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Building resilience in dryland ecosystems: A climate adaptation strategy menu for pinyon–juniper woodlands
Pinyon–juniper (PJ) woodlands, one of the most extensive mature and old-growth woodland types in the Western United States, provide critical ecological, cultural, and economic benefits but face increasing threats from climate change, altered disturbance regimes, invasive species, and pests. We developed the PJ Woodland Climate Adaptation Management Menu, a decision support tool designed to guide adaptive, climate-informed management of PJ ecosystems, particularly within the Colorado Plateau ecoregion. The menu was created through an iterative, collaborative process involving literature review, integration of strategies from existing adaptation frameworks, and extensive input from scientists, land managers, and community partners during workshops and focus groups. The menu links specific, evidence-based approaches to each of six broad strategies, including soliciting community input, mitigating disturbance, enhancing and maintaining biodiversity, conserving ecotones, timing actions for optimal outcomes, and accepting climate-driven changes when appropriate. It is intended for use with the Adaptation Workbook to help managers connect local goals and climate vulnerabilities to tailored management tactics. Hypothetical scenarios demonstrate the menu’s application to contrasting PJ woodland conditions, from die-off events to old-growth maintenance. Lessons learned during development underscore the value of early stakeholder engagement, cross-sector collaboration, and balancing diverse ecological objectives. This menu offers a flexible, transferable framework to strengthen climate resilience in PJ woodlands and serves as a model that could improve adaptation planning in other dryland forest ecosystems.
Spatio-temporal ecological models via physics-informed neural networks for studying chronic wasting disease
To mitigate the negative effects of emerging wildlife diseases in biodiversity and public health it is critical to accurately forecast pathogen dissemination while incorporating relevant spatio-temporal covariates. Forecasting spatio-temporal processes can often be improved by incorporating scientific knowledge about the dynamics of the process using physical models. Ecological diffusion equations are often used to model epidemiological processes of wildlife diseases where environmental factors play a role in disease spread. Physics-informed neural networks (PINN) are deep learning algorithms that constrain neural network predictions based on physical laws and therefore are powerful forecasting models useful even in cases of limited and imperfect training data. In this paper, we develop a novel ecological modeling tool using PINNs, which fits a feedforward neural network and simultaneously performs parameter identification in a partial differential equation (PDE) with varying coefficients. We demonstrate the applicability of our model by comparing it with the commonly used Bayesian stochastic partial differential equation method and traditional machine learning approaches, showing that our proposed model exhibits superior prediction and forecasting performance when modeling chronic wasting disease in deer in Wisconsin. Furthermore, our model provides the opportunity to obtain scientific insights into spatiotemporal covariates affecting spread and growth of diseases. This work contributes to future machine learning and statistical methodology development by studying spatio-temporal processes enhanced by prior physical knowledge.
Effects of increased soil nitrogen on the dominance of alien annual plants in the Mojave Desert
1. Deserts are one of the least invaded ecosystems by plants, possibly due to naturally low levels of soil nitrogen. Increased levels of soil nitrogen caused by atmospheric nitrogen deposition may increase the dominance of invasive alien plants and decrease the diversity of plant communities in desert regions, as it has in other ecosystems. Deserts should be particularly susceptible to even small increases in soil nitrogen levels because the ratio of increased nitrogen to plant biomass is higher compared with most other ecosystems. 2. The hypothesis that increased soil nitrogen will lead to increased dominance by alien plants and decreased plant species diversity was tested in field experiments using nitrogen additions at three sites in the in the Mojave Desert of western North America. 3. Responses of alien and native annual plants to soil nitrogen additions were measured in terms of density, biomass and species richness. Effects of nitrogen additions were evaluated during 2 years of contrasting rainfall and annual plant productivity. The rate of nitrogen addition was similar to published rates of atmospheric nitrogen deposition in urban areas adjacent to the Mojave Desert (3·2 g N m −2 year −1 ). The dominant alien species included the grasses Bromus madritensis ssp. rubens and Schismus spp. ( S. arabicus and S. barbatus ) and the forb Erodium cicutarium . 4. Soil nitrogen addition increased the density and biomass of alien annual plants during both years, but decreased density, biomass and species richness of native species only during the year of highest annual plant productivity. The negative response of natives may have been due to increased competitive stress for soil water and other nutrients caused by the increased productivity of aliens. 5. The effects of nitrogen additions were significant at both ends of a natural nutrient gradient, beneath creosote bush Larrea tridentata canopies and in the interspaces between them, although responses varied among individual alien species. The positive effects of nitrogen addition were highest in the beneath-canopy for B. rubens and in interspaces for Schismus spp. and E. cicutarium . 6. The results indicated that increased levels of soil nitrogen from atmospheric nitrogen deposition or from other sources could increase the dominance of alien annual plants and possibly promote the invasion of new species in desert regions. Increased dominance by alien annuals may decrease the diversity of native annual plants, and increased biomass of alien annual grasses may also increase the frequency of fire. 7. Although nitrogen deposition cannot be controlled by local land managers, the managers need to understand its potential effects on plant communities and ecosystem properties, in particular how these effects may interact with land-use activities that can be managed at the local scale. These interactions are currently unknown, and hinder the ability of managers to make appropriate land-use decisions related to nitrogen deposition in desert ecosystems. 8. Synthesis and applications. The effects of nitrogen deposition on invasive alien plants should be considered when deciding where to locate new conservation areas, and in evaluating the full scope of ecological effects of new projects that would increase nitrogen deposition rates.
Assessment and monitoring of recreation impacts and resource conditions on mountain summits: Examples from the Northern Forest, USA
Mountain summits present a unique challenge to manage sustainably: they are ecologically important and, in many circumstances, under high demand for recreation and tourism activities. This article presents recent advances in the assessment of resource conditions and visitor disturbance in mountain summit environments, by drawing on examples from a multiyear, interdisciplinary study of summits in the northeastern United States. Primary impact issues as a consequence of visitor use, such as informal trail formation, vegetation disturbance, and soil loss, were addressed via the adaption of protocols from recreation ecology studies to summit environments. In addition, new methodologies were developed that provide measurement sensitivity to change previously unavailable through standard recreation monitoring protocols. Although currently limited in application to the northeastern US summit environments, the methods presented show promise for widespread application wherever summits are in demand for visitor activities.
Visualizing the ecological importance of pre-Euro-American settlement fire across three Midwestern landscapes
Bearing-tree data were used to calculate an index, pyrophilic percentage, depicting the importance of fire before Euro-American settlement on three landscapes, two within the Prairie Peninsula and one outside the region. Based on functional traits, bearing trees were classified as either pyrophilic or pyrophobic, applied to Public Land Survey points, and the pyrophilic percentage was calculated for each point. Kriging was applied to this point database to create a continuous surface of pyrophilic percentages. Regression analysis was used to relate this surface to environmental factors. Regression models created separately for each study area explained 38 to 53% of the variation in pyrophilic percentage. A positive association between pyrophilic percentage and distance to water and summer potential evapotranspiration was consistent across all study sites. The consistently high values and spatial patterns of pyrophilic percentage revealed fire-dominated landscapes interspersed with patches of pyrophobic vegetation. The restriction of pyrophobic areas to the leeside (east) of waterbodies indicated these served as firebreaks in a fire-swept landscape. Lake Michigan must have had a profound effect on pre- Euro-American settlement fire environments, serving as a massive physical firebreak while casting a moist maritime climate eastward. In southern and southwestern Illinois, the Mississippi River and associated tributaries along with an increase in topographic complexity also served as firebreaks, with pyrophobic forests restricted to riparian zones which progressively graded to pyrophilic vegetation on surrounding uplands. Our analysis expands the use of Public Land Survey data by converting bearing trees into a meaningful fire ecology index. While much of the landscape included in our study area is now in agriculture or urbanized, pyrophilic percentage maps can help guide land managers in the application of fire for restoration, conservation, and forestry purposes.
A framework for ecological decision support systems: Building the right systems and building the systems right
Workshops in the late 1990's launched the commitment of the U.S. Geological Survey's Biological Resources Division (BRD) to develop and implement decision support systems (DSS) applications. One of the primary goals of this framework document is to provide sufficient background and information for Department of the Interior (DOI) bureau stakeholders and other clients to determine the potential for DSS development. Such an understanding can assist them in carrying out effective land planning and management practices. This document provides a definition of DSS and its characteristics and capabilities. It proceeds to describe issues related to meeting resource managers needs, such as the needs for specific applications, customer requirements, information and technology transfer, user support, and institutionalization. Using the decision process as a means to guide DSS development and determine users needs is also discussed. We conclude with information on method to evaluate DSS development efforts and recommended procedures for verification and validation.
Adaptation strategies and approaches for managing fire in a changing climate
As the effects of climate change accumulate and intensify, resource managers juggle existing goals and new mandates to operationalize adaptation. Fire managers contend with the direct effects of climate change on resources in addition to climate-induced disruptions to fire regimes and subsequent ecosystem effects. In systems stressed by warming and drying, increased fire activity amplifies the pace of change and scale of severe disturbance events, heightening the urgency for management action. Fire managers are asked to integrate information on climate impacts with their professional expertise to determine how to achieve management objectives in a changing climate with altered fire regimes. This is a difficult task, and managers need support as they incorporate climate adaptation into planning and operations. We present a list of adaptation strategies and approaches specific to fire and climate based on co-produced knowledge from a science–management partnership and pilot-tested in a two-day workshop with natural resource managers and regional stakeholders. This “menu” is a flexible and useful tool for fire managers who need to connect the dots between fire ecology, climate science, adaptation intent, and management implementation. It was created and tested as part of an adaptation framework used widely across the United States and should be applicable and useful in many fire-prone forest ecosystems.
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
An updated genetic marker for detection of Lake Sinai Virus and metagenetic applications
Background Lake Sinai Viruses (LSV) are common RNA viruses of honey bees ( Apis mellifera ) that frequently reach high abundance but are not linked to overt disease. LSVs are genetically heterogeneous and collectively widespread, but despite frequent detection in surveys, the ecological and geographic factors structuring their distribution in A. mellifera are not understood. Even less is known about their distribution in other species. Better understanding of LSV prevalence and ecology have been hampered by high sequence diversity within the LSV clade. Methods Here we report a new polymerase chain reaction (PCR) assay that is compatible with currently known lineages with minimal primer degeneracy, producing an expected 365 bp amplicon suitable for end-point PCR and metagenetic sequencing. Using the Illumina MiSeq platform, we performed pilot metagenetic assessments of three sample sets, each representing a distinct variable that might structure LSV diversity (geography, tissue, and species). Results The first sample set in our pilot assessment compared cDNA pools from managed A. mellifera hives in California ( n = 8) and Maryland ( n = 6) that had previously been evaluated for LSV2, confirming that the primers co-amplify divergent lineages in real-world samples. The second sample set included cDNA pools derived from different tissues (thorax vs. abdomen, n = 24 paired samples), collected from managed A. mellifera hives in North Dakota. End-point detection of LSV frequently differed between the two tissue types; LSV metagenetic composition was similar in one pair of sequenced samples but divergent in a second pair. Overall, LSV1 and intermediate lineages were common in these samples whereas variants clustering with LSV2 were rare. The third sample set included cDNA from individual pollinator specimens collected from diverse landscapes in the vicinity of Lincoln, Nebraska. We detected LSV in the bee Halictus ligatus (four of 63 specimens tested, 6.3%) at a similar rate as A. mellifera (nine of 115 specimens, 7.8%), but only one H. ligatus sequencing library yielded sufficient data for compositional analysis. Sequenced samples often contained multiple divergent LSV lineages, including individual specimens. While these studies were exploratory rather than statistically powerful tests of hypotheses, they illustrate the utility of high-throughput sequencing for understanding LSV transmission within and among species.
An integrated path for spatial capture–recapture and animal movement modeling
Ecologists and conservation biologists increasingly rely on spatial capture–recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.
Estimating density and detection of bobcats in fragmented Midwestern landscapes using spatial capture-recapture data from camera traps
Camera-trapping data analyzed with spatially explicit capture–recapture (SCR) models can provide a rigorous method for estimating density of small populations of elusive carnivore species. We sought to develop and evaluate the efficacy of SCR models for estimating density of a presumed low-density bobcat ( Lynx rufus ) population in fragmented landscapes of west-central Illinois, USA. We analyzed camera-trapping data from 49 camera stations in a 1,458-km 2 area deployed over a 77-day period from 1 February to 18 April 2017. Mean operational time of cameras was 52 days (range = 32–67 days). We captured 23 uniquely identifiable bobcats 113 times and recaptured these same individuals 90 times; 15 of 23 (65.2%) individuals were recaptured at ≥2 camera traps. Total number of bobcat capture events was 139, of which 26 (18.7%) were discarded from analyses because of poor image quality or capture of only a part of an animal in photographs. Of 113 capture events used in analyses, 106 (93.8%) and 7 (6.2%) were classified as positive and tentative identifications, respectively; agreement on tentative identifications of bobcats was high (71.4%) among 3 observers. We photographed bobcats at 36 of 49 (73.5%) camera stations, of which 34 stations were used in analyses. We estimated bobcat density at 1.40 individuals (range = 1.00–2.02)/100 km 2 . Our modeled bobcat density estimates are considerably below previously reported densities (30.5 individuals/100 km 2 ) within the state, and among the lowest yet recorded for the species. Nevertheless, use of remote cameras and SCR models was a viable technique for reliably estimating bobcat density across west-central Illinois. Our research establishes ecological benchmarks for understanding potential effects of colonization, habitat fragmentation, and exploitation on future assessments of bobcat density using standardized methodologies that can be compared directly over time. Further application of SCR models that quantify specific costs of animal movements (i.e., least-cost path models) while accounting for landscape connectivity has great utility and relevance for conservation and management of bobcat populations across fragmented Midwestern landscapes.
Near-term spatial hydrologic forecasting in Everglades, USA for landscape planning and ecological forecasting
Operational ecological forecasting is an emerging field that leverages ecological models in a new, cross-disciplinary way – using a real-time or nearly real-time climate forecast to project near-term ecosystem states. These applications give decision-makers lead time to anticipate and manage state changes that degrade ecosystem functions or directly impact humans. The Everglades Forecasting model (EverForecast) is an operational forecast model designed specifically for conservation management purposes including water management. It provides up to six-month forecasts of daily projected, spatially continuous stage values across the Everglades. We validated EverForecast quarterly to measured historical values at 207 gages (1 Jan 2000 – 31 Dec 2019). EverForecast hindcasted water stage accurately captured measured stage variation, with a low percentage of measured stage exceeding hindcasted values. Over the whole spatial extent, the mean RMSE is 20.98 cm, the mean MAE is 14.42 cm, and the mean MBE is 0.91 cm.
Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective
Detailed bathymetric maps of the sea floor in Long Island Sound are of great interest to the Connecticut and New York research and management communities because of this estuary's ecological, recreational, and commercial importance. The completed, geologically interpreted digital terrain models (DTMs), ranging in area from 12 to 293 square kilometers, provide important benthic environmental information, yet many applications require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 12 multibeam and 2 LIDAR (Light Detection and Ranging) contiguous bathymetric DTMs, produced by the National Oceanic and Atmospheric Administration during charting operations, into one dataset that covers much of eastern Long Island Sound and extends into westernmost Block Island Sound. The new dataset is adjusted to mean lower low water, is gridded to 4-meter resolution, and is provided in UTM Zone 18 NAD83 and geographic WGS84 projections. This resolution is adequate for sea floor-feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the grid include exposed bedrock outcrops, boulder lag deposits of submerged moraines, sand-wave fields, and scour depressions that reflect the strength of the oscillating and asymmetric tidal currents. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic artifacts visible in the bathymetric data include a dredged channel, shipwrecks, dredge spoils, mooring anchors, prop-scour depressions, buried cables, and bridge footings. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities in this major east-coast estuary.
Using passive integrated transponder (PIT) tags to monitor and research bats: Applications, benefits, and limitations
Worldwide declines of bat populations underscore the value of developing and refining survey tools to assess and monitor population statuses and dynamics. Passive integrated transponder (PIT) tags can be an effective marking technique, facilitating the monitoring of individual bats at roost sites by using radio frequency (RFID) readers and antennas. We detail 5 ongoing studies, discuss the rationale for our study designs, and offer recommendations for monitoring and researching bats with PIT tags that are broadly applicable across species and locations. Using data from RFID readers, we show how population parameters can be precisely estimated across space and time, while improving our understanding of bat ecology and vulnerability to threats. We discuss PIT-tag loss as a potential limitation that varies across species, sex, and season, present minimum loss rates from 2 studies, and describe consequences and techniques to ameliorate this issue. Overall, integrating PIT tags with autonomous RFID readers and antennas provides a powerful survey method for monitoring, researching, and conserving bat populations.
Movement ecology
(Yackulic) At first glance, the decision to study movement in Galapagos tortoises seems curious. Given the slow speed of tortoises and tendency to forage and rest as they move, it seems implausible that tortoises would string their slow bursts of activity together to accomplish large-scale movements. Nonetheless, as early as 1815 (Porter 1815), visitors to Galapagos have noted the propensity for tortoises to walk long distances along well used trails, leading to seasonal changes in the distribution of tortoises on the various islands of the Archipelago. In recent years, advances in the technology used to track animals have led to a better understanding of movement and the diversity of movement strategies among many animal taxa. This chapter focuses on the application of these technologies to study of movement in Galapagos tortoises. Recent work has shown not only the diversity of movement strategies employed by Galapagos tortoises, but also illustrated how movement can both cause and be a consequence of interaction between reproductive and foraging ecologies of tortoises and the presence of strong environmental gradients. Understanding how critical unimpeded movement is to the persistence of Galapagos tortoises also informs efforts to maintain connectivity to, and suitable habitat within, tortoise range outside of protected areas.
Linking multi-temporal satellite imagery to coastal wetland dynamics and bird distribution
Ecosystems are characterized by dynamic ecological processes, such as flooding and fires, but spatial models are often limited to a single measurement in time. The characterization of direct, fine-scale processes affecting animals is potentially valuable for management applications, but these are difficult to quantify over broad extents. Direct predictors are also expected to improve transferability of models beyond the area of study. Here, we investigated the ability of non-static and multi-temporal habitat characteristics to predict marsh bird distributions, while testing model generality and transferability between two coastal habitats. Distribution models were developed for king rail ( Rallus elegans ), common gallinule ( Gallinula galeata ), least bittern ( Ixobrychus exilis ), and purple gallinule ( Porphyrio martinica ) in fresh and intermediate marsh types in the northern Gulf Coast of Louisiana and Texas, USA. For model development, repeated point count surveys of marsh birds were conducted from 2009 to 2011. Landsat satellite imagery was used to quantify both annual conditions and cumulative, multi-temporal habitat characteristics. We used multivariate adaptive regression splines to quantify bird-habitat relationships for fresh, intermediate, and combined marsh habitats. Multi-temporal habitat characteristics ranked as more important than single-date characteristics, as temporary water was most influential in six of eight models. Predictive power was greater for marsh type-specific models compared to general models and model transferability was poor. Birds in fresh marsh selected for annual habitat characterizations, while birds in intermediate marsh selected for cumulative wetness and heterogeneity. Our findings emphasize that dynamic ecological processes can affect species distribution and species-habitat relationships may differ with dominant landscape characteristics.
Simulating the impact of human land use change on forest composition in the Great Plains agroecosystems with the Seedscape model
The expansion and contraction of marginal cropland in the Great Plains often involves small forested strips of land that provide important ecological benefits. The effect of human disturbance on these forests is not well known. Because of their unique structure such forests are not well-represented by forest gap models. In this paper, the development, testing and application of a new model known as Seedscape are described. Seedscape is a modification of the JABOWA-II model, and it uses a spatially-explicit landscape to resolve small-scale features of highly fragmented forests in the eastern Great Plains. It was tested and evaluated with observations from two sites, one in Nebraska and a second in eastern Iowa. Seedscape realistically simulates succession at the Nebraska site, but is less successful at the Iowa site. Seedscape was also applied to the Nebraska site to simulate the effect that varying forest corridor widths, in response to the presumed expansion/contraction of adjacent agricultural land, has on succession properties. Results suggest that small differences in widths have negligible effects on forest composition, but large differences in widths may cause statistically-significant changes in the relative importance of some species. We assert that long-term ecological change in human dominated landscapes is not well understood, in part, because of inadequate modeling techniques. Seedscape provides a much-needed tool for assessing the ecological implications of land use change in forests of predominately agricultural landscapes.