Looking beyond leaves: variation in nutrient leaching potential of seasonal litterfall among different species within an urban forest.

Urban litterfall that is deposited on impervious surface leaches nutrients into stormwater, contributing to downstream eutrophication. Previous studies have focused on the leaching potential of deciduous leaf litter, while other smaller-volume litterfall types-such as blossoms and fruit-may leach significant amounts of nitrogen, phosphorus, and carbon. These additional litterfall types represent an unaccounted-for source of nutrients to urban stormwater. We explored variation in leaching potential of dissolved nutrients and organic carbon across litter types and species by collecting litterfall (blossoms, fruit, leaves) from ten common urban tree species. After 24 h of leaching, we measured total phosphorus (TP), total dissolved nitrogen (TDN), and dissolved organic carbon (DOC) contributions and compared differences across litter types and species. Litter basket estimates then allowed us to quantify annual litterfall inputs. We found that blossoms leached 3-20 times more TDN and 1.5-7 times more TP than leaves of the same species. Furthermore, considering litterfall mass, several species had greater springtime nutrient-leaching potential compared to fall due to high leaching potential in blossoms and lower potential in leaves. We found mixed effects of leaf crushing and leachate solution (stormwater, salinity) on leaching rates. This study highlights the need to consider all litterfall types as well as variation in urban forest communities and conditions when seeking to budget, control, and maintain for potential nutrient sources from the urban forest. Supplementary information: The online version contains supplementary material available at 10.1007/s11252-022-01217-8.

Survey design for broad-scale, territory-based occupancy monitoring of a raptor: Ferruginous hawk (Buteo regalis) as a case study.

Given the uncertain population status of low-density, widely-occurring raptors, monitoring changes in abundance and distribution is critical to conserving populations. Nest-based monitoring is a common, useful approach, but the difficulty and expense of monitoring raptor nests and importance of reliable trend data to conservation requires that limited resources are allocated efficiently. Power analyses offer a helpful tool to ensure that monitoring programs have the ability to detect trends and to optimize financial resources devoted to monitoring. We evaluated alternative monitoring designs for raptors to identify appropriate survey effort to detect population trends. We used data collected from a territory-occupancy study of ferruginous hawks throughout Wyoming to guide simulations and evaluate the ability to detect trends in occupancy rates. Results suggest that greater gains in precision of trend estimation may be achieved through the addition of more sites and not more visits; statistical power was ≥80% when monitoring lasted 20 years and population declines were 20%; and probability of detection affected statistical power less than rates of population decline. Monitoring at least 150 sites for 20 years would provide reasonable estimates of trend in occupancy given certain rates of detection and occupancy, but only for population declines of 20%. Removal sampling did not result in substantial changes of any metrics used to evaluate simulations, providing little justification for employing the standard design if territory occupancy is the variable of interest. Initial rates of territory occupancy may be biased high, a problem inherent to many studies that monitor territory occupancy. We explored the effects of lower rates of initial occupancy on the ability to detect trends. Although we present data from a study of ferruginous hawks, our simulations can be applied to other raptor species with similar life history and population dynamics to provide guidance for future trend estimation of territory occupancy.

Mule deer and energy development-Long-term trends of habituation and abundance.

As the extent and intensity of energy development in North America increases, so do disturbances to wildlife and the habitats they rely upon. Impacts to mule deer are of particular concern because some of the largest gas fields in the USA overlap critical winter ranges. Short-term studies of 2-3 years have shown that mule deer and other ungulates avoid energy infrastructure; however, there remains a common perception that ungulates habituate to energy development, and thus, the potential for a demographic effect is low. We used telemetry data from 187 individual deer across a 17-year period, including 2 years predevelopment and 15 years during development, to determine whether mule deer habituated to natural gas development and if their response to disturbance varied with winter severity. Concurrently, we measured abundance of mule deer to indirectly link behavior with demography. Mule deer consistently avoided energy infrastructure through the 15-year period of development and used habitats that were an average of 913 m further from well pads compared with predevelopment patterns of habitat use. Even during the last 3 years of study, when most wells were in production and reclamation efforts underway, mule deer remained >1 km away from well pads. The magnitude of avoidance behavior, however, was mediated by winter severity, where aversion to well pads decreased as winter severity increased. Mule deer abundance declined by 36% during the development period, despite aggressive onsite mitigation efforts (e.g. directional drilling and liquid gathering systems) and a 45% reduction in deer harvest. Our results indicate behavioral effects of energy development on mule deer are long term and may affect population abundance by displacing animals and thereby functionally reducing the amount of available habitat.

Modeling Late-Summer Distribution of Golden Eagles (Aquila chrysaetos) in the Western United States.

Increasing development across the western United States (USA) elevates concerns about effects on wildlife resources; the golden eagle (Aquila chrysaetos) is of special concern in this regard. Knowledge of golden eagle abundance and distribution across the western USA must be improved to help identify and conserve areas of major importance to the species. We used distance sampling and visual mark-recapture procedures to estimate golden eagle abundance from aerial line-transect surveys conducted across four Bird Conservation Regions in the western USA between 15 August and 15 September in 2006-2010, 2012, and 2013. To assess golden eagle-habitat relationships at this scale, we modeled counts of golden eagles seen during surveys in 2006-2010, adjusted for probability of detection, and used land cover and other environmental factors as predictor variables within 20-km2 sampling units randomly selected from survey transects. We found evidence of positive relationships between intensity of use by golden eagles and elevation, solar radiation, and mean wind speed, and of negative relationships with the proportion of landscape classified as forest or as developed. The model accurately predicted habitat use observed during surveys conducted in 2012 and 2013. We used the model to construct a map predicting intensity of use by golden eagles during late summer across our ~2 million-km2 study area. The map can be used to help prioritize landscapes for conservation efforts, identify areas where mitigation efforts may be most effective, and identify regions for additional research and monitoring. In addition, our map can be used to develop region-specific (e.g., state-level) density estimates based on the latest information on golden eagle abundance from a late-summer survey and aid designation of geographic management units for the species.

Estimating resource selection with count data.

Resource selection functions (RSFs) are typically estimated by comparing covariates at a discrete set of "used" locations to those from an "available" set of locations. This RSF approach treats the response as binary and does not account for intensity of use among habitat units where locations were recorded. Advances in global positioning system (GPS) technology allow animal location data to be collected at fine spatiotemporal scales and have increased the size and correlation of data used in RSF analyses. We suggest that a more contemporary approach to analyzing such data is to model intensity of use, which can be estimated for one or more animals by relating the relative frequency of locations in a set of sampling units to the habitat characteristics of those units with count-based regression and, in particular, negative binomial (NB) regression. We demonstrate this NB RSF approach with location data collected from 10 GPS-collared Rocky Mountain elk (Cervus elaphus) in the Starkey Experimental Forest and Range enclosure. We discuss modeling assumptions and show how RSF estimation with NB regression can easily accommodate contemporary research needs, including: analysis of large GPS data sets, computational ease, accounting for among-animal variation, and interpretation of model covariates. We recommend the NB approach because of its conceptual and computational simplicity, and the fact that estimates of intensity of use are unbiased in the face of temporally correlated animal location data.

Identifying and prioritizing ungulate migration routes for landscape-level conservation.

As habitat loss and fragmentation increase across ungulate ranges, identifying and prioritizing migration routes for conservation has taken on new urgency. Here we present a general framework using the Brownian bridge movement model (BBMM) that: (1) provides a probabilistic estimate of the migration routes of a sampled population, (2) distinguishes between route segments that function as stopover sites vs. those used primarily as movement corridors, and (3) prioritizes routes for conservation based upon the proportion of the sampled population that uses them. We applied this approach to a migratory mule deer (Odocoileus hemionus) population in a pristine area of southwest Wyoming, USA, where 2000 gas wells and 1609 km of pipelines and roads have been proposed for development. Our analysis clearly delineated where migration routes occurred relative to proposed development and provided guidance for on-the-ground conservation efforts. Mule deer migration routes were characterized by a series of stopover sites where deer spent most of their time, connected by movement corridors through which deer moved quickly. Our findings suggest management strategies that differentiate between stopover sites and movement corridors may be warranted. Because some migration routes were used by more mule deer than others, proportional level of use may provide a reasonable metric by which routes can be prioritized for conservation. The methods we outline should be applicable to a wide range of species that inhabit regions where migration routes are threatened or poorly understood.

Estimating habitat selection when GPS fix success is less than 100%.

Inferences about habitat selection by animals derived from sequences of relocations obtained with global positioning system (GPS) collars can be influenced by GPS fix success. Environmental factors such as dense canopy cover or rugged terrain can reduce GPS fix success, making subsequent modeling problematic if fix success depends on the selected habitat. Ignoring failed fix attempts may affect estimates of model coefficients and lead to incorrect conclusions about habitat selection. Here, we present a habitat selection model that accounts for missing locations due to habitat-induced data losses, called a resource selection function (RSF) for GPS fix success. The model's formulation is similar to adjusting estimates of probability of occupancy when detection is less than 100% in patch occupancy sampling. We demonstrate use of the model with GPS data collected from an adult female mule deer (Odocoileus hemionus) and discuss how to analyze data from multiple animals. In the simulations presented, our habitat selection model was generally unbiased for GPS data sets missing up to 50% of the locations.

Potential for seed-mediated gene flow in agroecosystems from transgenic safflower (Carthamus tinctorius L.) intended for plant molecular farming.

Safflower has been transformed for field scale molecular farming of high-value proteins including several pharmaceuticals. Viable safflower seed remaining in the soil seed bank after harvest could facilitate seed and pollen-mediated gene flow. Seeds may germinate in subsequent years and volunteer plants may flower and potentially outcross with commodity safflower and/or produce seed. Seeds from volunteers could become admixed with conventional crops at harvest, and/or replenish the seed bank. Seed in following crops could be transported locally and internationally and facilitate gene flow in locations where regulatory thresholds and public acceptance differ from Canada. Seed-mediated gene flow was examined in three studies. Safflower seed loss and viability following harvest of commercial fields of a non-transgenic cultivar were determined. We assessed seed longevity of transgenic and non-transgenic safflower, on the soil surface and buried at two depths. Finally, we surveyed commercial safflower fields at different sites and measured density and growth stage of safflower volunteers, in other crops the following year and documented volunteer survival and viable seed production. Total seed loss at harvest in commercial fields, ranged from 231 to 1,069 seeds m(-2) and the number of viable seeds ranged from 81 to 518 seeds m(-2). Safflower has a relatively short longevity in the seed bank and no viable seeds were found after 2 years. Based on the seed burial studies it is predicted that winter conditions would reduce safflower seed viability on the soil surface by >50%, leaving between 40 and 260 viable seeds m(-2). The density of safflower volunteers emerging in the early spring of the following year ranged from 3 to 11 seedlings m(-2). Safflower volunteers did not survive in fields under chemical fallow, but in some cereal fields small numbers of volunteers did survive and generate viable seed. Results will be used to make recommendations for best management practices to reduce seed-mediated gene flow from commercial production of plant molecular farming with safflower.