Conventional oil and natural gas infrastructure increases brown-headed cowbird (Molothrus ater) relative abundance and parasitism in mixed-grass prairie

Interspecific interactions disrupted by roads

Roads have pervasive impacts on wildlife, including habitat loss and fragmentation, road mortality, habitat pollution and increased human use of habitats surrounding them. However, the effects of roads on interspecific interactions are less understood. Here we provide a synthesis of the existing literature on how species interactions may be disrupted by roads, identify knowledge gaps, and suggest avenues for future research and conservation management. We conducted a systematic search using the Web of Science database for each species interaction (predation, competition, mutualism, parasitism, commensalism and amensalism). These searches yielded 2144 articles, of which 195 were relevant to our topic. Most of these studies focused on predation (50%) or competition (24%), and less frequently on mutualism (17%) or, parasitism (9%). We found no studies on commensalism or amensalism. Studies were biased towards mammals from high-income countries, with most conducted in the USA (34%) or Canada (18%). Our literature review identified several patterns. First, roads disrupt predator-prey relationships, usually with negative impacts on prey populations. Second, new disturbed habitats created in road corridors often benefit more competitive species, such as invasive species, although some native or endangered species can also thrive there. Third, roads degrade mutualistic interactions like seed dispersal and pollination. Fourth, roads can increase parasitism rates, although the intensity of the alteration is species specific. To reduce the negative impacts of roads on interspecific interactions, we suggest the following management actions: (i) verges should be as wide and heterogenous as possible, as this increases microhabitat diversity, thus enhancing ecosystem services like pollination and seed dispersal; (ii) combining different mowing regimes can increase the complexity of the habitat corridor, enabling it to act as a habitat for more species; (iii) the use of de-icing salts should be gradually reduced and replaced with less harmful products or maintenance practices; (iv) wildlife passes should be implemented in groups to reduce animal concentrations inside them; (v) periodic removal of carcasses from the road to reduce the use of this resource by wildlife; and (vi) implementation of traffic-calming schemes could enhance interspecific interactions like pollination and avoid disruption of predator-prey relationships.

Oil Infrastructure has Greater Impact than Noise on Stress and Habitat Selection in Three Grassland Songbirds

Oil extraction may impact wildlife by altering habitat suitability and affecting stress levels and behavior of individuals, but it can be challenging to disentangle the impacts of infrastructure itself on wildlife from associated noise and human activity at well sites. We evaluated whether the demographic distribution and corticosterone levels of three grassland passerine species (Chestnut-collared Longspur, Calcarius ornatus; Baird's Sparrow, Centronyx bairdii; and Savannah Sparrow Passerculus sandwichensis) were impacted by oil development in southern Alberta, Canada. We used a landscape-scale oil well noise-playback experiment to evaluate whether impacts of wells were caused by noise. Surprisingly, higher-quality female Chestnut-collared Longspurs tended to nest closer to oil wells, while higher-quality Savannah Sparrows generally avoided nesting sites impacted by oil wells. Corticosterone levels in all species varied with the presence of oil development (oil wells, noise, or roads), but the magnitude and direction of the response was species and stimulus specific. While we detected numerous impacts of physical infrastructure on stress physiology and spatial demographic patterns, few of these resulted from noise. However, all three species in this study responded to at least one disturbance associated with oil development, so to conserve the grassland songbird community, both the presence of physical infrastructure and anthropogenic noise should be mitigated.

Grassland songbird abundance is influenced more strongly by individual types of disturbances than cumulative disturbances associated with natural gas extraction

Grassland birds have undergone widespread global population declines due to loss and degradation of native grasslands. Activities associated with non-renewable energy derived from oil and natural gas extraction have substantially increased on grasslands. The cumulative disturbance generated by natural gas development creates a network of non-linear (e.g., bare ground and exotic plant species) and linear (e.g., roads, trails, pipelines) features that may degrade habitat quality for grassland species. We quantified grassland songbird abundance in two areas of southwestern Saskatchewan, Canada, to determine whether variation in abundance 1) depended on the type and amount of disturbance at two spatial extents, and 2) was more affected by the cumulative impacts of natural gas development than any single type of disturbance. We found that specific types of disturbances impacted the abundance of most species to varying degrees. The cover of different types of linear disturbance had the strongest effect on the most species. Natural gas disturbance within 450 m of point counts was more influential than disturbance within 200 m for nearly all species in both areas. Only Savannah sparrow (Passerculus sandwichensis) abundance was most strongly influenced by the cumulative amount of disturbance with abundance decreasing with increased disturbance. Overall, we detected few consistent patterns among species, or within species between our two study areas. Our results indicated that the impact of natural gas infrastructure can extend beyond the local influences associated with well sites and that relatively small amounts of disturbance (<2%) may impact grassland songbird abundance. We recommend that researchers use caution when studying well-density effects or combining individual types of disturbance without understanding the separate effects each type of disturbance has on the species or community of interest. Not doing so may lead to investing resources into management practices that do not have the greatest possible benefit for grassland songbirds.

Quantifying habitat loss and modification from recent expansion of energy infrastructure in an isolated, peripheral greater sage-grouse population

New technologies and increasing energy demand have contributed to rapid expansion of unconventional oil and gas development in the U.S. in the past two decades. Quantifying the effects of energy infrastructure on land cover and wildlife habitat is essential for informing land-use policy, developing wildlife conservation strategies, and projecting impacts of future development. The greater sage-grouse (Centrocercus urophasianus; GrSG) is a species of concern in sagebrush ecosystems of the western U.S. and Canada and the focus of widespread conservation and management efforts. Increasing energy development within GrSG range has prompted the need to quantify and predict impacts of energy infrastructure on their habitat and populations. We mapped the annual distribution, surface type, and activity level of energy and non-energy infrastructure in the Parachute-Piceance-Roan (PPR), a small, peripheral greater sage-grouse population in Colorado with expanding oil and gas development, from 2005 to 2015. During that time, the footprint of energy infrastructure more than doubled to 3,275 ha (+108.6%), including 195 new well pads, 930 ha of new pipelines, and 230 km of new roads. In contrast, non-energy infrastructure decreased to 532 ha (-8.3%). The majority of energy infrastructure present each year (77-84%) was supporting infrastructure (i.e. facilities, roads, pipelines) rather than well pads, with an average of 2.24 ± 0.52 SE ha of supporting infrastructure per ha of well pad. Pipelines comprised 74-80% of reclaimed surface and roads comprised 54-69% of disturbed surface across years. By 2015, anthropogenic infrastructure covered 2.70% of occupied range and 2.93% of GrSG habitat, and energy infrastructure covered 2.50% and 10.79% of two priority habitat management area zones in the PPR. Three land cover classes most affected by energy infrastructure were also those strongly selected by GrSG. Topographic constraints appear to concentrate energy infrastructure in areas with gentler topography that also have the highest GrSG use. Together, these patterns suggest that future energy development will cause substantial additional loss and modification of GrSG habitat in the PPR. Our findings are valuable for assessing surface disturbance caps for land-use management and projections of energy infrastructure effects on wildlife habitat in this and other expanding oil and gas fields.

Varying dataset resolution alters predictive accuracy of spatially explicit ensemble models for avian species distribution

Species distribution models can be made more accurate by use of new "Spatiotemporal Exploratory Models" (STEMs), a type of spatially explicit ensemble model (SEEM) developed at the continental scale that averages regional models pixel by pixel. Although SEEMs can generate more accurate predictions of species distributions, they are computationally expensive. We compared the accuracies of each model for 11 grassland bird species and examined whether they improve accuracy at a statewide scale for fine and coarse predictor resolutions. We used a combination of survey data and citizen science data for 11 grassland bird species in Oklahoma to test a spatially explicit ensemble model at a smaller scale for its effects on accuracy of current models. We found that only four species performed best with either a statewide model or SEEM; the most accurate model for the remaining seven species varied with data resolution and performance measure. Policy implications: Determination of nonheterogeneity may depend on the spatial resolution of the examined dataset. Managers should be cautious if any regional differences are expected when developing policy from range-wide results that show a single model or timeframe. We recommend use of standard species distribution models or other types of nonspatially explicit ensemble models for local species prediction models. Further study is necessary to understand at what point SEEMs become necessary with varying dataset resolutions.