of a cell. 4. Compute the conservation priority score by back-transforming the mean of the log_ratios for cells. Back-transformation has the effect of putting the scores in the original scale of the ratio. For example, if the conservation priority score is 1.5 for a cell, then species will tend to be predicted at a probability 50% greater than their median predicted probability, on average. This is the score that has been mapped. We used 43 species (of 82 evaluated overall) to calculate the log ratio. These species yielded predictive models that discriminated presence or absence of individuals at the p < 0.10 level. Palm Warbler Eastern Towhee Golden-winged Warbler Connecticut Warbler Pine Warbler Wood Thrush Canada Warbler Swainson's Thrush Magnolia Warbler American Redstart White-breasted Nuthatch Yellow-bellied Flycatcher Black-throated Green Warbler Indigo Bunting Winter Wren Chipping Sparrow Yellow-throated Vireo Red-breasted Nuthatch Blue Jay Northern Parula Alder Flycatcher Golden-crowned Kinglet Rose-breasted Grosbeak Yellow-bellied Sapsucker Great-crested Flycatcher Myrtle Warbler American Crow American Robin Least Flycatcher Veery Chestnut-sided Warbler Nashville Warbler Ovenbird Brown Creeper Downy Woodpecker Eastern Wood-Pewee Hairy Woodpecker Hermit Thrush Dark-eyed Junco Scarlet Tanager Song Sparrow This score is the number of species that have a Partners in Flight (PIF) conservation priority score >18 in Bird Conservation Region 12 and a predicted probability of occurrence in the cell of at least 0.20 (20%). Grassland or open country species and species that had poor predictive models were excluded, leaving 16 species for this analysis: Golden-winged Warbler Connecticut Warbler Wood Thrush Canada Warbler Yellow-bellied Flycatcher Black-throated Green Warbler Indigo Bunting Winter Wren Chipping Sparrow Yellow-throated Vireo Rose-breasted Grosbeak Yellow-bellied Sapsucker Least Flycatcher Veery Chestnut-sided Warbler Nashville Warbler White-throated Sparrow Red-eyed Vireo Ovenbird Brown Creeper Downy Woodpecker Eastern Wood-Pewee Hairy Woodpecker Hermit Thrush Dark-eyed Junco Scarlet Tanager Song Sparrow This score uses the same 43 species as described above for the Log Ratio scores. The predicted probability for each species in each 4 km x 4 km cell is multiplied by the corresponding PIF conservation score. The mean of these weighted scores gives a composite score for the entire cell. Species with low PIF scores or low predicted probabilities will tend to have low influence on the PIF weighted score for any given cell.
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