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At least 55 records · Page 3Linked to original sources
USGS2022

Ungulate migrations of the western United States, volume 2

Migration is widespread across taxonomic groups and increasingly recognized as fundamental to maintaining abundant wildlife populations and communities. Many ungulate herds migrate across the western United States to access food and avoid harsh environmental conditions. With the advent of global positioning system (GPS) collars, researchers can describe and map the year-round movements of ungulates at both large and small spatial scales. The migrations can traverse landscapes that are a mix of different jurisdictional ownership and management. Today, the landscapes migrating herds traverse are increasingly threatened by fencing, high-traffic roads, oil and gas development, and other types of permanent development. Through the use of GPS collars, a model of science-based conservation emerged in which migration corridors, stopovers, and winter ranges can be mapped in detail, thereby allowing threats and conservation opportunities to be identified and remedied. In 2018, the U.S. Geological Survey (USGS) assembled a Corridor Mapping Team (CMT) to work collaboratively with western states to map migrations of Odocoileus hemionus (mule deer), Cervus canadensis (elk), and Antilocapra americana (pronghorn). Led by the USGS Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of Federal scientists, university researchers, and biologists and analysts from participating State and Tribal agencies. The first set of maps described a total of 42 migrations across 5 western states and was published in 2020 as the first volume of this report series. This second volume describes an additional 65 migrations mapped within 9 western states and select Tribal lands. As the western United States continues to grow, this report series and the associated map files released by the USGS will allow for migration maps to be used for conservation planning by a wide array of State and Federal stakeholders to reduce barriers to migration caused by fences, roads, and other development.

western United States↗
USGS2014

Strategic conservation planning for the Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team

The Eastern North Carolina/Southeastern Virginia Strategic Habitat Conservation Team (ENCSEVA) is a partnership among local federal agencies and programs with a mission to apply Strategic Habitat Conservation to accomplish priority landscape-level conservation within its geographic region. ENCSEVA seeks to further landscape-scale conservation through collaboration with local partners. To accomplish this mission, ENCSEVA is developing a comprehensive Strategic Habitat Conservation Plan (Plan) to provide guidance for its members, partners, and collaborators by establishing mutual conservation goals, objectives, strategies, and metrics to gauge the success of conservation efforts. Identifying common goals allows the ENCSEVA team to develop strategies that leverage joint resources and are more likely to achieve desired impacts across the landscape. The Plan will also provide an approach for ENCSEVA to meet applied research needs (identify knowledge gaps), foster adaptive management principles, identify conservation priorities, prioritize threats (including potential impacts of climate change), and identify the required capacity to implement strategies to create more resilient landscapes. ENCSEVA seeks to support the overarching goals of the South Atlantic Landscape Conservation Cooperative (SALCC) and to provide scientific and technical support for conservation at landscape scales as well as inform the management of natural resources in response to shifts in climate, habitat fragmentation and loss, and other landscape-level challenges (South Atlantic LCC 2012). The ENCSEVA ecoregion encompasses the northern third of the SALCC geography and offers a unique opportunity to apply landscape conservation at multiple scales through the guidance of local conservation and natural resource management efforts and by reporting metrics that reflect the effectiveness of those efforts (Figure 1). The Environmental Decision Analysis Team, housed within the North Carolina Cooperative Fish and Wildlife Research Unit at North Carolina State University, is assisting the ENCSEVA team in developing a scientifically sound basis for the Plan though the elicitation of expert knowledge and the organization of that knowledge using the Open Standards for the Practice of Conservation. The Open Standards for the Practice of Conservation is a framework that is well suited to incorporating decision-making tools such as Structured Decision Making and provides a multi-step process to conceptually organize conservation projects in a manner that enhances the rigor and transparency of expert and knowledge-based plans. It helps define explicit pathways from 2 planned conservation activities and ultimate impact, as well as indicators to measure success (Stem et al. 2005). Specifically, the framework identifies conservation targets, key ecological attributes, threats, and associated indicators to monitor responses given the implementation of a conservation action (Conservation Measures Partnership 2007). This report serves to provide a scientific foundation for the Plan by summarizing the expert opinion of wildlife biologists, ecologists, hydrologists, researchers, natural resource managers, and conservation practitioners regarding five environments (wetlands, riverine systems, estuaries, uplands, and barrier islands) within the ENCSEVA geography. Specifically, this report describes (1) the approach to elicit expert knowledge meant to support the strategic plan, (2) how this knowledge can inform collaborative conservation planning, and (3) a summary of opportunities available for the ENCSEVA team to address threats and impacts associated with climate change within the ecoregion.

Technical Bulletin↗
USGS2017

Five-year external reviews of the eight Department of Interior Climate Science Centers: Southeast Climate Science Center

In 2008, the U.S. Congress authorized the establishment of the National Climate Change and Wildlife Science Center (NCCWSC) within the U.S. Department of Interior (DOI). Housed administratively within the U.S. Geological Survey (USGS), NCCWSC is part of the DOI’s ongoing mission to meet the challenges of climate change and its effects on wildlife and aquatic resources. From 2010 through 2012, NCCWSC established eight regional DOI Climate Science Centers (CSCs). Each of these regional CSCs operated with the mission to “synthesize and integrate climate change impact data and develop tools that the Department’s managers and partners can use when managing the Department’s land, water, fish and wildlife, and cultural heritage resources” (Salazar 2009). The model developed by NCCWSC for the regional CSCs employed a dual approach of a federal USGS-staffed component and a parallel host-university component established competitively through a 5-year cooperative agreement with NCCWSC. At the conclusion of this 5-year agreement, a review of each CSC was undertaken, with the Southeast Climate Science Center (SE CSC) review in February 2016. The SE CSC is hosted by North Carolina State University (NCSU) in Raleigh, North Carolina, and is physically housed within the NCSU Department of Applied Ecology along with the Center for Applied Aquatic Ecology, the North Carolina Cooperative Fish and Wildlife Research Unit (CFWRU), and the North Carolina Agromedicine Institute. The U.S. Department of Agriculture Southeast Regional Climate Hub is based at NCSU as is the National Oceanic and Atmospheric Administration (NOAA) Southeast Regional Climate Center, the North Carolina Institute for Climate Studies, the North Carolina Wildlife Resources Commission, the NOAA National Weather Service, the State Climate Office of North Carolina, and the U.S. Forest Service Eastern Forest Environmental Threat Assessment Center. This creates a strong core of organizations operating in close proximity focused on climate issues. The geographic area covered by the SE CSC represents all or part of 16 states and the Caribbean Islands and has overlapping boundaries with seven Landscape Conservation Cooperatives (LCCs): Appalachian LCC, Eastern Tallgrass Prairie and Big Rivers LCC, Gulf Coast Prairie LCC, Gulf Coastal Plains and Ozarks LCC, Peninsular Florida LCC, South Atlantic LCC, and Caribbean LCC. The SE CSC region also encompasses 134 U.S. Fish and Wildlife Service refuges and 89 National Park Service (NPS) units and is home to 11 federally recognized and 54 state recognized tribes.

Report↗
USGS2013

Possible return of Acropora cervicornis at Pulaski Shoal, Dry Tortugas National Park, Florida

Seabed classification is essential to assessing environmental associations and physical status in coral reef ecosystems. At Pulaski Shoal in Dry Tortugas National Park, Florida, nearly continuous underwater-image coverage was acquired in 15.5 hours in 2009 along 70.2 km of transect lines spanning ~0.2 km 2 . The Along-Track Reef-Imaging System (ATRIS), a boat-based, high-speed, digital imaging system, was used. ATRIS-derived benthic classes were merged with a QuickBird satellite image to create a habitat map that defines areas of senile coral reef, carbonate sand, seagrasses, and coral rubble. This atypical approach of starting with extensive, high-resolution in situ imagery and extrapolating between transect lines using satellite imagery leverages the strengths of each remote-sensing modality. The ATRIS images also captured the spatial distribution of two species once common on now-degraded Florida-Caribbean coral reefs: the stony staghorn coral Acropora cervicornis , a designated threatened species, and the long-spined urchin Diadema antillarum . This article documents the utility of ATRIS imagery for quantifying number and estimating age of A. cervicornis colonies ( n = 400, age range, 5–11 y) since the severe hypothermic die-off in the Dry Tortugas in 1976–77. This study is also the first to document the largest number of new colonies of A. cervicornis tabulated in an area of the park where coral-monitoring stations maintained by the Fish and Wildlife Research Institute have not been established. The elevated numbers provide an updated baseline for tracking revival of this species at Pulaski Shoal.

Florida↗
USGS2010

Wyoming Landscape Conservation Initiative Science and Management Workshop Proceedings, May 12-14, 2009, Laramie, Wyoming

The U.S. Geological Survey (USGS) hosted the second Wyoming Landscape Conservation Initiative (WLCI) Science and Management Workshop at the University of Wyoming Conference Center and Hilton Garden Inn on May 12, 13, and 14, 2009, in Laramie, Wyo. The workshop focused on six topics seen as relevant to ongoing WLCI science and management activities: mapping and modeling resources for decisionmaking; data information and management; fish and wildlife research; changing landscapes; monitoring; and reclamation and offsite mitigation. Panelists gave presentations on ongoing research in these six areas during plenary sessions followed by audience discussions. Three breakout groups focused on discussing wildlife, reclamation, and monitoring. Throughout the plenary sessions, audience discussions, and breakout groups, several needs were repeatedly emphasized by panelists and workshop participants: developing a conservation plan and identifying priority areas and species for conservation actions; gaining a deeper understanding of sagebrush ecology; identifying thresholds for wildlife that can be used to create an 'early warning system' for managers; continuing to collect basic data across the landscape; facilitating even greater communication and partnership across agencies and between scientists and land managers; and engaging proactively in understanding new changes on the landscape such as wind energy development and climate change. Detailed proceedings from the workshop are captured and summarized in this report.

Scientific Investigations Report↗
USGS2020

Ungulate migrations of the western United States, Volume 1

Across the western United States, many ungulate herds must migrate seasonally to access resources and avoid harsh winter conditions. Because these migration paths cover vast landscapes (in other words migration distances up to 150 miles [241 kilometers]), they are increasingly threatened by roads, fencing, subdivisions, and other development. Over the last decade, many new tracking studies have been conducted on migratory herds, and analytical methods have been developed that allow for population-level corridors and stopovers to be mapped and prioritized. In 2018, the U.S. Geological Survey assembled a Corridor Mapping Team to provide technical assistance to western states working to map bison, elk, moose, mule deer, and pronghorn migrations using existing Global Positioning System data. Led by the Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of federal scientists, university researchers, and biologists and analysts from participating state agencies. In its first year, the team has worked to develop standardized analytical and computational methods and a workflow applicable to datasets typically collected by state agencies. In 2019, the team completed analyses necessary to map corridors, stopovers, routes and winter ranges in Arizona, Idaho, Nevada, Utah, and Wyoming. A total of 26 corridors, 16 migration routes, 25 stopovers, and 9 winter ranges were mapped across these states and are included in this report. This report and associated data release provide the means for the habitats required for migration to be taken into account by state and federal transportation officials, land and wildlife managers, planners, and other conservationists working to maintain big-game migration in the western states.

Scientific Investigations Report↗
USGS2001

Development of a bird banding recapture database

Recaptures (and resightings) constitute the vast majority of post-release data from banded or otherwise marked nongame birds. A powerful suite of contemporary analytical models is available for using recapture data to estimate population size, survival rates and other parameters, and many banders collect recapture data for their project specific needs. However, despite widely recognized, broader programmatic needs for more and better data, banders' recapture data are not centrally reposited and made available for use by others. To address this need, the US Bird Banding Laboratory, the Canadian Bird Banding Office and the Georgia Cooperative Fish and Wildlife Research Unit are developing a bird banding recapture database. In this poster we discuss the critical steps in developing the database, including: determining exactly which recapture data should be included; developing a standard record format and structure for the database; developing electronic means for collecting, vetting and disseminating the data; and most importantly, developing metadata descriptions and individual data set profiles to facilitate the user's selection of appropriate analytical models. We provide examples of individual data sets to be included in the database, and we assess the feasibility of developing a prescribed program for obtaining recapture data from banders who do not presently collect them. It is expected that the recapture database eventually will contain millions of records made available publicly for a variety of avian research and management purposes

Book chapter↗
USGS1995

Residues and trends of organochlorine pesticide and polychlorinated biphenyls in birds from Texas, 1965-88

Concentrations of DDE (a metabolite of DDT) in birds decreased during recent years in most areas of the continental United States. Organochlorine pesticides were widely used in agriculture in Texas from the early 1950s to the 1970s. I used previously published data to determine whether concentrations of DDE and polychlorinated biphenyls (PCBs) in birds from Texas have followed a decreasing trend similar to that in birds from other areas in the United States. A total of 2,669 bird samples was collected between 1965 and 1988 from diverse locations in Texas and was analyzed for organochlorines and other environmental contaminants. The brown pelican ( Pelecanus occidentalis ), peregrine falcon ( Falco peregrinus ), laughing gull ( Larus atricilla ), black skimmer ( Rynchops niger ), and European starling ( Sturnus vulgaris ) were the most frequently studied species. DDE and PCBs were the most commonly detected organochlorines in bird tissues. Mean DDE concentrations ranged from 0.4 to 61.00 parts per million (ppm) wet weight (ww) and PCBs from 0.02 to 32.00 ppm ww. Concentrations of DDE in eggs and carcasses of black skimmers decreased significantly during 1970-84 and dropped from approximately 10 to nearly 3 ppm ww. PCBs decreased from approximately 7 ppm ww to 1 ppm ww in eggs and carcasses. DDE concentrations in eggs of brown pelicans varied from more than 3 ppm ww in 1970 to approximately 1 ppm ww in 1983; and PCB concentrations diminished from about 10 to 1 ppm ww. Decreasing trends in concentrations of DDE and PBCs were observed in most species, although in some cases, the estimated trends were not significantly different from zero. Concentrations of DDE in birds from the Texas coast decreased from more than 6.0 ppm in 1978 to below 0.5 ppm in 1985. The decreasing ratios in selected species varied from approximately 2.0 to 12.0 (DDE) and from 4.5 to 9.0 (PCBs). The results indicate that in general from 1965 to 1988, DDE and PCBs declined in birds from Texas.

Texas↗
USGS2008

Conservation genetics and species recovery

Recent advances in molecular genetics have proven to be extremely useful in efforts to conserve imperiled species. Genetics data are used to identify appropriate units of management (e.g., populations, metapopulations), effective sizes of breeding populations, population mixing rates, and other variables. These data help managers make decisions about which populations to preserve, whether to move individuals from one site to another, how to breed species most effectively in captivity, and even, in some cases, what taxonomic classification is most appropriate. Many U.S. Geological Survey (USGS) Science Centers and Cooperative Fish and Wildlife Research Units have developed capabilities in genetics research. The two case studies that follow illustrate how USGS geneticists are assisting managers in recovering species on the brink.

Endangered Species Bulletin↗
USGS2016

Estimating black bear density in New Mexico using noninvasive genetic sampling coupled with spatially explicit capture-recapture methods

During the 2004–2005 to 2015–2016 hunting seasons, the New Mexico Department of Game and Fish (NMDGF) estimated black bear abundance (Ursus americanus) across the state by coupling density estimates with the distribution of primary habitat generated by Costello et al. (2001). These estimates have been used to set harvest limits. For example, a density of 17 bears/100 km2 for the Sangre de Cristo and Sacramento Mountains and 13.2 bears/100 km2 for the Sandia Mountains were used to set harvest levels. The advancement and widespread acceptance of non-invasive sampling and mark-recapture methods, prompted the NMDGF to collaborate with the New Mexico Cooperative Fish and Wildlife Research Unit and New Mexico State University to update their density estimates for black bear populations in select mountain ranges across the state. We established 5 study areas in 3 mountain ranges: the northern (NSC; sampled in 2012) and southern Sangre de Cristo Mountains (SSC; sampled in 2013), the Sandia Mountains (Sandias; sampled in 2014), and the northern (NSacs) and southern Sacramento Mountains (SSacs; both sampled in 2014). We collected hair samples from black bears using two concurrent non-invasive sampling methods, hair traps and bear rubs. We used a gender marker and a suite of microsatellite loci to determine the individual identification of hair samples that were suitable for genetic analysis. We used these data to generate mark-recapture encounter histories for each bear and estimated density in a spatially explicit capture-recapture framework (SECR). We constructed a suite of SECR candidate models using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We used Akaike’s Information Criterion corrected for small sample size (AICc) to rank and select the most supported model from which we estimated density. We set 554 hair traps, 117 bear rubs and collected 4,083 hair samples. We identified 725 (367 M, 358 F) individuals; the sex ratio for each study area was approximately equal. Our density estimates varied within and among mountain ranges with an estimated density of 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) for the NSC, 19.74 bears/100 km2 (95% CI: 13.77 – 28.30) in the SSC, 25.75 bears/100 km2 (95% CI: 13.22 – 50.14) in the Sandias, 21.86 bears/100 km2 (95% CI: 17.83 – 26.80) in the NSacs, and 16.55 bears/100 km2 (95% CI: 11.64 – 23.53) in the SSacs. Overall detection probability for hair traps and bear rubs, combined, was low across all study areas and ranged from 0.00001 to 0.02. We speculate that detection probabilities were affected by failure of some hair samples to produce a complete genotype due to UV degradation of DNA, and our inability to set and check some sampling devices due to wildfires in the SSC. Ultraviolet radiation levels are particularly high in New Mexico compared to other states where NGS methods have been used because New Mexico receives substantial amounts of sunshine, is relatively high in elevation (1,200 m – 4,000 m), and is at a lower latitude. Despite these sampling difficulties, we were able to produce density estimates for New Mexico black bear populations with levels of precision comparable to estimated black bear densities made elsewhere in the U.S. Our ability to generate reliable black bear density estimates for 3 New Mexico mountain ranges is attributable to our use of a statistically robust study design and analytical method. There are multiple factors that need to be considered when developing future SECR-based density estimation projects. First, the spatial extent of the population of interest and the smallest average home range size must be determined; these will dictate size of the trapping array and spacing necessary between hair traps. The number of technicians needed and access to the study areas will also influence configuration of the trapping array. We believe shorter sampling occasions could be implemented to reduce degradation of DNA due to UV radiation; this might help increase amplification rates and thereby increase both the number of unique individuals identified and the number of recaptures, improving the precision of the density estimates. A pilot study may be useful to determine the length of time hair samples can remain in the field prior to collection. In addition, researchers may consider setting hair traps and bear rubs in more shaded areas (e.g., north facing slopes) to help reduce exposure to UV radiation. To reduce the sampling interval it will be necessary to either hire more field personnel or decrease the number of hair traps per sampling session. Both of these will enhance detection of long-range movement events by individual bears, increase initial capture and recapture rates, and improve precision of the parameter estimates. We recognize that all studies are constrained by limited resources, however, increasing field personnel would also allow a larger study area to be sampled or enable higher trap density. In conclusion, we estimated the density of black bears in 5 study areas within 3 mountains ranges of New Mexico. Our estimates will aid the NMDGF in setting sustainable harvest limits. Along with estimates of density, information on additional demographic rates (e.g., survival rates and reproduction) and the potential effects that climate change and future land use may have on the demography of black bears may also help inform management of black bears in New Mexico, and may be considered as future areas for research.

New Mexico↗
USGS2020

Using video survey to examine the effect of habitat on gag grouper encounter

Gag is a reef fish that was declared overfished in the Gulf of Mexico (GOM) in 2009. Although Gag are no longer listed as overfished, fisheries managers are concerned that stocks may not be recovering. Our objective was to identify habitat characteristics important to Gag, and their effect on the probability of Gag occurrence. We obtained data from three separate fisheries-independent video surveys that sampled in the eastern GOM from 2010-2017: the National Atmospheric and Oceanic Administration (NOAA) Panama City, FL Office, the NOAA Southeast Area Monitoring and Assessment Program, and the Florida Fish and Wildlife Research Institute. We ran a separate mixed effects logistic regression for each survey, and used Akaike’s Information Criteria to determine the best fitting models. Some variables - percent rock coverage, vertical relief, latitude, and depth - were present in all confidence models. Depth did not have the same relationship with Gag across all surveys, suggesting that shallower habitats (<50 m) might be more suitable for juveniles, whereas deeper habitats (>50 m) might be more suitable for adults. Managers may be able to help Gag and encourage their recovery by using these data to establish or expand protected areas throughout shallower waters.

Florida↗
USGS2023

The bee lab

Introduction The U.S. Geological Survey (USGS) Bee Lab is a collaborative interagency joint venture and international leader for bee (Hymenoptera: Apoidea) identification, survey design, quantification of bee and plant interrelations, and development and maintenance of occurrence databases. Each of these objectives supports native bee conservation by providing critical data and tools for the United States and other countries. The Bee Lab is part of the USGS Eastern Ecological Science Center (EESC) and located in Laurel, Maryland, at the U.S. Fish and Wildlife Service (USFWS) Patuxent Research Refuge. The laboratory houses scientists from the EESC, USGS’s Cooperative Fish and Wildlife Research Units, and the USFWS to develop identification tools and survey design support for State, Federal, Tribal, and nongovernment organization partners. In addition to the development of identification tools, important objectives include developing keys for native and nonnative bee species and making those tools accessible to partners and the public. Among the most visible and reused products produced during the development of the tools are the detailed photographs of the bees themselves. Accurate bee identification allows for better monitoring of bee species and examination of environmental factors that may influence their populations.

Fact Sheet↗
USGS2002

Ecological dynamics of wetlands at Lisbon Bottom, Big Muddy National Fish and Wildlife Refuge, Missouri

The study documented the interaction between hydrology and the biological dynamics within a single spring season at Lisbon Bottom in 1999. The study goal was to provide information necessary for resource managers to develop management strategies for this and other units of the Big Muddy National Fish and Wildlife Refuge. Researchers studied the hydrology, limnology, and biological dynamics of zooplankton, macroinvertebrates, fish and waterbird communities. Lisbon Bottom is one of several parcels of 1993 flood-damaged land that was purchased from willing sellers by the U.S. Fish and Wildlife Service as part of the Big Muddy National Fish and Wildlife Refuge. Lisbon Bottom is a loop bend in the river near Glasgow in Howard County, Missouri between approximately river mile (RM) 213 to RM 219. Flooding at Lisbon in 1993 and 1995 breeched local levees and created a diverse wetland complex.

Missouri↗
USGS1986

This week?s Citation Classic: 'Stickel, L. F. A comparison of certain methods of measuring ranges of small mammals. J. Mammalogy 35: 1-15, 1954.'

During my first employment as a junior biologist conducting food habits analyses at the Patuxent Research Refuge (now Patuxent Wildlife Research Center) of the US Fish and Wildlife Service, the first station director, Arnold L. Nelson, gave each staff biologist the opportunity to spend a little time conducting field studies on the 2,600-acre research area. These studies were to help in ecological evaluation of the area, but also, no doubt, functioned as a morale builder for biologists daily engaged in difficult, demanding and confining laboratory work. I undertook to measure the population density of small mammals in different habitats. The state-of-the-art methods recommended to me and prevalent in the literature worried me, especially after preliminary field work. Reading the classic, paper by W.H. Burt [Terrioriality and home range concepts as applied to mammals. J. Mammalogy 24:346-352, 1943] was a turning point for me in seeing that knowledge of home-range size was the key to measuring population density. My first papers employed these concepts in field evaluations. However, they could give-only limited attention to the question of how home ranges could be measured. Furthermore, the importance of knowledge of the home range to habitat evaluation and to understanding animal behavior was becoming increasingly apparent. Advocacy of many different methods of measuring home ranges appeared in the literature. It did not seem possible to evaluate them objectively. It occurred to me that artificial populations could be used to help in understanding the mechanisms of measuring home ranges. The effects of random trap-visiting, bias toward central traps, trap-spacing, range shape, and other factors could be considered. So grids of traps were inked onto oversize graph paper, and simulated ranges were cut from plastic to be tossed as randomly as possible on the trap-grids. It was a slow, laborious job. Analysis showed that random captures in artificial populations produced patterns that were similar in many ways to those observed in field studies; the necessity of appropriate trap-spacing in relation to range size became obvious. Some commonly used methods of expressing range size proved to be clearly superior to others. However, the artificial populations could not fully simulate actual populations, where use patterns changed as conditions changed and the ?boundaries? of ranges tended to shift continuously or with time. Progress was made, but problems remained. I suspect that the reasons the paper has been cited frequently rest on the continuing interest in home-range behavior and the continuing difficulty in field evaluations, despite the many advances in observational methodology. The sophisticated techniques that became possible with the use of computers [R.I. Jennrich and F.B. Turner. Measurement of non-circular home range. J. Theor. Biol 23:227-237, 1969] also presented new possibilities for analysis and understanding of home-range characteristics and created a resurgence of interest in home-range behavior and its biological significance.

Current Contents / Agriculture, Biology & Environm↗