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At least 163 records · Page 9Linked to original sources

USGS2017

Skagit River coho salmon life history model—Users’ guide

Natural resource management is conducted in the context of multiple anthropogenic stressors and is further challenged owing to changing climate. Experiments to determine the effects of climate change on complex ecological systems are nearly impossible. However, using a simulation model to synthesize current understanding of key ecological processes through the life cycle of a fish population can provide a platform for exploring potential effects of and management responses to changing conditions. Potential climate-change scenarios can be imposed, responses can be observed, and the effectiveness of potential actions can be evaluated. This approach is limited owing to future conditions likely deviating in range and timing from conditions used to create the model so that the model is expected to become obsolete. In the meantime, however, the modeling process explicitly states assumptions, clarifies information gaps, and provides a means to better understand which relationships are robust and which are vulnerable to changing climate by observing whether and why model output diverges from actual observations through time. The purpose of the model described herein is to provide such a decision-support tool regarding coho ( Oncorhynchus kisutch ) salmon for the Sauk-Suiattle Indian Tribe of Washington State. The Skagit coho salmon model is implemented in a system dynamics format and has three primary stocks—(1) predicted smolts, (2) realized smolts, and (3) escapement. “Predicted smolts” are the number of smolts expected based on the number of spawners in any year and the Ricker production curve. Pink salmon ( Oncorhynchus gorbuscha ) return to the Skagit River in odd years, and when they overlap with juvenile rearing coho salmon, coho smolt production is substantially higher than in non-pink years. Therefore, the model uses alternative Ricker equations to predict smolts depending on whether their juvenile year was a pink or non-pink year. The stock “realized smolts” is calculated based on the expected effect of streamflow conditions to alter the productivity predicted by the Ricker curve. Adverse conditions include scouring flow events that occur when redds are present; high-flow events during winter on juveniles, which can cause fish displacement and adverse water turbidity; and extremely low flows in summer. The stock “escapement” represents the fish remaining after accounting for ocean mortality and harvest. Ocean mortality has been linked with indices of ocean conditions, which are related to ocean biological productivity. Ocean survival also may have a density-dependent component such that lower survival is associated with higher numbers of smolts. The model allows the user to change certain model parameters and inputs, and choose among alternative predictors for certain modeled relations.

Washington↗

USGS2000

Evaluation of seismic slope-performance models using a regional case study

This paper compares four permanent displacement models based on Newmark's sliding-block analogy for assessing regional seismic slope-performance. The models vary primarily by the ground motion descriptor used to correlate with Newmark displacement. The first uses peak ground-acceleration (PGA). The second uses PGA but normalizes displacements by predominant period and equivalent cycles. The third uses Arias intensity. The fourth calculates cumulative displacements from double-integrating simulated earthquake accelerograms. The models are implemented in a GIS to characterize seismic slope-performance for the Oakland East quadrangle near San Francisco, California. The resulting slope-performance maps are compared visually and through statistical analysis to expose potential differences and assess the effects of using a particular approach within a decision-making context. These maps were created for the purpose of comparison and are not suitable for use as critical decision-making tools. The models forecast notably different levels of slope-performance, with the PGA-based models predicting the greatest Newmark displacement on average. Thus, considering the variety of slope-performance models, it is suggested that practitioners avoid reliance on a single model. Instead, multiple models can be implemented in a GIS framework to gain a better perspective of the potential hazard and make a more informed decision.

California↗

USGS2022

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat

Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.

Ecological Applications↗

USGS2015

An empirical evaluation of landscape energetic models: Mallard and American black duck space use during the non-breeding period

Bird conservation Joint Ventures are collaborative partnerships between public agencies and private organizations that facilitate habitat management to support waterfowl and other bird populations. A subset of Joint Ventures has developed energetic carrying capacity models (ECCs) to translate regional waterfowl population goals into habitat objectives during the non-breeding period. Energetic carrying capacity models consider food biomass, metabolism, and available habitat to estimate waterfowl carrying capacity within an area. To evaluate Joint Venture ECCs in the context of waterfowl space use, we monitored 33 female mallards ( Anas platyrhynchos ) and 55 female American black ducks ( A. rubripes ) using global positioning system satellite telemetry in the central and eastern United States. To quantify space use, we measured first-passage time (FPT: time required for an individual to transit across a circle of a given radius) at biologically relevant spatial scales for mallards (3.46 km) and American black ducks (2.30 km) during the non-breeding period, which included autumn migration, winter, and spring migration. We developed a series of models to predict FPT using Joint Venture ECCs and compared them to a biological null model that quantified habitat composition and a statistical null model, which included intercept and random terms. Energetic carrying capacity models predicted mallard space use more efficiently during autumn and spring migrations, but the statistical null was the top model for winter. For American black ducks, ECCs did not improve predictions of space use; the biological null was top ranked for winter and the statistical null was top ranked for spring migration. Thus, ECCs provided limited insight into predicting waterfowl space use during the non-breeding season. Refined estimates of spatial and temporal variation in food abundance, habitat conditions, and anthropogenic disturbance will likely improve ECCs and benefit conservation planners in linking non-breeding waterfowl habitat objectives with distribution and population parameters. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Arkansas, Delaware, Louisiana, Michigan, New Jerse↗

USGS2026

Synthesizing beaver coexistence messaging with the capability, opportunity, and motivation behavior model

In the western United States, conservation practitioners are increasingly working with private landowners to restore habitat for North American beavers ( Castor canadensis ) and to use nonlethal mitigation techniques when beavers damage crops and infrastructure. Effective communication is critical for promoting coexistence, yet on-the-ground conservation messaging seldom links to behavior change theories. We conducted 23 semistructured interviews with practitioners to examine the approaches they used to communicate with private landowners about beaver coexistence in Oregon (USA). Although we did not set out to interview practitioners about their messages targeting capability, opportunity, and motivation (elements of the COM-B model of behavior), we used the COM-B model to synthesize the primary dimensions of practitioners’ complex, real-world communication about human–wildlife coexistence. We found that practitioners used multiple communication channels to listen for and respond to landowners’ capability, opportunity, and motivation. They tailored messages to affirm and enhance knowledge and skills, identify and address site-specific and social contexts, and align beaver impacts with landowner goals. Our findings suggest the COM-B model can go beyond guiding audience analysis and behavioral intervention design to help practitioners tailor real-time communication with landowners about coexistence behavior. The model, based on our use of COM-B to analyze existing communication, could be used to provide practitioners with techniques for making sense of their existing communication efforts, for identifying gaps, and for dynamically tailoring their communication.

Oregon↗

USGS2025

UAV-derived models of vegetation characteristics do not transfer to extreme drought and wet conditions across a northern Arizona landscape

Context Shifts in precipitation regimes due to climate change are significantly impacting dryland ecosystems, including vegetation composition and structure. Unoccupied aerial vehicles (UAVs) are widely used to monitor vegetation, but whether models built to predict changes in these characteristics are robust under extreme precipitation regimes is unclear. Objectives We aimed to predict key vegetation characteristics under three precipitation regimes (ambient, drought, and water addition) and assess model performance across these moisture conditions. We also evaluated how models built under ambient conditions predicted vegetation characteristics under extreme precipitation regimes. Methods UAV surveys were conducted at five sites subject to long-term precipitation manipulation along an elevation gradient in northern Arizona, United States (U.S.). Twenty-one vegetation indices and point cloud data from the UAV imagery were used to develop models to predict vegetation structure and composition characteristics. Model performance and transferability were assessed via error and directional bias within each treatment (i.e., in situ) and from ambient to precipitation treatments (i.e., model transfer). Results UAV-based models accurately measured vegetation characteristics across all regimes, but maximum height showed significantly higher error under drought conditions. Models developed under ambient precipitation and applied to extreme precipitation treatments exhibited significant differences in the error and directional bias, indicating they may not be suitable under climate change. Conclusions UAV-based models are effective for monitoring vegetation characteristics but may lose accuracy under extreme precipitation regimes expected under climate change. This study emphasizes the need to improve model transferability and suggests refining landscape monitoring approaches to consider extreme changes in precipitation and associated vegetation responses.

Arizona↗

USGS2013

The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.

Nevada↗

USGS2018

Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA

Nitrate contamination of groundwater in agricultural areas poses a major challenge to the sustainability of water resources. Aquifer vulnerability models are useful tools that can help resource managers identify areas of concern, but quantifying nitrogen (N) inputs in such models is challenging, especially at large spatial scales. We sought to improve regional nitrate (NO 3 − ) input functions by characterizing unsaturated zone NO 3 − transport to groundwater through use of surrogate, machine-learning metamodels of a process-based N flux model. The metamodels used boosted regression trees (BRTs) to relate mappable landscape variables to parameters and outputs of a previous “vertical flux method” (VFM) applied at sampled wells in the Fox, Wolf, and Peshtigo (FWP) river basins in northeastern Wisconsin. In this context, the metamodels upscaled the VFM results throughout the region, and the VFM parameters and outputs are the metamodel response variables. The study area encompassed the domain of a detailed numerical model that provided additional predictor variables, including groundwater recharge, to the metamodels. We used a statistical learning framework to test a range of model complexities to identify suitable hyperparameters of the six BRT metamodels corresponding to each response variable of interest: NO 3 − source concentration factor (which determines the local NO 3 − input concentration); unsaturated zone travel time; NO 3 − concentration at the water table in 1980, 2000, and 2020 (three separate metamodels); and NO 3 − “extinction depth”, the eventual steady state depth of the NO 3 − front. The final metamodels were trained to 129 wells within the active numerical flow model area, and considered 58 mappable predictor variables compiled in a geographic information system (GIS). These metamodels had training and cross-validation testing R 2 values of 0.52 – 0.86 and 0.22 – 0.38, respectively, and predictions were compiled as maps of the above response variables. Testing performance was reasonable, considering that we limited the metamodel predictor variables to mappable factors as opposed to using all available VFM input variables. Relationships between metamodel predictor variables and mapped outputs were generally consistent with expectations, e.g. with greater source concentrations and NO 3 − at the groundwater table in areas of intensive crop use and well drained soils. Shorter unsaturated zone travel times in poorly drained areas likely indicated preferential flow through clay soils, and a tendency for fine grained deposits to collocate with areas of shallower water table. Numerical estimates of groundwater recharge were important in the metamodels and may have been a proxy for N input and redox conditions in the northern FWP, which had shallow predicted NO 3 − extinction depth. The metamodel results provide proof-of-concept for regional characterization of unsaturated zone NO 3 − transport processes in a statistical framework based on readily mappable GIS input variables.

Wisconsin↗

USGS1999

Robustness of closed capture-recapture methods to violations of the closure assumption

Closed-population capture–recapture methods have been used extensively in animal ecology, both by themselves and within the context of Pollock’s robust design and multistate models, to estimate various parameters of population and community dynamics. The defining assumption of geographic and demographic closure (i.e., no births, deaths, immigration, or emigration) for the duration of sampling is restrictive and is likely to be violated in many field situations. I evaluated several types of violations of the closure assumption and found that completely random movement in and out of a study area does not introduce bias to estimators from closed-population methods, although it decreases precision. In addition, if capture probabilities vary only with time, the closed-population Lincoln-Petersen estimator is unbiased for the size of the superpopulation when there are only births/immigration or only deaths/emigration. However, for other cases of nonrandom movement, closed-population estimators were biased when movement was Markovian (dependent on the presence/absence of the animal in the previous time period), when an animal was allowed one entry to and one exit from the study area, or when there was trap response or heterogeneity among animals in capture probability. In addition, the probability that an animal is present and available for capture (e.g., breeding propensity) can be estimated using Pollock’s robust design only when movement occurs at a broader temporal scale than that of sampling.

Ecology↗

USGS2025

Development of a two-stage life cycle model to inform the Trap and Haul Program for Coho salmon in the Lewis River, Washington

Restoration of salmon populations in the upper Lewis River Basin depends on a trap-and-haul program owing to the Lewis River Hydroelectric Project (Project) operated by PacifiCorp and Cowlitz PUD (Utilities), which has been a barrier to salmon passage since the 1930s. Thus, sustaining the Coho salmon ( Oncorhynchus kisutch ) population upstream of the Project currently depends on two fundamental factors: (1) the collection of upstream migrating adult Coho salmon at Merwin Dam, the lower most dam within the Project, and transporting them by truck to spawn above Swift Dam, the upper most dam within the Project; and (2) the collection of out-migrating juvenile Coho salmon at the downstream collection facility at Swift Dam for transport and release below the Project. The reintroduction program began once the downstream collection facility at Swift Dam was commissioned in late-2012 with the first year of transport data being collected in 2013. Over the past decade, the Utilities have been collecting data on juvenile outmigrants and adult fish returns at the dams. The need to construct a life cycle model for Lewis River anadromous fish was identified by the Lewis River Aquatic Technical Subgroup, with the understanding that many years (>15) of data collection are needed to adequately measure the life cycle production of coho salmon. Use of past data to construct models could help inform future data collection and provide a framework that can be updated annually to measure trap and haul program performance within a life cycle context (Note: Data are not currently available from PacifiCorp. Contact organization Chris Karchesky for further information). Because Coho salmon can live as long as five years, estimating demographic parameters for Coho salmon populations over their life cycle requires at least 10 or more years of data collection. Over the past decade, PacifiCorp has been collecting data on fish collection efficiency and the numbers of adult and juvenile salmon transported around the Lewis River dams, providing sufficient data to formulate a life cycle model that can guide future data collection efforts and provide preliminary information to resource managers The goal of the statistical life cycle model was to estimate annual production and survival during two critical life-stage transitions (1) the freshwater production from escapement of adults released upstream of Swift Dam, and the collection of downstream migrating juveniles at the passage facility at Swift Dam, and (2) the smolt-to-adult survival from the time of collection at Swift Dam to their return as adults. We used the Beverton-Holt stock-recruitment model to estimate juvenile production from the number of spawners. This approach allowed us to test for density dependence at current spawner abundances while estimating annual productivity, defined as the number of juveniles produced per spawner at low spawner abundance. Productivity was then expressed as a function of the number of juveniles collected and transported downstream of the Project. Because juvenile Fish Collection Efficiency (FCE) directly affects the number of juveniles that survive to continue downstream migration, FCE is a primary determinant of fish production. Consequently, the modeling framework is well suited to evaluate the performance of trap and haul programs within a life cycle context. The objectives of this study were to: (1) gather and collate available data on adult and juvenile Coho salmon at Merwin and Swift dams, (2) quantify adult escapement, juvenile abundance, and the age at outmigration and adult return, (3) describe, formulate, and fit the integrated population model (IPM) to the data, and (4) summarize our findings, identify data gaps, and identify potential opportunities for future studies that could provide information used to improve model estimation and inference. Our key findings were: (1) over and above the number of spawning females, FCE was the primary factor affecting productivity of Coho salmon above Swift Dam, (2) smolt-to-adult return (SAR) rates were relatively high considering that harvest was included in the estimate, averaging about 4.5% and ranging as high as 12.9%, and (3) juvenile capacity upriver of Swift Dam was difficult to estimate due to the limited range in spawning females over the time series of data, suggesting the model may be improved by collecting data at higher spawner abundances. In addition, by including FCE in the model, we estimated that the median pre-collection productivity, defined as the number of juveniles produced per spawner when FCE = 1, was 64 juveniles per spawner. Because this two-stage life cycle model partitions factors that affect fish production in river versus the ocean, the model estimates should help inform fishery managers about the overall role that fish collection at Swift Dam plays in the recovery and sustainability of Lewis River Coho salmon. By providing the model with (1) more years of data, (2) higher numbers of spawning females, and (3) data on age at juvenile migration in relation to age at adult return greater certainty in the estimates of capacity and SAR can be attained. Ultimately, information provided by the model can assist in the evaluation and continued improvement of the current trap and haul program to support anadromous fishes in the Lewis River Basin.

BioRxiv↗

USGS2012

Elucidating spatially explicit behavioral landscapes in the Willow Flycatcher

Animal resource selection is a complex, hierarchical decision-making process, yet resource selection studies often focus on the presence and absence of an animal rather than the animal's behavior at resource use locations. In this study, we investigate foraging and vocalization resource selection in a population of Willow Flycatchers, Empidonax traillii adastus , using Bayesian spatial generalized linear models. These models produce “behavioral landscapes” in which space use and resource selection is linked through behavior. Radio telemetry locations were collected from 35 adult Willow Flycatchers ( n = 14 males, n = 13 females, and n = 8 unknown sex) over the 2003 and 2004 breeding seasons at Fish Creek, Utah. Results from the 2-stage modeling approach showed that habitat type, perch position, and distance from the arithmetic mean of the home range (in males) or nest site (in females) were important factors influencing foraging and vocalization resource selection. Parameter estimates from the individual-level models indicated high intraspecific variation in the use of the various habitat types and perch heights for foraging and vocalization. On the population level, Willow Flycatchers selected riparian habitat over other habitat types for vocalizing but used multiple habitat types for foraging including mountain shrub, young riparian, and upland forest. Mapping of observed and predicted foraging and vocalization resource selection indicated that the behavior often occurred in disparate areas of the home range. This suggests that multiple core areas may exist in the home ranges of individual flycatchers, and demonstrates that the behavioral landscape modeling approach can be applied to identify spatially and behaviorally distinct core areas. The behavioral landscape approach is applicable to a wide range of animal taxa and can be used to improve our understanding of the spatial context of behavior and resource selection.

Utah↗

USGS2015

Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape

Content Changing aspen distribution in response to climate change and fire is a major focus of biodiversity conservation, yet little is known about the potential response of aspen to these two driving forces along topoclimatic gradients. Objective This study is set to evaluate how aspen distribution might shift in response to different climate-fire scenarios in a semi-arid montane landscape, and quantify the influence of fire regime along topoclimatic gradients. Methods We used a novel integration of a forest landscape succession and disturbance model (LANDIS-II) with a fine-scale climatic water deficit approach to simulate dynamics of aspen and associated conifer and shrub species over the next 150 years under various climate-fire scenarios. Results Simulations suggest that many aspen stands could persist without fire for centuries under current climate conditions. However, a simulated 2–5 °C increase in temperature caused a substantial reduction of aspen coverage at lower elevations and a modest increase at upper elevations, leading to an overall reduction of aspen range at the landscape level. Increasing fire activity may favor aspen increase at its upper elevation limits adjacent to coniferous forest, but may also favor reduction of aspen at lower elevation limits adjacent to xeric shrubland. Conclusions Our study highlights the importance of incorporating fine-scale terrain effects on climatic water deficit and ecohydrology when modeling species distribution response to climate change. This modeling study suggests that climate mitigation and adaptation strategies that use fire would benefit from consideration of spatial context at landscape scales.

Landscape Ecology↗

USGS2018

Using geologic structures to constrain constitutive laws not accessible in the laboratory

In this essay, we explore a central problem of structural geology today, and in the foreseeable future, which is the determination of constitutive laws governing rock deformation to produce geologic structures. Although laboratory experiments provide much needed data and insights about constitutive laws, these experiments cannot cover the range of conditions and compositions relevant to the formation of geologic structures. We advocate that structural geologists address this limitation by interpreting natural experiments, documented with field and microstructural data, using continuum mechanical models that enable the deduction of constitutive laws. To put this procedure into a historical context, we review the founding of structural geology by James Hutton in the late 18th century, and the seminal contributions to continuum mechanics from Newton to Cauchy that provide the tools to model geologic structures. The procedure is illustrated with two examples drawn from recent and on-going field investigations of crustal and mantle lithologies . We conclude by pointing to future research opportunities that will engage structural geologists in the pursuit of constitutive laws during the 21st century.

Journal of Structural Geology↗

USGS2015

Female sea lamprey shift orientation toward a conspecific chemical cue to escape a sensory trap

The sensory trap model of signal evolution hypothesizes that signalers adapt to exploit a cue used by the receiver in another context. Although exploitation of receiver biases can result in conflict between the sexes, deceptive signaling systems that are mutually beneficial drive the evolution of stable communication systems. However, female responses in the nonsexual and sexual contexts may become uncoupled if costs are associated with exhibiting a similar response to a trait in both contexts. Male sea lamprey ( Petromyzon marinus ) signal with a mating pheromone, 3-keto petromyzonol sulfate (3kPZS), which may be a match to a juvenile cue used by females during migration. Upstream movement of migratory lampreys is partially guided by 3kPZS, but females only move toward 3kPZS with proximal accuracy during spawning. Here, we use in-stream behavioral assays paired with gonad histology to document the transition of female preference for juvenile- and male-released 3kPZS that coincides with the functional shift of 3kPZS as a migratory cue to a mating pheromone. Females became increasingly biased toward the source of synthesized 3kPZS as their maturation progressed into the reproductive phase, at which point, a preference for juvenile odor (also containing 3kPZS naturally) ceased to exist. Uncoupling of female responses during migration and spawning makes the 3kPZS communication system a reliable means of synchronizing mate search. The present study offers a rare example of a transition in female responses to a chemical cue between nonsexual and sexual contexts, provides insights into the origins of stable communication signaling systems.

Behavioral Ecology↗

USGS2017

Safari Science: Assessing the reliability of citizen science data for wildlife surveys

Protected areas are the cornerstone of global conservation, yet financial support for basic monitoring infrastructure is lacking in 60% of them. Citizen science holds potential to address these shortcomings in wildlife monitoring, particularly for resource-limited conservation initiatives in developing countries – if we can account for the reliability of data produced by volunteer citizen scientists (VCS). This study tests the reliability of VCS data vs. data produced by trained ecologists, presenting a hierarchical framework for integrating diverse datasets to assess extra variability from VCS data. Our results show that while VCS data are likely to be overdispersed for our system, the overdispersion varies widely by species. We contend that citizen science methods, within the context of East African drylands, may be more appropriate for species with large body sizes, which are relatively rare, or those that form small herds. VCS perceptions of the charisma of a species may also influence their enthusiasm for recording it. Tailored programme design (such as incentives for VCS) may mitigate the biases in citizen science data and improve overall participation. However, the cost of designing and implementing high-quality citizen science programmes may be prohibitive for the small protected areas that would most benefit from these approaches. Synthesis and applications . As citizen science methods continue to gain momentum, it is critical that managers remain cautious in their implementation of these programmes while working to ensure methods match data purpose. Context-specific tests of citizen science data quality can improve programme implementation, and separate data models should be used when volunteer citizen scientists' variability differs from trained ecologists' data. Partnerships across protected areas and between protected areas and other conservation institutions could help to cover the costs of citizen science programme design and implementation.

Journal of Applied Ecology↗

USGS2020

High spatial fidelity among foraging trips of Masked Boobies from Pedro Cays, Jamaica

In marine environments, tropical and subtropical habitats are considered to be inherently less productive than more temperate systems. As such, foraging site fidelity among vertebrate predators occupying low-latitude marine systems is generally low as a response to an increased unpredictability of resources. We investigated the foraging movements of Masked Boobies breeding on Middle Cay, Jamaica using GPS loggers to examine if the presence of a nearby bathymetric feature influenced foraging site fidelity in a tropical system, the Caribbean Sea. According to the movements of tracked individuals, this population of boobies shows a high degree of spatial fidelity in foraging site selection, concentrated on the northern edge of Pedro Bank. We suggest this feature as an important location for marine conservation in the region and demonstrate its utility to foraging boobies via habitat modeling using a maximum entropy approach of relevant habitat variables. Finally, we place this study into the global context of Masked Booby foraging by examining the published literature of relevant tracking studies for population-level similarity in foraging metrics. According to hierarchical clustering of foraging effort, Masked Boobies demonstrate a density-dependent response to foraging effort regardless of colony origin or oceanic basin consistent with the principles of Ashmole’s Halo.

Middle Cay, Pedro Bank↗

USGS2020

Deglacierization of a marginal basin and implications for outburst floods, Mendenhall Glacier, Alaska

Suicide Basin is a partly glacierized marginal basin of Mendenhall Glacier, Alaska, that has released glacier lake outburst floods (GLOFs) annually since 2011. The floods cause inundation and erosion in the Mendenhall Valley, impacting homes and other infrastructure. Here, we utilize in-situ and remote sensing data to assess the recent evolution and current state of Suicide Basin. We focus on the 2018 and 2019 melt seasons, during which we collected most of our data, partly using unmanned aerial vehicles (UAVs). To provide longer-term context, we analyze DEMs collected since 2006 and model glacier surface mass balance over the 2006–2019 period. During the 2018 and 2019 outburst flood events, Suicide Basin released ~30 × 10 6 m 3 of water within approximately 4–5 days. Since lake drainage was partial in both years, these ~30 × 10 6 m 3 represent only a fraction (~60%) of the basin's total storage capacity. In contrast to previous years, subglacial drainage was preceded by supraglacial outflow over the ice dam, which lasted ~1 day in 2018 and 6 days in 2019. Two large calving events occurred in 2018 and 2019, with submerged ice breaking off the main glacier during lake filling, thereby increasing the basin's storage capacity. In 2018, the floating ice in the basin was 36 m thick on average. In 2019, ice thickness was 29 m, suggesting rapid decay of the ice tongue despite increasing ice inflow from Mendenhall Glacier. The ice dam at the basin entrance thinned by more than 5 m a –1 from 2018 to 2019, which is approximately double the rate of the reference period 2006–2018. While ice-dam thinning reduces water storage capacity in the basin, that capacity is increased by declining ice volume in the basin and longitudinal lake expansion, with the latter process challenging to predict. The potential for premature drainage onset (i.e., drainage before the lake's storage capacity is reached), intermittent drainage decelerations, and early drainage termination further complicates prediction of future GLOF events.

Alaska↗

USGS1996

Methods and techniques for rigorous calibration of a cellular automaton model of urban growth

Several lessons about the process of calibration were learned during development of a self-modifying cellular automaton model to predict urban growth. This model, part of a global change research project on human-induced land transformations, was used to predict the spatial extent of urban growth 100 years into the future. The context of the prediction was to evaluate urban environmental disturbances such as land use conversion, urban heat island intensification, and greenhouse gas generation. Using data for the San Francisco Bay area as a test case, methods were developed, including interactive and statistical versions of the model, animation and visualization tools, automated testing methods, and Monte Carlo simulations. This presentation will enumerate, analyze, and discuss the lessons learned during the extensive process of model calibration. Experience with the methods developed may have broader use in assisting the rigorous calibration for other CA models, and perhaps those coupled environmental models with an extensive spatial data component. These methods are now under test as the project moves to a new data set for the Washington, D.C.-Baltimore area.

Conference Paper↗