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At least 361 records · Page 20Linked to original sources

Simulation modeling of complex climate, wildfire, and vegetation dynamics to address wicked problems in land management

Complex, reciprocal interactions among climate, disturbance, and vegetation dramatically alter spatial landscape patterns and influence ecosystem dynamics. As climate and disturbance regimes shift, historical analogs and past empirical studies may not be entirely appropriate as templates for future management. The need for a better understanding of the potential impacts of climate changes on ecosystems is reaching a new level of urgency, especially in highly perturbed or vulnerable ecological systems. Simulation models are extremely useful tools for guiding management decisions in an era of rapid change, thus providing potential solutions for wicked problems in land management—those that are difficult to solve and inherently resistant to easily definable solutions. We identify three experimental approaches for landscape modeling that address management challenges in the context of uncertain climate futures and complex ecological interactions: (1) an historical comparative approach, (2) a future comparative approach, and (3) threshold detection. We provide examples of each approach from previously published studies of simulated climate, disturbance, and landscape dynamics in forested landscapes of the western United States, modeled with the FireBGCv2 ecosystem process model. Cumulatively, model outcomes indicate that typical land management strategies will likely not be sufficient to counteract the impacts of rapid climate change and altered disturbance regimes that threaten the stability of ecosystems. Without implementation of new, adaptive management strategies, future landscapes are very likely to be different than historical or contemporary ones, with significant and sometimes persistent changes triggered by interactions of climate and wildfire.

Montana, New Mexico, Wyoming

Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

Michigan

Spatial network clustering reveals elk population structure and local variation in prevalence of chronic wasting disease

Spatial organization plays prominent roles in disease transmission, genetics, and demography of wildlife populations and is therefore an important consideration not only for wildlife management, but also for inference about populations and processes. We used hierarchical agglomerative clustering of a spatial graph network to partition Wind Cave National Park (WICA) into five regions used by 163 female elk ( Cervus elaphus ) marked with global positioning system collars during 2005–08 and 2011–13. We grouped elk based on differential use of the five regions, developed a priori models for inter-group variation in the occurrence of chronic wasting disease (CWD), and used Akaike's information criterion to compare models and stratify regions. Previous descriptions of elk population structure, which have been based on social contact or overlap of individual ranges, have distinguished spatially disjunct population subsets. Constructing hierarchical partitions of the landscape enabled us to also discern and describe overlapping and nested subsets. During 2016–18, apparent park-wide prevalence of CWD was 0.18 (90% CI = [0.146, 0.182]); however, prevalence within three spatial strata used primarily by different elk ranged from 0.03 ([0.008, 0.074]) to 0.29 ([0.211, 0.375]). In context with published estimates of recruitment, predation, and anthropogenic mortality, such differences in prevalence equate to increasing local abundance of elk in southwestern WICA, stable to declining abundance in the west/northwest, and rapidly declining abundance in the east. Despite the modest size of WICA (11,357 ha), park-wide averages conflate effects of elk distribution and disease, obscuring spatial patterns with profound implications for study and management of elk and CWD. Graph networks have been used widely in ecology to describe such phenomena as social relationships, connectivity of habitat patches, animal movements, and the spread of disease. Extension to partitioning of geographic range is straightforward but entails different considerations. We discuss allocation of sampling effort, construction of an initial partition, specification of a model for graph cohesion, selection of a clustering algorithm, and identification of useful partitions.

North Dakota

A simple prioritization tool to diagnose impairment of stream temperature for coldwater fishes in the Great Basin

We provide a simple framework for diagnosing the impairment of stream water temperature for coldwater fishes across broad spatial extents based on a weight-of-evidence approach that integrates biological criteria, species distribution models, and geostatistical models of stream temperature. As a test case, we applied our approach to identify stream reaches most likely to be thermally impaired for Lahontan Cutthroat Trout Oncorhynchus clarkii henshawi in the upper Reese River, located in the northern Great Basin, Nevada. We first evaluated the capability of stream thermal regime descriptors to explain variation across 170 sites, and we found that the 7-d moving average of daily maximum stream temperatures (7DADM) provided minimal among-descriptor redundancy and, based on an upper threshold of 20°C, was also a good indicator of acute and chronic thermal stress. Next, we quantified the range of Lahontan Cutthroat Trout within our study area using a geographic distribution model. Finally, we used a geostatistical model to assess spatial variation in 7DADM and predict potential thermal impairment at the stream reach scale. We found that whereas 38% of reaches in our study area exceeded a 7DADM of 20°C and 35% were significantly warmer than predicted, only 17% both exceeded the biological criterion and were significantly warmer than predicted. This filtering allowed us to identify locations where physical and biological impairment were most likely within the network and that would represent the highest management priorities. Although our approach lacks the precision of more comprehensive approaches, it provides a broader context for diagnosing impairment and is a useful means of identifying priorities for more detailed evaluations across broad and heterogeneous stream networks.

Nevada

Hakalau’s moving castle: How climate change and restoration are shifting an island fortress for forest birds

Hakalau Forest Unit of the Big Island National Wildlife Refuge Complex (hereafter, Hakalau) protects the largest area with the highest endemic forest bird diversity in Hawaiʻi, including four federally listed species. Hakalau’s higher elevation montane forest provides refuge from avian malaria ( Plasmodium relictum ), a primary driver of Hawaiian honeycreeper extinctions. However, recent declines in Hakalau’s birds at lower elevations could indicate that conditions have become suitable for disease vector Culex quinquefasciatus . We evaluated the statuses of Hakalau’s bird populations in the context of recent climatic changes using new survey data from point-transect distance sampling, producing abundance estimates from 1999 to 2024. We stratified our analysis across four elevation ranges (<1500 m, 1500–1700 m, 1700–1900 m, and >1900 m) and assessed trends for each species using state-space models (SSMs). We constrained population trajectories to be biologically realistic by incorporating population dynamic models within the SSMs. We observed highly species-specific abundance trends below 1500 m, predominantly stable to upward trends within 1500–1700 m, stable trends within 1700–1900 m, and upward trends above 1900 m. Declines in Hawaiʻi ʻamakihi ( Chlorodrepanis v. virens ) and endangered ʻakiapōlāʻau ( Hemignathus wilsoni ) abundance coincided with lengthening warm seasonal temperatures indicative of shrinking disease-free habitat below 1700 m. Above 1900 m, however, increases in nearly all species indicate that reforestation has likely restored disease-free habitat since 1999. While most species were stable to increasing overall, surveillance for mosquitoes and disease at lower elevations, documenting changes in habitat, and continuing bird population monitoring can help to gauge their long-term persistence at Hakalau.

Hawaii

Variable normal-fault rupture behavior, northern Lost River fault zone, Idaho, USA

The 1983 Mw 6.9 Borah Peak earthquake generated ∼36 km of surface rupture along the Thousand Springs and Warm Springs sections of the Lost River fault zone (LRFZ, Idaho, USA). Although the rupture is a well-studied example of multisegment surface faulting, ambiguity remains regarding the degree to which a bedrock ridge and branch fault at the Willow Creek Hills influenced rupture progress. To explore the 1983 rupture in the context of the structural complexity, we reconstruct the spatial distribution of surface displacements for the northern 16 km of the 1983 rupture and prehistoric ruptures in the same reach of the LRFZ using 252 vertical-separation measurements made from high-resolution (5–10-cm-pixel) digital surface models. Our results suggest the 1983 Warm Springs rupture had an average vertical displacement of ∼0.3–0.4 m and released ∼6% of the seismic moment estimated for the Borah Peak earthquake and <12% of the moment accumulated on the Warm Springs section since its last prehistoric earthquake. The 1983 Warm Springs rupture is best described as the moderate-displacement continuation of primary rupture from the Thousand Springs section into and through a zone of structural complexity. Historical and prehistoric displacements show that the Willow Creek Hills have impeded some, but not all ruptures. We speculate that rupture termination or penetration is controlled by the history of LRFZ moment release, displacement, and rupture direction. Our results inform the interpretation of paleoseismic data from near zones of normal-fault structural complexity and demonstrate that these zones may modulate rather than impede rupture displacement.

Idaho

Estuaries of the Greater Everglades Ecosystem: Laboratories of Long-term Change

Restoring the greater Everglades ecosystem of south Florida is arguably the largest ecosystem restoration effort to date. A critical goal is to return more natural patterns of flow through south Florida wetlands and into the estuaries, but development of realistic targets requires acknowledgement that ecosystems are constantly evolving and changing in response to a variety of natural and human-driven stressors. Examination of ecosystems over long periods of time requires analysis of sedimentary records, such as those deposited in the wetlands and estuaries of south Florida. As sediment accumulates, it preserves information about the animals and plants that lived in the environment and the physical, chemical, and climatic conditions present. One of the methods used to interpret this information is paleoecology-the study of the ecology of previously living organisms. Paleoecologic investigations of south Florida estuaries provide quantitative data on historical variability of salinity and trends that may be applied to statistical models to estimate historical freshwater flow. These data provide a unique context to estimate future ecosystem response to changes related to restoration activities and predicted changes in sea level and temperature, thus increasing the likelihood of successful and sustainable ecosystem restoration.

Fact Sheet

Information on black-footed ferret biology collected within the framework of ferret conservation

Once feared to be extinct, black-footed ferrets ( Mustela nigripes ) were rediscovered near Meeteetse, Wyoming, in 1981, resulting in renewed conservation and research efforts for this highly endangered species. A need for information directly useful to recovery has motivated much monitoring of ferrets since that time, but field activities have enabled collection of data relevant to broader biological themes. This special feature is placed in a context of similar books and proceedings devoted to ferret biology and conservation. Articles include general observations on ferrets, modeling of potential impacts of ferrets on prairie dogs ( Cynomys spp.), discussions on relationships of ferrets to prairie dog habitats at several spatial scales (from individual burrows to patches of burrow systems) and a general treatise on the status of black-footed ferret recovery.

Wyoming

Invertebrate trophic structure on marine ferromanganese and phosphorite hardgrounds

The Southern California Borderland hosts a variety of geologic and oceanographic features that allow for diverse habitats to occur in a restricted region with a strong oxygen minimum zone (OMZ) and hard substrates. These include ferromanganese (FeMn) crusts and phosphorites targeted for deep-seabed mining in other regions. Baseline studies regarding hardground macro- (> 0.3 mm) and megafaunal (> 2 cm) invertebrates are lacking, although they contribute to understanding nutrient cycling and resilience of deep-sea communities to ocean deoxygenation, fishing, or mineral extraction. With the goal of understanding how substrate type, depth, and dissolved oxygen concentration influence invertebrate trophic structure, we surveyed δ 13 C and δ 15 N values of invertebrates on hard substrates on the Southern California Borderland margin along a depth gradient (120–2400 m) through the OMZ at inshore (< 100 km from shore) and offshore (100–250 km from shore) sites, using generalized additive models and community-level metrics. Macrofaunal isotopic values correlate with substrate type, exhibiting higher trophic diversity on FeMn crusts and specialized communities on phosphorites. Megafaunal isotopic values correlate with proximity to shore; animals offshore seem to depend more on phytoplanktonic production than animals inshore. In general, δ 15 N increased with decreasing dissolved oxygen and increasing depth, possibly due to remineralization processes within the OMZ and with depth. We discuss how feeding modes and community composition might influence the observed patterns. This study elucidates the importance of the environmental context in shaping invertebrate trophic structure on continental margins and provides baseline knowledge that may be useful in regions where these minerals are targeted for extraction.

Limnology and Oceanography

Long-term trends of local bird populations based on monitoring schemes: Are they suitable for justifying management measures?

Local biodiversity monitoring is important to assess the effects of global change, but also to evaluate the performance of landscape and wildlife protection, since large-scale assessments may buffer local fluctuations, rare species tend to be underrepresented, and management actions are usually implemented on local scales. We estimated population trends of 58 bird species using open-population N-mixture models based on count data in two localities in southeastern Spain, which have been collected according to a citizen science monitoring program (SACRE, Monitoring Common Breeding Birds in Spain) over 21 and 15 years, respectively. We performed different abundance models for each species and study area, accounting for imperfect detection of individuals in replicated counts. After selecting the best models for each species and study area, empirical Bayes methods were used for estimating abundances, which allowed us to calculate population growth rates ( λ ) and finally population trends. We also compared the two local population trends and related them with national and European trends, and species functional traits (phenological status, dietary, and habitat specialization characteristics). Our results showed increasing trends for most species, but a weak correlation between populations of the same species from both study areas. In general, local population trends were consistent with the trends observed at national and continental scales, although contrasting patterns exist for several species, mainly with increasing local trends and decreasing Spanish and European trends. Moreover, we found no evidence of a relationship between population trends and species traits. We conclude that using open-population N-mixture models is an appropriate method to estimate population trends, and that citizen science-based monitoring schemes can be a source of data for such analyses. This modeling approach can help managers to assess the effectiveness of their actions at the local level in the context of global change.

Journal of Ornithology

Transient triggering of near and distant earthquakes

We demonstrate qualitatively that frictional instability theory provides a context for understanding how earthquakes may be triggered by transient loads associated with seismic waves from near and distance earthquakes. We assume that earthquake triggering is a stick-slip process and test two hypotheses about the effect of transients on the timing of instabilities using a simple spring-slider model and a rate- and state-dependent friction constitutive law. A critical triggering threshold is implicit in such a model formulation.

Bulletin of the Seismological Society of America

Long-term aridity shapes grassland drought resistance and modulates the roles of plant diversity and functional composition

Understanding the drivers of plant community stability is crucial for predicting ecosystem responses to extreme drought events. In grasslands, drought resistance supports the maintenance of key functions such as above-ground primary productivity, making the identification of resistance drivers essential to guide management under climate change. Proposed factors contributing to grassland stability include multiple diversity facets, functional traits and long-term climate, but most assessments focus on temporal invariability under historical disturbance regimes, leaving mechanisms of extreme drought resistance and their variation across climatic contexts relatively underexplored. Here, we analysed data from 54 grassland sites of the International Drought Experiment to examine the resistance of above-ground net primary productivity to a short-term (i.e. 1 year) extreme drought. We investigated the relative importance and joint influence of functional composition (i.e. community-weighted means of leaf and root traits), plant diversity facets (taxonomic, functional and phylogenetic) and climate (aridity and rainfall variability) on drought resistance. We used structural equation models to disentangle direct, indirect, and moderating pathways linking these drivers to drought resistance. Long-term aridity appeared as one of the most important drivers of grassland resistance to drought, with more arid sites showing lower resistance. Moreover, aridity impacted resistance through indirect effects by shaping functional composition and plant diversity, and by moderating the influence of plant diversity and functional composition. Functional composition related to dehydration avoidance and dehydration tolerance was also positively associated with resistance, while diversity had a weaker relationship with resistance, mostly through functional and phylogenetic facets. Interannual rainfall variability also influenced resistance, with different effects in more arid versus humid and less arid sites. Synthesis . Widely studied stability drivers such as plant diversity and functional composition have only partial explanatory power for short-term drought resistance of above-ground productivity in grasslands at a global scale. The abiotic context, particularly long-term aridity, is crucial for understanding ecosystem responses to rainfall variation and can improve predictive models for advancing the study of ecosystem resistance to drought. Along with management practices that target high species diversity or specific traits, restoration and conservation practices should support vulnerable sites experiencing high aridity

Journal of Ecology

The role of historical fire disturbance in the carbon dynamics of the pan-boreal region: A process-based analysis

[1] Wildfire is a common occurrence in ecosystems of northern high latitudes, and changes in the fire regime of this region have consequences for carbon feedbacks to the climate system. To improve our understanding of how wildfire influences carbon dynamics of this region, we used the process-based Terrestrial Ecosystem Model to simulate fire emissions and changes in carbon storage north of 45°N from the start of spatially explicit historically recorded fire records in the twentieth century through 2002, and evaluated the role of fire in the carbon dynamics of the region within the context of ecosystem responses to changes in atmospheric CO 2 concentration and climate. Our analysis indicates that fire plays an important role in interannual and decadal scale variation of source/sink relationships of northern terrestrial ecosystems and also suggests that atmospheric CO 2 may be important to consider in addition to changes in climate and fire disturbance. There are substantial uncertainties in the effects of fire on carbon storage in our simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. To improve the ability to better predict how fire will influence carbon storage of this region in the future, new analyses of the retrospective role of fire in the carbon dynamics of northern high latitudes should address these uncertainties.

Journal of Geophysical Research G: Biogeosciences

Hybrid broadband ground-motion simulation validation of small magnitude active shallow crustal earthquakes in New Zealand

This article presents a comprehensive validation of the hybrid broadband ground-motion simulation approach (via the commonly used Graves and Pitarka method) in a New Zealand context with small magnitude point source ruptures using an extensive set of 5218 ground motions recorded at 212 sites from 479 active shallow crustal earthquakes across the country. Modifications to the simulation method inferred from a previous New Zealand validation are implemented, and the improvements are explicitly quantified. Empirical ground-motion models are also considered to provide a benchmark for simulation prediction accuracy and precision. Examination of intensity measure residuals identifies that the simulation method modifications lead to reduced model prediction bias and within-event variability and provides evidence toward the use of spatially varying coefficient models for simulation parameters, such as the high-frequency Brune stress parameter. Additional biases identified include, among others, underprediction of significant durations at soft soil sites and overprediction of short-period pseudo-spectral accelerations at stiff alluvial gravel and rock sites due to low-estimated 30 m time-averaged shear-wave velocity values.

Earthquake Spectra

Calculation of broadband time histories of ground motion, Part II: Kinematic and dynamic modeling using theoretical Green's functions and comparison with the 1994 northridge earthquake

In the evolution of methods for calculating synthetic time histories of ground motion for postulated earthquakes, kinematic source models have dominated to date because of their ease of application. Dynamic models, however, which incorporate a physical relationship between important faulting parameters of stress drop, slip, rupture velocity, and rise time, are becoming more accessible. This article compares a class of kinematic models based on the summation of a fractal distribution of subevent sizes with a dynamic model based on the slip-weakening friction law. Kinematic modeling is done for the frequency band 0.2 to 10.0. Hz, dynamic models are calculated from 0.2 to 2.0. Hz. The strong motion data set for the 1994 Northridge earthquake is used to evaluate and compare the synthetic time histories. Source models are propagated to the far field by convolution with 1D and 3D theoretical Green&rsquo;s functions. In addition, the kinematic model is used to evaluate the importance of propagation path effects: velocity structure, scattering, and nonlinearity. At present, the kinematic model gives a better broadband fit to the Northridge ground motion than the simple slip-weakening dynamic model. In general, the dynamic model overpredicts rise times and produces insufficient shorter-period energy. Within the context of the slip-weakening model, the Northridge ground motion requires a short slip-weakening distance, on the order of 0.15 m or less. A more complex dynamic model including rate weakening or one that allows shorter rise times near the hypocenter may fit the data better.

Bulletin of the Seismological Society of America

Site occupancy models with heterogeneous detection probabilities

Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these ?site occupancy? models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link (2003, Biometrics 59, 1123?1130) demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.

Biometrics

Cape Romain partnership for coastal protection

This final report summarizes activities, outcomes, and lessons learned from a 3-year project titled “Climate Change Adaptation for Coastal National Wildlife Refuges” with the Cape Romain National Wildlife Refuge (NWR) and local partners in the surrounding South Carolina Lowcountry. The Lowcountry is classified as the 10-county area encompassing the coastal plain of South Carolina (this report specifically focuses on Berkeley, Charleston, and Georgetown Counties). The goals of this work, sponsored by the U.S. Geological Survey’s Southeast Climate Adaptation Science Center (SECASC), were to foster active engagement with stakeholders; to develop a comprehensive definition of adaptation problems faced by agencies, organizations, and individuals near the Cape Romain NWR that accounts for global change, local values, knowledge and perceptions; and to encourage social learning and building of effective networks and trust across South Carolina Lowcountry organizations and individuals. Although project scoping began at the scale of the Atlantic seaboard, by engaging with NWRs from Massachusetts to Florida, participating refuge personnel eventually selected the Cape Romain NWR to serve as a case study for testing our goals. The Cape Romain Partnership for Coastal Conservation was established to address global change impacts at a regional level and includes representation from Federal and State resource agencies, local conservation nongovernmental organizations, and organizations representing underserved community interests. Research topics, originating from discussions with Cape Romain Partnership for Coastal Conservation members, focused on quantifying key drivers of change including localized sea-level rise (SLR) predictions, estimates of coastal hurricane inundation as amplified by SLR, and urban growth trends and forecasts. These key drivers provided a foundation to engage stakeholders in planning exercises to begin a process of collective understanding and collaborative decision making. The goal of this process was to develop collective strategies of adaptation to enhance community and ecosystem resilience in the South Carolina Lowcountry. South Carolina’s Lowcountry is experiencing rapid environmental and social transformation because of SLR rates approaching twice the global average, chronic tidal flooding and catastrophic storm surges, erosion and loss of habitats that provide essential services to wildlife and humans, and increasing social polarization fueled by aggressive low-density urban growth and other forms of land conversion. To support characterizations of plausible future scenarios, we used available or, in some cases, developed new models to project future conditions of key environmental and social-economic drivers. Because of the imprecision of mean global SLR projections, the SECASC commissioned a climatological study to account for local conditions and multiple representative concentration pathways to project a tailored distribution of future sea levels. These projections were matched to SLR scenarios provided by existing models to anticipate the range of future coastal habitat changes in the South Carolina Lowcountry. SLR scenarios were also incorporated into existing storm-surge models, which do not account for alternate baseline sea levels, to project the local effects of future hurricanes. To evaluate the extent and effects of population growth and urban expansion, we relied on an existing urban-growth model to map the spatial distribution of land-conversion probabilities, the total area of which is predicted to increase twofold to threefold over the next 60 years. In addition to this simplified model, an econometric model is in development to account for nonlinear feedback dynamics in land value, land use, and ecosystem service production. Although not yet completed, the goals of this model are to produce more-detailed projections of growth dynamics and to allow predictions of development patterns resulting from alternate land-use planning policies and incentives. Collaborative planning for an uncertain future requires more than providing decision makers with information on future physical and ecological conditions; developing effective and consensual strategies must also integrate sociological values, multiple cultural perspectives, and an understanding of human behavior. To support broad stakeholder engagement in integrative approaches to adaptation planning, emphasis was placed on the importance of considering differences in how individuals perceive their environment and create meaning. Because cultural frameworks form the basis for perceptions and, ultimately, the behaviors of individuals and institutions, we describe a model of human behavior and how it can be used to understand the effect of cultural complexity and variation in perception on choices, behavioral change, and long-term maintenance of behaviors. We consider a model commonly used in the field of behavioral health that accommodates variation in human perception when describing stages of behavior and the dynamics of behavioral change. Tailoring communication and engagement activities to targeted stakeholders is likely to benefit from increased understanding of behavioral change processes. The complex nature of this problem limited the usefulness of a traditional decision-analytic approach, we explored alternative methods for engagement, collaborative learning and decision making. Recognizing that project partners and Lowcountry stakeholders may be at different stages of preparedness and interest level for modifying behavior as a function of global change, we facilitated a scenario-planning exercise to familiarize partners with this well-established approach for communicating the opportunities and threats arising under alternative, plausible futures. We developed narratives for four alternative South Carolina Lowcountry scenarios to be used in later strategic planning that focus on quantitative trends for three primary drivers with high impact and high uncertainty: manifestations of climate change, social-political shifts at a global level, and forces of local value and power structures. This scenario-planning exercise underscored the complex relation between the temporospatial scale of the production of ecological goods and services and the institutional scale at which they are managed. We then guided the partners through an assessment of the relevant strengths and weaknesses of the Cape Romain Partnership for Coastal Protection, using the threats and opportunities characterized by each scenario to understand how the partnership might respond when attempting to meet conservation and societal objectives. The partnership identified key strengths including partnership experience, outreach and technical capacities, a substantial conservation land base, and high social cohesion in the South Carolina Lowcountry. Limited communication expertise, institutional inertia, and insufficient staffing and funding were recognized as important weaknesses across the partnership. By examining and scoring combinations of internal strengths and weaknesses and external threats and opportunities, the partnership developed sets of prioritized strategies to consider in the context of a given scenario. Although we had insufficient time to examine all scenarios in detail, the intent was to identify a portfolio of strategic actions to address threats and opportunities represented in multiple plausible futures. Top-ranking strategies encompassed a range of actions that focused on strengthening the conservation community and communicating the benefits of nature (that is, ecosystem services) to leveraging partnerships to expand land protection. This report also details the methods and preliminary results of several models developed or applied in support of this project. Two parcel-selection algorithms were used to evaluate anticipated habitat changes and patterns of urban growth to guide decisions on optimal conservation reserve design to protect habitat communities. One approach used a widely available planning software (MARXAN) to maximize conservation benefits near the Cape Romain NWR, whereas the other approach was a novel application of economic theory to account for uncertainty in future conditions and for the risks of unanticipated habitat loss. This latter model applies modern portfolio theory to estimate the risk of investing in any portfolio of land parcels (that is, candidate “reserves”) under climate-change uncertainty by quantifying the variation and spatial correlation of conservation benefits derived from each portfolio. We expanded the range of actions beyond simply whether or not to invest in a set of land parcels, an approach commonly used in spatial conservation planning, to also include consideration of divestment from currently protected lands. Such refinements allow for better accounting of system dynamics and can evaluate the benefits of flexible conservation tools such as rolling easements. Model results were conditional on a decision maker’s risk tolerance but highlighted general strategies of land conservation to increase future habitat representation beyond what is expected under the current protected land base. We built models that may help inform coastal planning by estimating salinity dynamics and the performance of oyster reef restoration efforts to predict the combined effects of global change and management of freshwater flows on coastal habitats and the processes that contribute to their resilience. These models can support restoration decisions by evaluating the expected benefits of site locations for shoreline protection and fisheries production. Lastly, we developed a spatially explicit economic model that predicts feedback dynamics among land value, land-use change, and effects on ecosystem service provision to explore zoning policies and incentives on urban growth and ecosystem services. We summarize these efforts with insights and considerations for the Cape Romain Partnership for Coastal Protection to continue to engage stakeholders in effective adaptation planning. First, notions of place attachment (referred to as sense of place), and the role of culture in social discourse are increasingly being used to understand the complex interactions between society and the environment and how societies respond and adapt to climate change. Sense of place was a unifying theme whenever the future of the South Carolina Lowcountry was discussed. The contribution of the South Carolina Lowcountry’s environmental wealth, rich cultural heritage, and quality of life to sense of place has important implications for how adaptation planning might best be pursued. More community-based governance of the commons (in other words, natural and cultural resources held in common), in which broad stakeholder participation and power sharing are key elements, is considered important. This devolution of governance is characterized by polycentric institutions and self-organizing social networks that promote a local culture of knowledge sharing, problem solving, and learning. These so-called bridging organizations (or individuals) often provide the leadership necessary to bring together potentially disparate Government agencies and institutions, private organizations, and individuals in a collective process of problem solving. Our observations also suggest that the conservation community in the South Carolina Lowcountry views its activities as integral to the broader governance of social-ecological systems, in which responses to the forces of global change are mediated through culture, economics, and politics. Rather than directly competing with other interests, the South Carolina Lowcountry conservation community seems to embrace an interpretation of conservation in which the fundamental objective is the quality of human life rather than environmental protection. Fundamental to the types of governance reforms described above is the notion of coproduction, in which experts and users collaborate to develop a shared body of knowledge. In this approach, scientists work with stakeholders to help frame questions, design research, and collect and analyze data. Such sustained collaborations are increasingly believed to be an effective way to produce useable (or actionable) science. The emphasis on social learning, leveraging strong social networks, coordinating and deliberating among diverse stakeholders, and applying principles of adaptive management is an essential contribution to adaptive capacity. The diverse and robust set of scientific approaches, methods to help stakeholders collaborate in effective and goal-driven planning processes, and decision tools resulting from this project hopefully will assist Cape Romain NWR and its partners prepare for climatic, ecological, and social changes over the coming decades.

South Carolina

Use of Numerical Models to Simulate Transport of Sewage-Derived Nitrate in a Coastal Aquifer, Central and Western Cape Cod, Massachusetts

The unconsolidated glacial sediments underlying Cape Cod, Massachusetts compose a regional aquifer system that is used both as a source of drinking water and as a disposal site for wastewater; in addition, the discharge of clean ground water from the aquifer system is needed for the maintenance of freshwater and marine ecosystems throughout the region. Because these uses of the aquifer conflict with one another in many areas of the Cape, local and regional planners have begun to develop sustainable wastewater plans that will facilitate the disposal of wastewater while protecting water supplies and improving the health of aquatic ecosystems. To assist local and regional planners in these efforts, the U.S. Geological Survey conducted a 2-year investigation to (1) assist local and regional planners in the evaluation of potential wastewater scenarios, (2) use results and interpretation from these analyses to develop hydrologic concepts transferable throughout the region, and (3) establish and test methods that would be of use in future evaluations. Wastewater-disposal scenarios need to be evaluated in the context of the regional ground-water-flow system. For a given rate of disposal, wastewater from sites at or near a regional ground-water divide is transported in a wider arc of flow directions, flows deeper in the system, and contaminates a larger part of the aquifer than does wastewater discharged from sites farther from the divide. Also, traveltimes of wastewater from sites near a ground-water divide to receptors are longer (as much as several hundred years) than traveltimes from sites farther from the divide. Thus, wastewater disposal at or near a divide will affect a larger part of the aquifer and likely contribute wastewater to more receptors than wastewater disposal farther from a divide; however, longer traveltimes could allow for more attenuation of wastewater-derived nitrate from those sites. Ground-water-flow models and particle tracking can be used to identify advective-transport patterns downgradient from wastewater-disposal sites and estimate traveltimes; however, these tools cannot predict the distribution of mass or concentrations of wastewater constituents, such as nitrate, in the aquifer. Flow-based particle-tracking analyses can be used to estimate mass-loading rates and time-varying concentrations at wells and ecological receptors by the accounting of mass-weighted particles discharging into the receptor of interest. This method requires no additional development beyond the flow model; however, post-modeling analyses are required. In addition, the method is based on the assumption that no mass is lost during transport, an assumption that likely is not valid in many systems. Solute-transport models simulate the subsurface transport of nitrate through the aquifer and predict the distribution of the mass of a solute in the aquifer at different transport times. This method does require additional model development beyond the flow model, but can predict timevarying concentrations at receptors. Estimates of mass-loading rates require minimal post-modeling analyses. Time-varying concentrations and mass-loading rates calculated for wells in eastern Barnstable by the two methods generally were in reasonable agreement. Inherent in the flow-based particle-tracking method is the assumption that mass is conserved along a given flow line and that there is no spreading of mass in the aquifer. Although the solute-transport models also incorporate a system-wide conservation of mass, these models allow for a spreading of mass in the aquifer, and mass is not conserved along a given flow line. As a result, estimates of concentrations and mass loading rates generally were higher in particle-tracking analyses than in solute-transport simulations. Results from the two types of simulations agreed best for wells that receive large amounts of wastewater with short traveltimes (less than 10 years) because insufficient transport

Scientific Investigations Report