The wildland-urban interface (WUI) is the area in which human settlements adjoin or intermix with ecosystems. Although research on the WUI has been focused on wildfire risk to settlements, we argue here that there is a need to quantify the extent of areas in which human settlements interact with adjoining ecosystems, regardless of their ability to support fire spread. Besides wildfires, human settlements affect neighboring ecosystems through biotic processes, including exotic species introduction, wildlife subsidization, disease transfer, landcover conversion, fragmentation, and habitat loss. The effects of WUI settlements on ecosystems are two tiered, starting with habitat modification and fragmentation and progressing to various diffusion processes in which direct and indirect effects of anthropogenic activities spread into neighboring ecosystems at varying scales. New scientific, management, and policy tools are needed in order to better understand the WUI as a unique social-ecological zone and to mitigate negative consequences of its continued growth.
File: BarMassada_etal_2014_BioScience.pdf
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Infrastructure is increasingly part of wildlife habitats. However, it is not clear how infrastructure affects habitat quality for wildlife adapted to natural disturbances. While potentially providing suitable habitat such as early-successional forest, infrastructure also enables human access, which may modify animal' movements, especially where hunted species are concerned. To investigated the effect of infrastructure for moose (Alces alces, n = 138), a heavily harvested species, we modelled circadian distances and movement rates over the year as a function of moose' distance to the nearest road, house and power line in different human-modified landscapes in Sweden (latitude 57-67). Distances between moose and roads followed a circadian pattern. Animals were more likely to be closer to roads between 18:00 in the evening and 6:00 in the morning (i.e., during times when traffic volumes are generally lower). Moose moved relatively faster when 125 m or closer to a road, or alternatively, were closer to roads when more active. We did not find these relationships between moose and houses or power lines. With respect to roads, our results suggest that moose may make a temporal adjustment. During hours when humans are less active, road-near habitats may be sought out. We suggest considering different resolutions to study the impact of different infrastructure types. We recommend future research to investigate animal movement and behaviour in relation to infrastructure to understand the utilization of human-modified habitats over time, and thus providing key information for wildlife management and conservation, particularly for species that are adapted to disturbed landscapes.
File: Neumann_etal_2013_LUP.pdf
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Biodiversity conservation requires prioritization to be effective. Biodiversity hotspots and conservation planning identify where to focus conservation efforts, but it is unclear when conservation is most successful. Our goals were to: (a) investigate if hot moments for conservation occur, (b) calculate how important and prevalent they are, and (c) discuss what may catalyze hot moments for conservation. We analyzed the worldwide network of protected areas since inception, analyzing both all countries, and those 35 countries that contained at least 1% of either the total count or the total area protected globally. The evidence for hot moments for conservation was very strong. Among all countries, 44% protected more than half of their protected area in 1 year, and 61% did so in one 5-year period. The 35 countries that contain most of the protected area globally (77%) protected 23% and 49%, respectively, within 1 or 5 years. Hot moments often coincided with societal upheaval such as the collapse of the USSR or the end of colonialism. Conservationists need to account for hot moments for conservation to be most effective
File: Radeloff_etal_2013_ConsLetters.pdf
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Most of our knowledge of reproduction of wild parrots in the Neotropics comes from studies of tropical lowland species, with few studies addressing species of high-altitude forests. We studied the reproductive biology of Tucuman Parrots (Amazona tucumana) in north-western Argentina between 2004 and 2009. We obtained data on reproductive output for 86 nests and on causes of mortality for 94 nests. Mean clutch-size per nesting attempt was 3.6 eggs 1.0 (s.d.). Hatching success (proportion of eggs laid that hatch) was 0.77 0.17. Fledging success (proportion of nestlings that fledge) was 0.83 0.13. The overall breeding success (mean number of fledglings per laying female per year) was 2.3 0.8. Overall finite nesting success (daily survival rate to the power of the nesting length) was 0.53 0.27, and chick finite nesting success rate was 0.74 0.22. We did not find differences in reproductive rate between Tucuman Parrots and other species of Amazona parrot from lowland habitats. Productivity and nesting success of Tucuman Parrots had high values in some years and low values in others. This was probably related to fruiting events of Podocarpus parlatorei - a critical food item. The main causes of nesting failure were predation (16%) and abandonment (12%). Our results suggest that for several species of Amazona in lowland habitats, predation and poaching may be the main limiting factors whereas climatic factors and food availability may contribute most to nesting failure at higher altitudes.
File: Rivera_etal_2013_Emu.pdf
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For decades, ecologists have measured habitat attributes in the field to understand and predict patterns of animal distribution and abundance. However, the scale of inference possible from field measured data is typically limited because large-scale data collection is rarely feasible. This is problematic given that conservation and management typical require data that are fine grained yet broad in extent. Recent advances in remote sensing methodology offer alternative tools for efficiently characterizing wildlife habitat across broad areas. We explored the use of remotely sensed image texture, which is a surrogate for vegetation structure, calculated from both an air photo and from a Landsat TM satellite image, compared with field-measured vegetation structure, characterized by foliage-height diversity and horizontal vegetation structure, to predict avian density and species richness within grassland, savanna, and woodland habitats at Fort McCoy Military Installation, Wisconsin, USA. Image texture calculated from the air photo best predicted density of a grassland associated species, grasshopper sparrow (Ammodramus savannarum), within grassland habitat (R2 = 0.52, p-value ,0.001), and avian species richness among habitats (R2 = 0.54, p-value ,0.001). Density of field sparrow (Spizella pusilla), a savanna associated species, was not particularly well captured by either field-measured or remotely sensed vegetation structure variables, but was best predicted by air photo image texture (R2 = 0.13, p-value = 0.002). Density of ovenbird (Seiurus aurocapillus), a woodland associated species, was best predicted by pixel-level satellite data (mean NDVI, R2 = 0.54, p-value ,0.001). Surprisingly and interestingly, remotely sensed vegetation structure measures (i.e., image texture) were often better predictors of avian density and species richness than field-measured vegetation structure, and thus show promise as a valuable tool for mapping habitat quality and characterizing biodiversity across broad areas.
File: Wood-2013-PLOS-One.pdf
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Model averaging is gaining popularity among ecologists for making inference and predictions. Methods for combining models include Bayesian model averaging (BMA) and Akaike's Information Criterion (AIC) model averaging. BMA can be implemented with different prior model weights, including the Kullback-Leibler prior asso- ciated with AIC model averaging, but it is unclear how the prior model weight affects model results in a predictive context. Here, we implemented BMA using the Bayesian Information Criterion (BIC) approximation to Bayes factors for building predictive models of bird abundance and occurrence in the Chihuahuan Desert of New Mexico. We examined how model predictive ability differed across four prior model weights, and how averaged coef?cient esti- mates, standard errors and coef?cients' posterior probabil- ities varied for 16 bird species. We also compared the predictive ability of BMA models to a best single-model approach. Overall, Occam's prior of parsimony provided the best predictive models. In general, the Kullback-Leibler prior, however, favored complex models of lower predictive ability. BMA performed better than a best single-model approach independently of the prior model weight for 6 out of 16 species. For 6 other species, the choice of the prior model weight affected whether BMA was better than the best single-model approach. Our results demonstrate that parsimonious priors may be favorable over priors that favor complexity for making predictions. The approach we present has direct applications in ecology for better pre- dicting patterns of species' abundance and occurrence.
File: St-Louis_etAl_Oecologia_Bayesian_Priors.pdf
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Since European settlement, hardwood dominated forests of the Upper American Midwest have under- gone compositional changes due to ?re suppression and changes in land use. It is not clear how these changes affect songbirds during spring migration. In 2009 and 2010, we quanti?ed foraging behavior by migratory songbirds during spring migration and collected data on tree and sapling diversity in the Kickapoo Valley Reserve in southwestern Wisconsin. Furthermore, we compared the 1840s distribution of tree species (from Public Land Survey System witness tree records) with current (2010) and estimated future (sapling) tree-composition to better understand how historic and future changes in tree composi- tion may impact migratory songbirds at spring migration stopover sites. Six tree species were selected as foraging substrates in higher proportion than they were available by eight migratory songbirds, including trees adapted to moderate shade such as northern red oak (Quercus rubra), white oak (Quercus alba), American elm (Ulmus americana), and slippery elm (Ulmus rubra), and shade-intolerant species such as big-tooth aspen (Populus grandidentata), and paper birch (Betula papyrifera). Whereas three shade-toler- ant tree species were selected in far lower proportion than they were available by eight migratory song- birds, including sugar maple (Acer saccharum), red maple (Acer rubrum), and basswood (Tilia americana). We found evidence that food accessibility, as measured by a novel approach relating a bird's attacks and search efforts to the average leaf petiole length of a tree species, was strongly inversely related with a bird's foraging success (q = =0.96, p-value <0.001). Although tree-species composition changed considerably from the 1840s to 2010, in both time periods the forest was dominated by a mix of sugar maple and oak species. However, sugar maple saplings currently form a nearly continuous layer in the understory and there is very low recruitment of shade-intolerant or moderately shade-tolerant species, suggesting a future shift towards dominance by shade-tolerant species. Our results suggest the current trajectory of forest succession may result in future conditions that provide lower quality foraging for migratory songbirds during spring migration than they currently experience in the Upper American Midwest.
File: Woodetal2012.pdf
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Aim Understanding what constituted species' ranges prior to large-scale human in?uence, and how past climate and land use change have affected range dynamics, provides conservation planners with important insights into how species may respond to future environmental change. Our aim here was to reconstruct the Holocene range of European bison (Bison bonasus) by combining a time-calibrated species distribution models (SDM) with a dynamic vegetation model. Location Europe. Method We used European bison occurrences from the Holocene in a maximum entropy model to assess bison range dynamics during the last 8000 years. As predictors, we used bioclimatic variables and vegetation reconstructions from the generalized dynamic vegetation model LPJ-GUESS. We compared our range maps with maps of farmland and human population expansion to identify the main species range constraints. Results The Holocene distribution of European bison was mainly determined by vegetation patterns, with bison thriving in both broadleaved and coniferous forests, as well as by mean winter temperature. The heartland of European bison was in Central and Eastern Europe, whereas suitable habitat in Western Europe was scarce. While environmentally suitable regions were overall stable, the expansion of settlements and farming severely diminished available habitat. Main conclusions European bison habitat preferences may be wider than previously assumed, and our results suggest that the species had a more eastern and northern distribution than previously reported. Vegetation and climate transformation during the Holocene did not affect the bison's range substantially. Conversely, human population growth and the spread of farming resulted in drastic bison habitat loss and fragmentation, likely reaching a tipping point during the last 1000 years. Combining SDM and dynamic vegetation models can improve range reconstructions and projections, and thus help to identify resilient conservation strategies for endangered species.
File: Kuemmerle_etal_2012_DD.pdf
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Human-wildlife con?icts like wildlife-vehicle collisions pose major challenges for the management and conservation of mobile wildlife in human-dominated landscapes, particularly when large species are involved. Mitigation measures to reduce risk of collisions may be based on information given by wildlife movement and collision data. To test whether movement and collision data indicate different spatiotem- poral risk zones, we predicted year-around probabilities of road-crossings of GPS-marked female moose (Alces alces) (n = 102), and compared them with spatiotemporal patterns of police recorded moose-vehi- cle collisions (n = 1158). Probability of moose road-crossings peaked in May, June, and between mid November and the beginning of January, i.e. during moose migration. Moose-vehicle collisions were more likely during autumn and winter. Comparing environmental attributes of crossing and collision sites showed signi?cant differences. The likelihood of collisions increased with the abundance of human-mod- i?ed areas and higher allowed speed, and was lower on forest roads. We found that animal movement data alone are insuf?cient to predict collision risk zones, while analyses of collision data alone overesti- mate the collision risk in certain habitats. Our ?ndings suggest that higher collision risk is largely due to low light and poor road surface conditions rather than to more animal road-crossings. This suggests that efforts to reduce wildlife collisions should focus on driver attitudes and road conditions rather than ani- mal movement, and any efforts to model the collision risk will require actual collision data, and not just movement data.
File: Neumann_etAl_BioCons_moose-roads.pdf
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Habitat connectivity is important for the survival of species that occupy habitat patches too small to sus- tain an isolated population. A prominent example of such a species is the European bison (Bison bonasus), occurring only in small, isolated herds, and whose survival will depend on establishing larger, well-con- nected populations. Our goal here was to assess habitat connectivity of European bison in the Carpathi- ans. We used an existing bison habitat suitability map and data on dispersal barriers to derive cost surfaces, representing the ability of bison to move across the landscape, and to delineate potential con- nections (as least-cost paths) between currently occupied and potential habitat patches. Graph theory tools were then employed to evaluate the connectivity of all potential habitat patches and their relative importance in the network. Our analysis showed that existing bison herds in Ukraine are isolated. How- ever, we identi?ed several groups of well-connected habitat patches in the Carpathians which could host a large population of European bison. Our analysis also located important dispersal corridors connecting existing herds, and several promising locations for future reintroductions (especially in the Eastern Car- pathians) that should have a high priority for conservation efforts. In general, our approach indicates the most important elements within a landscape mosaic for providing and maintaining the overall connec- tivity of different habitat networks and thus offers a robust and powerful tool for conservation planning.
File: Potential_habitat_connectivity.pdf
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