Mesocarnivores fill a vital role in ecosystems through effects on community health and structure. Anthropogenic-altered landscapes can benefit some species and adversely affect others. For some carnivores, prey availability increases with urbanization, but landscape use can be complicated by interactions among carnivores as well as differing human tolerance of some species. We used camera traps to survey along a gradient of urban, rural, and forest cover to quantify how carnivore landscape use varies among guild members and determine if a species was a human exploiter, adapter, or avoider. Our study was conducted in and around Corvallis, Oregon from April 2018 to February 2019 (11,914 trap nights) using 47 camera trap locations on a gradient from urban to rural. Our focal species were bobcat (Lynx rufus), coyote (Canis latrans), gray fox (Urocyon cinereoargenteus), opossum (Didelphis virginiana), raccoon (Procyon lotor), and striped skunk (Mephitis mephitis). Raccoon and opossum were human exploiters with low use of forest cover and positive association with urban and rural developed areas likely due to human-derived resources as well as some refugia from larger predators. Coyote and gray fox were human adapters with high use of natural habitats while the effects of urbanization ranged from weak to indiscernible. Bobcat and striped skunk appeared to be human avoiders with negative relationship with urban cover and higher landscape use of forest cover. We conducted a diel temporal activity analysis and found mostly nocturnal activity within the guild, but more diurnal activity by larger bodied predators compared to the smaller species. Although these species coexist as a community in human-dominated landscapes throughout much of North America, the effects of urbanization were not equal across species. Our results, especially for gray fox and striped skunk, are counter to research in other regions, suggesting that mesopredator use of urbanized landscapes can vary depending on the environmental conditions of the study area and management actions are likely to be most effective when decisions are based on locally derived data.
Keys to Greater Sage-Grouse (Centrocercus uropha-sianus) management are maintenance of expansive stands of sagebrush (Artemisia species [spp.]), especially varieties of big sagebrush (Artemisia tridentata) with abundant forbs in the understory, particularly during spring; undisturbed and somewhat open sites for leks; and healthy perennial grass and forb stands intermixed with sagebrush for brood rearing. Within suitable habitats, areas should have 15–25 percent canopy cover of sagebrush 30–80 centimeters (cm) tall for nesting and 10–25 percent canopy cover 40–80 cm tall for brood rearing (Connelly and others, 2000b). In winter habitats, shrubs should be exposed 25–35 cm above snow and have 10–30 percent canopy cover exposed above snow. In nesting and brood-rearing habitats, the understory should have at least 15 percent cover of grasses and at least 10 percent cover of forbs greater than or equal to (>) 18 cm tall. Greater Sage-Grouse have been reported to use habitats with 5–110 cm aver-age vegetation height, 5–160 cm visual obstruction reading, 3–51 percent grass cover, 3–20 percent forb cover, 3–69 per-cent shrub cover, 7–63 percent sagebrush cover, 14–51 percent bare ground, and 0–18 percent litter cover. The descriptions of key vegetation characteristics are provided in table B1 (after the “References” section). Unless otherwise noted, this account refers to habitat requirements and environmental factors affecting Greater Sage-Grouse but not Gunnison Sage-Grouse (Centrocercus minimus). Habitats used by Gunnison Sage-Grouse are generally similar to habitats used by Greater Sage-Grouse, but some differences have been reported (Young and others, 2000; Aldridge and others, 2012). The Greater Sage-Grouse is a game bird and is hunted throughout most of its current range (Reese and Connelly, 2011). This account does not address harvest or its effects on populations; rather, this account focuses on the effects of habitat management. Vernacular and scientific names of plants and animals follow the Integrated Taxonomic Information System
Fire plays an important role in wildland ecosystems, critical to sustaining biodiversity, wildlife habitat and ecosystem health. By area, 70% of US prescribed burns take place in the Southeast, where treatment objectives range widely and accomplishing them depends on finding specific weather conditions for the effective and controlled application of fire. The climatological variation of the preferred weather window is examined here using two weather model reanalyses, with focus on conditions critical to smoke dispersion and erratic fire behaviour. Large spatial gradients were evident in some months (e.g. 3× change across the Appalachian Mountains in winter). Over most of the Southeast, availability of preferred conditions in summer was several (up to 8) times less than in autumn or winter. We offer explanation for this variability in terms of the mean seasonal changes of key weather conditions (especially mixing height and transport wind). We also examine the interannual variability of the preferred weather window for linkage to the tropical Pacific (1979–2010). Associations with the subset of El Niño events identified by outgoing-longwave-radiation suggest skilful seasonal fire weather forecasts are feasible. Together, these findings offer a predictive tool to prioritise allocation of scarce prescribed fire resources and maximise annual area treated across this landscape.
In order to increase the pace and scale of managing forests to reduce wildfire risk in the western U.S., federal agencies have adopted policies that promote an all lands management (ALM) approach, which extends management actions across jurisdictional boundaries. To better implement such policies, ALM approaches require new governance systems that overcome barriers found in existing systems, which typically address jurisdictions separately. Polycentric governance systems, characterized by multiple and diverse actors at different scales operating in coordination with one another under an overarching set of rules, have emerged to address wildfire risk in multi-ownership landscapes. We describe these polycentric systems using three case studies of US Forest Service-Natural Resources Conservation Service Joint Chiefs’ Landscape Restoration Partnership projects in Oregon and California. While all three cases demonstrate polycentric systems, we found diversity in terms of partnering organizations and levels of success in implementing wildfire risk reduction projects. Lessons from our research can inform more effective implementation of ALM policies for managing natural resources and processes in multi-jurisdictional landscapes. Our research suggests these systems can be strengthened when: bottom-up and top-down processes and incentives for establishing them converge; actors within the system coordinate effectively; policies enable flexibility and adaptiveness for how systems function in different places; multiple actors at multiple scales are able to supplement one another’s capacity; and legal and policy mechanisms facilitate efficient transfer of funding and resources between actors in the system to accomplish work.
Forests provide a suite of goods and services that are vital to human health and livelihoods. Studies of ecosystem services, which frequently attempt to place a monetary value on forest processes and organisms, can help inform management decisions by providing a baseline for discussing the costs and benefits of different management options.
A recent study by Pacific Northwest Research Station researchers, Adelaide “Di” Johnson and Ryan Bellmore, along with retired Forest Service fisheries biologist Ron Medel and Alaska Department of Fish and Game fisheries biologist Stormy Haught, aimed to quantify the number and monetary value of commercially caught Pacific salmon from Alaska’s Tongass and Chugach National Forests. These two national forests contain some of the world’s largest remaining tracts of intact temperate rain forest.
Between 2007 and 2016, the Tongass and Chugach supported harvests of approximately 48 million salmon per year, valued at more than $88 million annually. This comprised approximately 25 percent of all commercially caught salmon in Alaska and 16 percent of its total monetary value. Quantitative information about the value of Alaska’s national forests for fish production can contribute to discussions about management decisions that might influence the capacity of these forests to sustain Pacific salmon in the future.
Modeling landscape use (i.e., estimating the probability or relative probability of use, occurrence, or selection in a given area and time) by ungulates is an increasingly common and important practice in research and management. Models of occupancy, distribution, movement, habitat use, and resource selection are formal approaches by which landscape use has been characterized and results published for a myriad of ungulate species. Understanding landscape use has benefited from a growing volume of data on animal locations and model covariates, and the ease of modeling with automated software. These models are particularly noteworthy in their potential to estimate use at multiple scales, characterize individual and population distributions, and predict spatiotemporal responses to environmental change. Despite these advantages, ecological processes can be secondary or forgotten. Models without a strong ecological foundation may perform well in case studies but fail to advance our understanding of a species’ habitat requirements and response to habitat change across a broad inference space. In response, we describe criteria, synthesized from the ecological literature, of direct relevance to modeling landscape use for advancing the ecological understanding and effective management of ungulates. Criteria include (1) a knowledge coproduction framework for scientist-manager collaborations; (2) an explicit inference space with supporting replication for broad inference; (3) process covariates and their ecological scaling to address habitat requirements; (4) ecologically plausible sets of competing models; (5) model evaluation to address objectives and hypotheses of ecological importance; (6) assessment of relationships with animal and population performance; and (7) reliable interpretations for ecological understanding and management uses. Contemporary modeling of landscape use has been challenged by large, disparate data sources and an emphasis on statistical methods. However, advances in knowledge and conservation of ungulates based on tenets of ecology, management, and inference are achievable with careful consideration of these criteria.
In heterogeneous landscapes, large herbivores employ plastic behavioral strategies to buffer themselves against negative effects of environmental variation on fitness. Yet, the mechanisms by which individual responses to such variation scale up to influence population performance remain uncertain. Analyses of space-use behaviors exemplify this knowledge gap, because such behaviors are often assumed, but rarely demonstrated, to have direct fitness consequences. We combined fine-scale data on forage biomass and quality with movement data and measures of somatic energy reserves to determine whether variation in use (the quantity of resource units, e.g., pixels on a landscape, that receive some level of investment by an animal during a specific sampling period) or selection (use of a resource unit relative to its availability to the animal during the same sampling period) of the nutritional landscape predicted early winter body condition of mule deer (Odocoileus hemionus). At the population level, mule deer exhibited stronger selection for high forage biomass at the landscape scale than at the home-range scale, and during summer than during spring. Use of the nutritional landscape varied among individual deer and had important consequences for early winter condition (an important determinant of survival and reproduction in capital-breeding ungulates). Females that consistently used vegetation communities that provided high biomass of preferred forage plants throughout spring and summer entered winter in better condition than females that used those vegetation communities less frequently. In contrast, selection (i.e., use relative to availability) of the nutritional landscape by individual deer was not significantly related to early winter condition at either the landscape or home-range scales. Our results highlight the value of using mechanistic, nutritional approaches to understand the potential fitness consequences of individual variation in behavior. In addition, our study suggests that patterns of forage use by ungulates may sometimes correlate more strongly with fitness than patterns of forage selection, which are scale-dependent and more vulnerable to biases stemming from the need to accurately quantify availability.
Landscape patterns in the northwestern United States are mostly shaped by the interaction of fire and succession, and conversely, vegetation patterns influence fire dynamics and plant colonization processes. Historical landscape pattern dynamics can be used by resource managers to assess current landscape conditions and develop target spatial characteristics for management activities. The historical range and variability (HRV) of landscape pattern can be quantified from simulated chronosequences of landscape vegetation maps and can be used to (1) describe temporal variation in patch statistics, (2) develop limits of acceptable change, and (3) design landscape treatment guidelines for ecosystem management. Although this simulation approach has many advantages, the limitations of this method have not been explored in detail. To demonstrate the advantages and disadvantages of this approach, we performed several simulation experiments using the spatially explicit, multiple pathway model a LANDscape Succession Model (LANDSUM) to quantify the range and variability in six class and landscape pattern metrics for four landscapes in the northwestern United States. First, we applied the model to spatially nested landscapes to evaluate the effect of landscape size on the HRV pattern metrics. Next, we averaged the HRV pattern metrics across maps generated from simulation time spans of 100, 500, and 1000 years and intervals 5, 10, 25 and 50 years to assess optimal output generation parameters. We then altered the elevation data layer to evaluate effect of topography on pattern metrics, and cut various shapes (circle, rectangle, square) from a landscape to examine landscape shape and orientation influences. Then, we altered the input vegetation maps to assess the influence of initial conditions on landscape metrics output. Finally, a sensitivity analysis of input fire probabilities and transition times was performed. Results indicate landscapes should be quite large to realistically simulation fire pattern. Landscape shape, and orientation are critically important to quantifying patch metrics. Simulation output need only be stored every 20-50 years but landscapes should be simulated for long time periods (≥1000 years). All landscapes are unique so conclusions generated here may not be entirely applicable to all western US landscapes.