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At least 1,261 records · Page 70Linked to original sources

Challenges of implementing a multi-agency monitoring and adaptive management strategy for federally threatened Chinook salmon and steelhead trout during and after dam removal in the Elwha River

Adaptive management, a process of planning, implementing, and evaluating management strategies, is often recommended for monitoring ecological systems. However, few examples of successful implementation and retrospective case studies exist. We provide a case study of adaptively managing hatchery-assisted protection and recovery for Chinook salmon ( Oncorhynchus tshawytscha ) and winter steelhead trout ( O. mykiss ) during and after the removal of two large mainstem dams in the Elwha River, WA. We summarize key aspects of the monitoring and adaptive management plan over the last decade and highlight successes, challenges, and complications during the plan’s implementation. The Elwha Monitoring and Adaptive Management Guidelines included a trigger-based system for moving through four phases of recovery that included preservation, recolonization, local adaptation, and viable natural population, each with differing levels of hatchery production as the management actions. The monitoring component of the plan has been very successful, providing critical data to guide management actions that otherwise may not have occurred and, opportunistically, provided data for other native species in the Elwha River. Implementing adaptive management provided mixed results and was at times hindered by divergent management goals among project partners, the inflexibility of the Endangered Species Act regulatory requirements as implemented for this project, and conflicting information among guidance documents. We learned that some metrics and triggers in the plan were ill-defined or too difficult to measure in the field. In some cases, the performance indicators and/or triggers were successfully modified to incorporate what was learned; however, in other cases, we were unable to revise the values due to differing opinions among partners. The ability to reach consensus on revised triggers appeared to be influenced by the recovery trajectory of the species involved. The implemented adaptive management strategy resulted in substantial collaboration and learning, which resulted in revised management strategies, but was imperfect. Sufficient long-term funding is necessary to implement a well-designed monitoring program and could benefit from including a defined leadership position to shepherd and facilitate a multi-stakeholder adaptive management program. Additionally, incorporating adaptive management into legally binding conditions under the Endangered Species Act is feasible, but requires substantial pre-planning in close coordination with regulatory agencies.

Washington↗

Improving ecosystem health in highly altered river basins: A generalized framework and its application to the Mississippi-Atchafalaya River Basin

Continued large-scale public investment in declining ecosystems depends on demonstrations of “success”. While the public conception of “success” often focuses on restoration to a pre-disturbance condition, the scientific community is more likely to measure success in terms of improved ecosystem health. Using a combination of literature review, workshops and expert solicitation we propose a generalized framework to improve ecosystem health in highly altered river basins by reducing ecosystem stressors, enhancing ecosystem processes and increasing ecosystem resilience. We illustrate the use of this framework in the Mississippi-Atchafalaya River Basin (MARB) of the central United States (U.S.), by (i) identifying key stressors related to human activities, and (ii) creating a conceptual ecosystem model relating those stressors to effects on ecosystem structure and processes. As a result of our analysis, we identify a set of landscape-level indicators of ecosystem health, emphasizing leading indicators of stressor removal (e.g., reduced anthropogenic nutrient inputs), increased ecosystem function (e.g., increased water storage in the landscape) and increased resilience (e.g., changes in the percentage of perennial vegetative cover). We suggest that by including these indicators, along with lagging indicators such as direct measurements of water quality, stakeholders will be better able to assess the effectiveness of management actions. For example, if both leading and lagging indicators show improvement over time, then management actions are on track to attain desired ecosystem condition. If, however, leading indicators are not improving or even declining, then fundamental challenges to ecosystem health remain to be addressed and failure to address these will ultimately lead to declines in lagging indicators such as water quality. Although our model and indicators are specific to the MARB, we believe that the generalized framework and the process of model and indicator development will be valuable in an array of altered river basins.

Mississippi-Atchafalaya River Basin↗

Identifying and filling critical knowledge gaps can optimize financial viability of blue carbon projects in tidal wetlands

One of the world’s largest “blue carbon” ecosystems, Louisiana’s tidal wetlands on the US Gulf of Mexico coast, is rapidly being lost. Louisiana’s strong legal, regulatory, and monitoring framework, developed for one of the world’s largest tidal wetland systems, provides an opportunity for a programmatic approach to blue carbon accreditation to support restoration of these ecologically and economically important tidal wetlands. Louisiana’s coastal wetlands span ∼1.4 million ha and accumulate 5.5–7.3 Tg yr −1 of blue carbon (organic carbon), ∼6%–8% of tidal marsh blue carbon accumulation globally. Louisiana has a favorable governance framework to advance blue carbon accreditation, due to centralized restoration planning, long term coastal monitoring, and strong legal and regulatory frameworks around carbon. Additional restoration efforts, planned through Louisiana’s Coastal Master Plan, over 50 years are projected to create, or avoid loss of, up to 81,000 ha of wetland. Current restoration funding, primarily from Deepwater Horizon oil spill settlements, will be fully committed by the early 2030s and additional funding sources are required. Existing accreditation methodologies have not been successfully applied to coastal Louisiana’s ecosystem restoration approaches or herbaceous tidal wetland types. Achieving financial viability for accreditation of these restoration and wetland types will require expanded application of existing blue carbon crediting methodologies. It will also require expanded approaches for predicting the future landscape without restoration, such as numerical modeling, to be validated. Additional methodologies (and/or standards) would have many common elements with those currently available but may be beneficial, depending on the goals and needs of both the state of Louisiana and potential purchasers of Louisiana tidal wetland carbon credits. This study identified twenty targeted needs that will address data and knowledge gaps to maximize financial viability of blue carbon accreditation for Louisiana’s tidal wetlands. Knowledge needs were identified in five categories: legislative and policy, accreditation methodologies and standards, soil carbon flux, methane flux, and lateral carbon flux. Due to the large spatial scale and diversity of tidal wetlands, it is expected that progress in coastal Louisiana has high potential to be generalized to similar wetland ecosystems across the northern Gulf of Mexico and globally.

Louisiana↗

Wet meadow regeneration through restoration of biophysical feedbacks

Wet meadows are globally significant ecosystems that provide critical hydrological, ecological, and biogeochemical functions, yet their extent has declined dramatically due to land use changes and hydrologic alteration. These sedge-dominated wetlands exist at the drier end of the wetland gradient, maintained by shallow groundwater and periodic inundation. This paper is a global synthesis of the ecological, geomorphic, and hydrological dynamics of wet meadows, with an emphasis on alluvial systems, to inform effective restoration strategies. We compare wet meadows to other wetlands, classify them into palustrine, lacustrine, and alluvial types, then focus on alluvial wet meadows and discuss how their formation and persistence depend on ground and surface water interactions, sediment deposition and flow obstructions, all mediated by biological processes. In particular, we highlight the role of hydric graminoids in resisting erosion and maintaining soil cohesion, how beaver promote meadow persistence, and the significance of wet meadows as carbon sinks. We also present stratigraphic evidence demonstrating that incision, often triggered by anthropogenic activity or changing climate, is the primary mechanism of alluvial wet meadow degradation, resulting in water table decline and shifts in vegetation composition. Restoration requires reversing these incisional processes through techniques that elevate water tables, disperse flow and retain sediment—methods traditionally associated with either soil conservation or stream restoration. These include nature-based solutions that create obstructions such as beaver dams and their analogues, rock and wood-based obstructions and incision trench or gully filling and grading. Given their multifunctional value—including but not limited to flood attenuation, biodiversity support, and carbon sequestration—wet meadows warrant a focused restoration framework. This review advocates for a valley-floor scale restoration paradigm that integrates hydrological reconnection, sediment retention, and biological reinforcement to ensure long-term resilience of these systems in the face of changing climate and land use pressures.

Frontiers in Environmental Science↗

Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.

Understanding habitat connectivity is critical for managing nonindigenous aquatic species (NAS) spread. Dams and watershed boundaries can be impassable to NAS during typical conditions but may become temporarily passable during flooding. The goal of our project was to develop an approach for identifying locations of aquatic connectivity at a fine spatial scale along watershed boundaries using readily available data. To develop this approach, we focused on the potential for range expansion of invasive fish in the United States via possible cross-boundary habitat connections. First, we developed an index using metrics of elevation, watershed size, and geology at regular points along a watershed boundary to stratify points by likelihood of connectivity during high precipitation (>20 mm of precipitation in a 3-day period). We then used a subset of points across a gradient of connectivity likelihoods to gather Landsat-derived observed surface water data and developed a statistical model to predict surface water presence from landscape characteristics. We applied the model throughout the entire watershed boundary to identify locations of hydrologic connectivity during high-water events. The presence of surface water on watershed boundaries was predicted by the interactions between watershed boundary point elevation relative to the minimum adjacent HUC-12 elevations and watershed boundary point elevation relative to neighboring point elevations (marginal R 2 = 0.94). Our approach can be used to identify potential areas of surface water connectivity between watersheds quickly and easily at a fine spatial scale using readily available, remotely sensed data that can inform conservation and management actions across disciplines.

North Dakota, South Dakota↗

Integrating habitat suitability and climate constraints to predict nonnative fish invasion risk for U.S. streams and inland lakes

Introduction: Nonnative fishes in streams and inland lakes can substantially alter aquatic ecosystems by degrading habitat conditions, competing with native species, and restructuring food webs. Identifying invasion hotspots can inform proactive management and prevention of nonnative species establishment. Methods: In this study, we identified streams and lakes across the conterminous United States that are vulnerable to invasion by 18 nonnative stream and 28 nonnative lake fish species. Habitat suitability models were developed separately for stream and lake species across nine ecoregions using natural and anthropogenic predictors, and species occurrences were predicted by integrating model results with climate match scores based on comparisons between environmental conditions in species’ native and potential nonnative ranges. We classified areas with both high habitat suitability and strong climate similarity as having high invasion potential and generated hotspot maps by stacking species-level predictions. Results: Florida exhibits the highest invasion risk for both habitat types. Stream hotspots were concentrated near major metropolitan areas, whereas lake hotspots were more widely distributed across the Great Lakes basin and the northeastern U.S. Twelve species were predicted to invade both habitat types, with goldfish ( Carassius auratus ) and pirapitinga ( Piaractus brachypomus ) showing particularly high invasion potential. Discussion: These findings provide a comprehensive assessment of nonnative freshwater fish invasion risk and support targeted monitoring and management strategies.

conterminous United States↗

Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

AIMS Environmental Science↗

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science↗

Simulating long-term effectiveness and efficiency of management scenarios for an invasive grass

Resource managers are often faced with trade-offs in allocating limited resources to manage plant invasions. These decisions must often be made with uncertainty about the location of infestations, their rate of spread and effectiveness of management actions. Landscape level simulation tools such as state-and-transition simulation models (STSMs) can be used to evaluate the potential long term consequences of alternative management strategies and help identify those strategies that make efficient use of resources. We analyzed alternative management scenarios for African buffelgrass ( Pennisetum ciliare syn. Cenchrus ciliaris ) at Ironwood Forest National Monument, Arizona using a spatially explicit STSM implemented in the Tool for Exploratory Landscape Scenario Analyses (TELSA). Buffelgrass is an invasive grass that is spreading rapidly in the Sonoran Desert, affecting multiple habitats and jurisdictions. This invasion is creating a novel fire risk and transforming natural ecosystems. The model used in this application incorporates buffelgrass dispersal and establishment and management actions and effectiveness including inventory, treatment and post-treatment maintenance. We simulated 11 alternative scenarios developed in consultation with buffelgrass managers and other stakeholders. The scenarios vary according to the total budget allocated for management and the allocation of that budget between different kinds of management actions. Scenario results suggest that to achieve an actual reduction and stabilization of buffelgrass populations, management unconstrained by fiscal restrictions and across all jurisdictions and private lands is required; without broad and aggressive management, buffelgrass populations are expected to increase over time. However, results also suggest that large upfront investments can achieve control results that require relatively minimal spending in the future. Investing the necessary funds upfront to control the invasion results in the most efficient use of resources to achieve lowest invaded acreage in the long-term.

Arizona↗

Encapsulating model complexity and landscape-scale analyses of state-and-transition simulation models: an application of ecoinformatics and juniper encroachment in sagebrush steppe ecosystems

State-and-transition simulation modeling relies on knowledge of vegetation composition and structure (states) that describe community conditions, mechanistic feedbacks such as fire that can affect vegetation establishment, and ecological processes that drive community conditions as well as the transitions between these states. However, as the need for modeling larger and more complex landscapes increase, a more advanced awareness of computing resources becomes essential. The objectives of this study include identifying challenges of executing state-and-transition simulation models, identifying common bottlenecks of computing resources, developing a workflow and software that enable parallel processing of Monte Carlo simulations, and identifying the advantages and disadvantages of different computing resources. To address these objectives, this study used the ApexRMS® SyncroSim software and embarrassingly parallel tasks of Monte Carlo simulations on a single multicore computer and on distributed computing systems. The results demonstrated that state-and-transition simulation models scale best in distributed computing environments, such as high-throughput and high-performance computing, because these environments disseminate the workloads across many compute nodes, thereby supporting analysis of larger landscapes, higher spatial resolution vegetation products, and more complex models. Using a case study and five different computing environments, the top result (high-throughput computing versus serial computations) indicated an approximate 96.6% decrease of computing time. With a single, multicore compute node (bottom result), the computing time indicated an 81.8% decrease relative to using serial computations. These results provide insight into the tradeoffs of using different computing resources when research necessitates advanced integration of ecoinformatics incorporating large and complicated data inputs and models. - See more at: http://aimspress.com/aimses/ch/reader/view_abstract.aspx?file_no=Environ2015030&flag=1#sthash.p1XKDtF8.dpuf

AIMS Environmental Science↗

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

California↗

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

AIMS Environmental Science↗

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

AIMS Environmental Science↗

Use of lidar point cloud data to support estimation of residual trace metals stored in mine chat piles in the Old Lead Belt of southeastern, Missouri

Historic lead and zinc (Pb-Zn) mining in southeast Missouri’s ―Old Lead Belt‖ has left large chat piles dominating the landscape where prior to 1972 mining was the major industry of the region. As a result of variable beneficiation methods over the history of mining activity, these piles remain with large quantities of unrecovered Pb and Zn and to a lesser extent cadmium (Cd). Quantifying the residual content of trace metals in chat piles is problematic because of the extensive field effort that must go into collecting elevation points for volumetric analysis. This investigation demonstrates that publicly available lidar point data from the U.S. Geological Survey 3D Elevation Program (3DEP) can be used to effectively calculate chat pile volumes as a method of more accurately estimating the total residual trace metal content in these mining wastes. Five chat piles located in St. Francois County, Missouri, were quantified for residual trace metal content. Utilizing lidar point cloud data collected in 2011 and existing trace metal concentration data obtained during remedial investigations, residual content of these chat piles ranged from 9247 to 88,579 metric tons Pb, 1925 to 52,306 metric tons Zn, and 51 to 1107 metric tons Cd. Development of new beneficiation methods for recovering these constituents from chat piles would need to achieve current Federal soil screening standards. To achieve this for the five chat piles investigated, 42 to 72% of residual Pb would require mitigation to the 1200 mg/kg Federal non-playground standard, 88 to 98% of residual Zn would require mitigation to the Ecological Soil Screening level (ESSL) for plant life, and 70% to 98% of Cd would require mitigation to achieve the ESSL. Achieving these goals through an existing or future beneficiation method(s) would remediate chat to a trace metal concentration level that would support its use as a safe agricultural soil amendment.

Missouri↗

Butyltin residues in southern sea otters (Enhydra lutris nereis) found dead along California coastal waters

Tributyltin (TBT) and its degradation products, mono- (MBT) and dibutyltin (DBT), were determined in liver, kidney, and brain tissues of adult southern sea otters (Enhydra lutris nereis) found dead along the coast of California during 1992a??1996. Hepatic concentrations of butyltin compounds (BTs = MBT + DBT + TBT) ranged from 40 to 9200 ng/g wet wt, which varied depending on the sampling location and gender. Concentrations of BTs in sea otters were comparable to those reported in stranded bottlenose dolphins from the U.S. Atlantic Coast during 1989a??1994. Greater accumulation of butyltins in sea otters was explained by their bottom-feeding habit and the diet that consists exclusively of invertebrates such as mollusks and gastropods. Livers of female sea otters contained approximately 2-fold greater concentrations of BTs than did those of males. The composition of butyltin compounds in sea otter tissues was predominated by TBT in most cases and suggestive of recent exposure. Large harbors such as Monterey Harbor that handle ships legally painted with TBT-containing antifouling paints continued to experience ecotoxicologically significant butyltin contamination. Sea otters, which were affected by infectious diseases, contained greater concentrations of BTs in their tissues than those that died from trauma and other unknown causes.

Californnia↗

Association between perfluorinated compounds and pathological conditions in southern sea otters

Concentrations of four perfluorinated contaminants, including perfluorooctanesulfonate (PFOS) and perfluorooctanoic acid (PFOA), were measured in liver tissue from 80 adult female sea otters collected from the California coast during 1992a??2002. Concentrations of PFOS and PFOA were in the ranges of <1a??884 and <5a??147 ng/g, wet wt, respectively. Concentrations of PFOA in the livers of these sea otters were among the highest values reported for marine mammals to date. Liver tissue from 6 male sea otters also was analyzed and contained significantly higher concentrations of PFOS than did tissues from female otters. To examine the association between exposures and potential effects, concentrations of PFOS and PFOA were compared among the adult female otters that died from infectious diseases, noninfectious causes, and from apparent emaciation. Concentrations of both PFOA and PFOS were significantly higher in sea otters in the infectious disease category than in the noninfectious category. Concentrations of PFOS and PFOA were not significantly different between noninfectious and emaciated otters, suggesting that the poor nutritive (body) status of emaciated otters did not affect the concentrations of perfluorochemicals in livers. Concentrations of PFOA increased significantly from 1992 to 2002, whereas PFOS concentrations increased from 1992 to 1998 and then decreased after 2000. Significant association between infectious diseases and elevated concentrations of PFOS/PFOA in the livers of sea otters is a cause for concern and suggests the need for further studies.

California↗

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↗