John M. Morton

Climate change, uncertainty, and natural resource management†

ABSTRACT Climate change and its associated uncertainties are of concern to natural resource managers. Although aspects of climate change may be novel (e.g., system change and nonstationarity), natural resource managers have long dealt with uncertainties and have developed corresponding approaches to decision-making. Adaptive resource management is an application of structured decision-making for recurrent decision problems with uncertainty, focusing on management objectives, and the reduction of uncertainty over time. We identified 4 types of uncertainty that characterize problems in natural resource management. We examined ways in which climate change is expected to exacerbate these uncertainties, as well as potential approaches to dealing with them. As a case study, we examined North American waterfowl harvest management and considered problems anticipated to result from climate change and potential solutions. Despite challenges expected to accompany the use of adaptive resource management to address problems associated with climate change, we conclude that adaptive resource management approaches will be the methods of choice for managers trying to deal with the uncertainties of climate change.

Time and energy budgets of American black ducks in winter

We used scan sampling techniques to quantify behavior and energy expenditure of American black ducks (Anas rubripes) at Chincoteague National Wildlife Refuge (NWR), Virginia, during the winters of 1985-86 and 1986-87. Time, tide, and habitat influenced black duck behaviors; therefore, diurnal time budgets were constructed by distributing scans over a time-tide matrix within refuge pool, saltmarsh, and tidal-water habitats. Black ducks observed during the day fed least and rested most when in refuge pools, and fed most and rested least when in tidal waters. Estimated daily energy expenditure (DEE) of American black ducks wintering at Chincoteague NWR was similar to values reported in Maine at a given temperature. Although DEE of undisturbed and disturbed flocks were similar, black ducks curtailed feeding and increased time spent in alert and locomotion behaviors in response to disturbance. We suggest that human disturbance of wintering black ducks impairs their physiological condition, thereby reducing winter survival and/or nutrient reserves carried to the breeding grounds. J. WILDL. MANAGE. 53(2):401-410 The decline in populations of American black ducks over the past 3 decades (Steiner 1984) has prompted behavioral research of wintering black ducks. Albright et al. (1983) investigated behavioral responses of wintering black ducks in Maine to temperature, wind chill, and availability of ice-free foraging habitat. Black ducks rested more and fed less with decreasing temperature and increasing ice, even as total DEE increased due to the demands of thermoregulation. Albright et al. (1983) suggested that black ducks in northern wintering areas experience extreme food shortages and that there was evidence of a physiological set-point below which it is more advantageous to rely on energy reserves than to expend energy searching for food. Hickey and Titman (1983) employed scan sampling to study black ducks wintering on Prince Edward Island; ducks fed less and rested more with increased wind chill and tide level. More information is needed to determine the amount of time black ducks spend in various habitats and to measure nocturnal activity (Hickey and Titman 1983). Brodsky and Weatherhead (1985a,b) demonstrated that local food availability can determine black duck behavioral responses to low temperatures in Canada. Brodsky and Weatherhead (1984) also studied the posturing of black ducks while resting and roosting as a mechanism for reducing thermoregulatory costs. They suggested that the management of energy expenditure is as much a consideration as management of energy intake by black ducks. We used the time-budget approach to quantify behavior and energy expenditure of black ducks wintering on, and in the vicinity of, Chincoteague NWR, Virginia. Objectives were to estimate time and energy expenditure within different habitats, identify environmental factors that influence behavioral response, and contrast black duck allocation of time and energy resources in tidal Virginia with results of studies conducted at higher latitudes. We thank M. R. Vaughan and D. R. Stauffer for suggestions and criticisms during the study and D. W. Howerter for field assistance. This study was supported by the U.S. Fish and Wildlife Service and the Department of Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University.

Habitat use and movements of American black ducks in winter

We determined habitat use and movement patterns of 22 female American black ducks (Anas rubripes) wintering at Chincoteague National Wildlife Refuge (NWR), Virginia, with radio telemetry and aerial survey techniques during 15 December 1985-28 February 1986. Proportional use of saltmarsh, impoundment, and natural pool habitats was greater (P 1. Habitat use was affected by the day-night cycle and a tide-ice interaction. J. WILDL. MANAGE. 53(2):390-400 American black duck populations wintering along the Atlantic Flyway have declined almost 50% since 1954 (Steiner 1984). Excessive harvest (Geis et al. 1971, Blandin 1982, Grandy 1983), acid rain (Hansen 1987), and hybridization with mallards (Anas platyrhynchos) (Heusmann 1974, Ankney et al. 1987) have been suggested as factors responsible for this decline. Others believe that loss and degradation of wintering habitat may be affecting black duck populations, although the evidence is somewhat con-

Toward accounting for ecoclimate teleconnections: intra- and inter-continental consequences of altered energy balance after vegetation change

ContextVegetation is projected to continue to undergo major structural changes in coming decades due to land conversion and climate change, including widespread forest die-offs. These vegetation changes are important not only for their local or regional climatic effects, but also because they can affect climate and subsequently vegetation in other regions or continents through “ecoclimate teleconnections”.ObjectivesWe propose that ecoclimate teleconnections are a fundamental link among regions within and across continents, and are central to advancing large-scale macrosystems ecology.Methods and resultsWe illustrate potential ecoclimate teleconnections in a bounding simulation that assumes complete tree cover loss in western North America due to tree die-off, and which predicts subsequent drying and reduced net primary productivity in other areas of North America, the Amazon and elsewhere. Central to accurately modeling such ecoclimate teleconnections is characterizing how vegetation change alters albedo and other components of the land-surface energy balance and then scales up to impact the climate system. We introduce a framework for rapid field-based characterization of vegetation structure and energy balance to help address this challenge.ConclusionsEcoclimate teleconnections are likely a fundamental aspect of macrosystems ecology needed to account for alterations to large-scale atmospheric-ecological couplings in response to vegetation change, including deforestation, afforestation and die-off.

Using Random Forests to Provide Predicted Species Distribution Maps as a Metric for Ecological Inventory & Monitoring Programs

Sustainable management efforts are currently hindered by a lack of basic information about the spatial distribution of species on large landscapes. Based on complex ecological databases, computationally advanced species distribution models can provide great progress for solving this ecological problem. However, current lack of knowledge about the ecological relationships that drive species distributions reduces the capacity for classical statistical approaches to produce accurate predictive maps. Advancements in machine learning, like classification and bagging algorithms, provide a powerful tool for quickly building accurate predictive models of species distributions even when little ecological knowledge is readily available. Such approaches are also well known for their robustness when dealing with large data sets that have low quality. Here, we used Random Forests (Salford System’s Ltd. and R language), a highly accurate bagging classification algorithm originally developed by L. Breiman and A. Cutler, to build multi-species avian distribution models using data collected as part of the Kenai National Wildlife Refuge Long-term Ecological Monitoring Program (LTEMP). Distribution maps are a useful monitoring metric because they can be used to document range expansions or contractions and can also be linked to population estimates. We utilized variable radius point count data collected in 2004 and 2006 at 255 points arranged in a 4.8 km resolution, systematic grid spanning the 7722 km2 spatial extent of Alaska’s Kenai National Wildlife Refuge. We built distribution models for 40 bird species that are present within 200m of 2–56% of the sampling points resulting in models that represent species which are both rare and common on the landscape. All models were built using a common set of 157 environmental predictor variables representing topographical features, climatic space, vegetation, anthropogenic variables, spatial structure, and 5 randomly generated neutral landscape variables for quality assessment. Models with that many predictors have not been used before in avian modeling, but are commonly used in similar types of applications in commercial disciplines. Random Forests produced strong models (ROC >0.8) for 16 bird species, marginal models (0.7 >ROC <0.8) for 13 species, and weak models (ROC <0.7) for 11 species. The ability of Random Forests to provide accurate predictive models was independent of how common or rare a bird was on the landscape. Random Forests did not rank any of the 5 neutral landscape variables as important for any of the 41 bird species. We argue that for inventory and monitoring programs the interpretive focus and confidence in reliability should be placed in the predictive ability of the map, and not in the assumed ecological meaning of the predictors or their linear relationships to the response variable. Given this focus, computer learning algorithms would provide a very powerful, cost-saving approach for building reliable predictions of species occurrence on the landscape given the current lack of knowledge on the ecological drivers for many species. Land management agencies need reliable predictions of current species distributions in order to detect and understand how climate change and other landscape drivers will affect future biodiversity.

A climate-change adaptation framework to reduce continental-scale vulnerability across conservation reserves

Rapid climate change, in conjunction with other anthropogenic drivers, has the potential to cause mass species extinction. To minimize this risk, conservation reserves need to be coordinated at multiple spatial scales because the climate envelopes of many species may shift rapidly across large geographic areas. In addition, novel species assemblages and ecological reorganization make future conditions uncertain. We used a GIS analysis to assess the vulnerability of 501 reserve units in the National Wildlife Refuge System as a basis for a nationally coordinated response to climate change adaptation. We used measures of climate change exposure (historic rate of temperature change), sensitivity (biome edge and critical habitat for threatened and endangered species), and adaptive capacity (elevation range, latitude range, watershed road density, and watershed protection) to evaluate refuge vulnerability. The vulnerability of individual refuges varied spatially within and among biomes. We suggest that the spat...

Estimating wolverine Gulo gulo population size using quadrat sampling of tracks in snow

Abstract Low densities and wide-ranging behaviour make wolverines Gulo gulo difficult to monitor. We used quadrat sampling of tracks in snow to estimate wolverine populations. We conducted aerial surveys in upper Turnagain Arm and the Kenai Mountains (TAKM) in south-central Alaska and in Old Crow Flats (OCF) in northern Yukon during March 2004 following procedures for the sample-unit probability estimator (SUPE). This technique uses network sampling of tracks in snow in a stratified random system of quadrats or sample units. In TAKM, we sampled 87 (51%) out of 171 quadrats within a survey area of 4,340 km2. The estimated density was 3.0 (± 0.4 SE) wolverines/1,000 km2 with a coefficient of variation (CV) of 12.0%. In OCF, we sampled 96 (71%) out of 135 quadrats within a survey area of 3,375 km2. The estimated density was 9.7 (± 0.6 SE) wolverines/1,000 km2 with a CV of 6.5%. Our results indicated that the SUPE technique is an efficient method of obtaining precise estimates of wolverine population size under markedly different environmental conditions and population densities. We suggest that, where practical, it may be a less labour-intensive and more cost-effective technique for estimating wolverine abundance compared with techniques that do not use probability sampling of tracks.

Population trends of Mariana Crow Corvus kubaryi on Rota, Commonwealth of the Northern Mariana Islands

Endemic to the islands of Guam and Rota in the Mariana Islands, Mariana Crow Corvus kubaryi is the only corvid in Micronesia. Currently, it survives on Guam only because of translocation of individuals from Rota (1999–2003). Island-wide surveys in 1982 and 1995 on Rota yielded population estimates of 1,348 and 592 respectively, indicating a 56% decrease in only 13 years. A sharp decline in the only viable Mariana Crow population has serious implications for conservation efforts on Rota and for efforts to re-establish the Guam population. However, the validity of the apparent decline has been debated among scientists and government management agencies. We augmented the 1982 and 1995 island-wide VCP surveys with (1) an additional island-wide survey conducted in 1998, and (2) roadside surveys conducted during 1991–1993 and again during 1999–2002. We also outline historical changes in Rota’s limestone forest based on aerial photographs and historical information. Data from all surveys indicate a significant decline in the Mariana Crow population. Declines occurred especially along the north-central coast and in the area east of the airport known as As Dudo in the 1990s, but the data indicate an island-wide decline over the entire span of the surveys. Introduced predators, human persecution, and habitat loss and degradation by anthropogenic and natural causes have all contributed to the decline. Long-term preservation of this species will require effective brown treesnake Boiga irregularis control, habitat protection, continued monitoring and research, and increased public education and awareness of Rota’s rare and endangered species.

Population status and nest success of the Critically Endangered Mariana Crow Corvus kubaryi on Rota, Northern Mariana Islands

The Mariana Crow Corvus kubaryi is a Critically Endangered species found only on the island of Rota, Northern Mariana Islands. It was extirpated from the neighbouring island of Guam by the introduced brown tree snake Boiga irregularis and the Rota population has been in decline since at least 1995. We identified only 60 pairs present on Rota in 2007 compared with an estimated 117 pairs in 1998, a decline of nearly 50% in nine years. The decline may be linked to proximity to human activities, though more data are needed. We monitored 204 crow nests between the 1996 and 2009 breeding seasons. Crows initiate clutches between August and April. The overall estimate of nest success was 25.7% ( n = 204). On average 49% of pairs produced at least one fledgling per season. The mean number of fledglings per pair per year is 0.66. Mean clutch size was 2.6 ( n = 82), mean number of nestlings was 1.4 ( n = 106), and mean number of fledglings per nest was 1.3 ( n = 68). Daily survival rates declined in later years, and increased during the nest cycle. The number of pairs with successful nests did not change during the study period, nor did the number of fledglings per pair. Predation appeared to be the primary cause of nest failure. The breeding season lasted around nine months and pairs re-nested after failure. Predation of adults and juveniles by cats, combined with possible inbreeding depression, habitat disturbance and human persecution appear to be the cause of decline of the Mariana Crow. We strongly recommend a programme of invasive predator control, habitat maintenance, and captive rearing to ensure the species’ survival.

NEST SITE SELECTION AND CONSEQUENCES FOR REPRODUCTIVE SUCCESS OF THE ENDANGERED MARIANA CROW (CORVUS KUBARYI)

Abstract Reasons for the decline of the Mariana Crow (Corvus kubaryi) on the Western Pacific island of Rota are currently unknown, but a need to protect nesting habitat has been suggested. We examined 55 actual nest sites and 60 random sites from 1997 to 1999 to investigate habitat characteristics specific to crow nest sites. Both nests and random plots were predominantly in limestone forest habitat. Discriminant function analyses indicate actual nest sites were differentiated from random sites based on a higher percentage of canopy cover and mean DBH of papaya (Carica papaya) and woody vines, as well as a higher stem count of species associated with limestone forests. This resulted in correct classification of a potential site as nesting versus random in 92% of the cases. Actual nests were >300 m from buildings, while random sites averaged (± SE) 226.7 ± 71.6 m from a building. Actual nest sites were about twice as far from a road as random nest sites. Twenty-eight of the 55 active nests fledged young. Nests in native forests were associated with higher reproductive success than nests in more disturbed areas. These findings suggest that damage to habitat from anthropogenic or natural causes may be limiting nesting success.