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At least 145 records · Page 8Linked to original sources
USGS2019

Wind erosion and dust from US drylands: a review of causes, consequences, and solutions in a changing world

Erosion by wind is one of the principal processes associated with land degradation in drylands and is a significant concern to land managers and policymakers globally. In the drylands of North America, millions of tons of soil are lost to wind erosion annually. Of the 60 million ha in the United States identified as most vulnerable to wind erosion (arid and dominated by fine sandy soils), 64% are managed by federal agencies (37 million ha). Here we review the drivers and consequences of wind erosion and dust emissions on drylands in the United States, with an emphasis on actionable responses available to policymakers and practitioners. We find that while dryland soils are often relatively stable when intact, disturbances includ-ing fire, domestic livestock grazing, and off-highway vehicles can increase horizontal eolian flux by an order of magnitude, in some cases as much as 40-fold. A growing body of literature documents the large-scale impacts of deposited dust changing the albedo of mountain snow cover and in some cases reducing regional water supplies by ~5%. Predicted future increases in aridity and extreme weather events, includ-ing drought, will likely increase wind erosion and consequent dust generation. Under a drier and more variable future climate, new and existing soil- and vegetation-disturbing practices may interact in synergis-tic ways, with dire consequences for environments and society that are unforeseen to many but fairly pre-dictable given current scientific understanding. Conventional restoration and reclamation approaches, which often entail surface disturbance and rely on adequate moisture to prevent erosion, also carry consid-erable erosion risk especially under drought conditions. Innovative approaches to dryland restoration that minimize surface disturbance may accomplish restoration or reclamation goals while limiting wind erosion risk. Finally, multidisciplinary and multijurisdictional approaches and perspectives are necessary to under-stand the complex processes driving dust emissions and provide timely, context-specific information for mitigating the drivers and impacts of wind erosion and dust.

Ecosphere↗
USGS2019

Vegetation and precipitation shifts interact to alter organic and inorganic carbon storage in cold desert soils

Dryland ecosystems are experiencing shifts in rainfall and plant community composition, which are expected to alter cycling and storage of soil carbon (C). Few experiments have been conducted to examine long‐term effects on (1) soil organic C (SOC) pools throughout the soil profile, and (2) soil inorganic C (SIC) pools as they relate to dynamic changes in C storage and climate change. We measured SOC and SIC from 0 to 1 m beneath plants and in adjacent interplant microsites following nearly 20 yr of experimental manipulations of plant community (native sagebrush steppe or monoculture of exotic crested wheatgrass) and the amount and timing of water availability (ambient, or doubling of annual rainfall in the dormant, DORM, or growing, GROW, season). Under sagebrush plants, GROW increased both SOC and SIC pools, resulting in total carbon (TC) pools 15% greater than plots receiving ambient precipitation, while DORM decreased SOC and SIC pools, decreasing TC pools 20% from ambient. Under crested wheatgrass plants, GROW increased SOC by 73% but decreased SIC by 11% relative to ambient, netting no change in TC pools, while DORM SIC pools were 5% greater than ambient, with no significant increase in either SOC or TC pools. GROW significantly increased TC pools for interplant microsites, regardless of vegetation treatment. At the community scale and summing C pools weighted by percent patch cover, patterns of TC pool were similar to plot measurements. Our findings suggest that sagebrush communities can become a net C source to the atmosphere with increases in dormant season rainfall rather than a C sink as previously predicted . We also provide evidence of SIC as an important and dynamic C sequestration mechanism in drylands. Consideration of vegetation type, all or most of the soil profile, and both organic and inorganic C pools are all important to accurately predict C sequestration with changing climate and disturbance in drylands.

Ecosphere↗
USGS2019

Disentangling effects of invasive species and habitat while accounting for observer error in a long-term amphibian study

The invasive American bullfrog ( Lithobates catesbeianus ) and a variety of non‐native sport fish commonly co‐occur in lowland lentic habitats of the western United States. Both invasive taxa are implicated in declines of native amphibians in this region, but few long‐term studies of communities exist. Further, field studies of invasive–native interactions are complicated by confounding habitat modifications and observation errors. We surveyed amphibians and measured habitat characteristics for 12 yr across 38 wetland sites within the Willamette Valley, Oregon, USA. We assessed the influence of invasive species, habitat, and their interactions on the distributions of five native amphibian species using a multispecies dynamic occupancy model that accounted for false‐negative and false‐positive detections. In general, habitat characteristics—such as within‐pond vegetation cover, surrounding forest, and drought severity—were important for local persistence of native species when bullfrogs co‐occurred. We also found evidence of a cumulative negative effect of bullfrogs and non‐native fish (families Centrarchidae and Ictaluridae) on northern red‐legged frog ( Rana aurora ) local persistence that was mediated by the dominance of invasive reed canarygrass ( Phalaris arundinacea ). Non‐native fish and bullfrogs had variable effects on native amphibian species, but neither invasive taxon appears to be causing declines in occupied sites within our study area. Moreover, species relationships with habitat differed when invaders were present, indicating that certain habitats may increase persistence of native amphibians in the invaded landscape.

Oregon↗
USGS2019

To forage or flee: Lessons from an elk migration near a protected area

Alteration of wide-ranging wildlife migrations can drastically impact the structure and function of ecosystems, yet the causes and consequences of shifting migration patterns remain largely unknown. Management decisions made in one portion of a landscape may induce spatial and temporal shifts of wildlife use in another, creating tension among private, state, and federal lands with varying missions. Recent declines in migratory behavior have initiated studies focused primarily on spring migration, but the timing and benefits of autumn migration have received limited attention due to the difficulty in assessing the extreme asynchrony in autumnal events, although nutrition during this time period is crucial to winter survival and reproduction. Here, we used five years of data from 73 female elk (Cervus canadensis) which utilize a landscape managed by 4 federal agencies, a state, and private landowners, to identify the driving factors behind the initiation of fall migration in two subpopulations, one of which migrates to a protected area where hunting is prohibited. Most elk departed summer range prior to frost or snow, with 67% of elk that used the protected area migrating prior to the onset of archery hunting season (1 September), preemptively avoiding risk, while no elk from the other subpopulation left prior to archery season. However, departure from productive summer range prior to frost or snow, nearly two months before vegetation senescence led to an important tradeoff. Early migrants gave up 0.30% of late summer-fall integrated NDVI (iNDVI) per day when they moved to the safety of the protected area, leading to an average difference of 15.81% in iNDVI between an individual departing on 30 August (the mean departure date) versus an individual departing on 1 November. Our results suggest that in areas where migratory ungulates span multiple jurisdictions, the benefits of migratory behavior may be dramatically impacted by unevenly distributed anthropogenic disturbance. As this is a common scenario globally, our work highlights the urgent need to improve our understanding of subtle changes in migratory behavior, both spatially and temporally, which may erode the resilience of migration to future change.

Wyoming↗
USGS2019

Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): A cross-system analysis

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis ) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long‐term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long‐term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long‐term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long‐term dynamics of body size. The long‐term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long‐term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.

Ecosphere↗
USGS2019

Simulating the effects of climate variability on waterbodies and wetland-dependent birds in the Prairie Pothole Region

Understanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota.

North Dakota↗
USGS2019

Quantifying risk of whale–vessel collisions across space, time, and management policies

Transportation industries can negatively impact wildlife populations, including through increased risk of mortality. To mitigate this risk successfully, managers and conservationists must estimate risk across space, time, and alternative management policies. Evaluating this risk at fine spatial and temporal scales can be challenging, especially in systems where wildlife–vehicle collisions are rare or imperfectly detected. The sizes and behaviors of wildlife and vehicles influence collision risk, as well as how much they co‐occur in space and time. We applied a modeling framework based on encounter theory to quantify the risk of lethal collisions between endangered North Atlantic right whales and vessels. Using Automatic Identification System vessel traffic data and spatially explicit estimates of right whale abundance that account for imperfect detection, we modeled risk at fine spatiotemporal scales before and after implementation of a vessel speed rule in the southeastern United States. The expected seasonal mortality rates of right whales decreased by 22% on average after the speed rule was implemented, indicating that the rule is effective at reducing lethal collisions. The rule's effect on risk was greatest where right whales were abundant and vessel traffic was heavy, and its effect varied considerably across time and space. Our framework is spatiotemporally flexible, process‐oriented, computationally efficient and accounts for uncertainty, making it an ideal approach for evaluating many wildlife management policies, including those regarding collisions between wildlife and vehicles and cases in which wildlife may encounter other dangerous features such as wind farms, seismic surveys, or fishing gear.

Georgia, Florida↗
USGS2019

Knowing your limits: Estimating range boundaries and co-occurrence zones for two competing plethodontid salamanders

Understanding threats to species persistence requires knowledge of where species currently occur. We explore methods for estimating two important facets of species distributions, namely where the range limit occurs and how species interactions structure distributions. Accurate understanding of range limits is crucial for predicting range dynamics and shifts in response to interspecific interactions and climate change. Additionally, species interactions are increasingly recognized as an important but not well‐understood predictor of range shifts. Our objective was to predict range limits and contact zones for two plethodontid salamanders, the highly range‐restricted Shenandoah salamander ( Plethodon shenandoah ) and the wide‐ranging red‐backed salamander ( Plethodon cinereus ). Using detection/non‐detection data, we assess four methodological decisions when estimating species’ distributions: (1) accounting for imperfect detection, (2) covariates to predict species occurrences, (3) accounting for species interactions, and (4) the inclusion of spatial autocorrelation. We found that Shenandoah salamander and red‐backed salamander co‐occurrence would have been underestimated and the range edge misidentified had we not accounted for incomplete detection. Covariates related to habitat were not sufficient to explain species’ range boundaries. Models that included spatial autocorrelation (i.e., a conditional autoregressive random effect) performed better than models that included just species interactions (i.e., detection and occurrence were conditional on the other species being present) and models that included both spatial autocorrelation and species interactions. Further, we found that the breadth of primary contact zones was typically 60–170 m, which is greater on average than previous estimates. In addition, we frequently observed secondary, disjunct contact zones along the range boundary. Understanding the extent to which species co‐occur and how the range boundaries are shaped is crucial to conservation efforts. Our work indicates that accounting for detection is crucial for accurately characterizing range edges and that spatial models may be especially effective in modeling distributions at the boundary.

Ecosphere↗
USGS2019

Developing an expert elicited simulation model to evaluate invasive species and fire management alternatives

Invasive species can alter ecosystem properties and cause state shifts in landscapes. Resource managers charged with maintaining landscapes require tools to understand implications of alternative actions (or inactions) on landscape structure and function. Simulation models can serve as a virtual laboratory to explore these alternatives and their potential impacts on a landscape. To be useful, however, managers need to participate in model development to ensure that model structure can evaluate the response of key resources to plausible actions. Here, we detail development of a state‐and‐transition simulation model (STSM) to evaluate buffelgrass ( Cenchrus ciliaris L. syn Pennisetum ciliare (L.) Link) in Saguaro National Park (SNP), Arizona, USA, through collaboration between managers and researchers. We integrate expert knowledge and research to create and parameterize a stochastic, spatially explicit STSM to evaluate specific management objectives. We also develop a dynamic link between the STSM and a fire behavior model to allow exploration of potential novel processes introduced to the ecosystem by buffelgrass invasion. Our projections show that buffelgrass can be expected to increase on the landscape and that the integration of fire into the model accelerates the projected rate of invasion and increases degradation of resources of management concern. We highlight the benefit of engaging end users in the modeling process so that the model is targeted to evaluate management objectives, in this case retention of saguaro cacti ( Carnegiea gigantea (Engelm.) Britton & Rose) on the landscape. Being able to integrate an external model that can help address the unique characteristics of a problem such as the introduction of fire into the SNP desert ecosystem increases the ability of simulations to address complex ecological and management questions.

Ecosphere↗
USGS2019

Mechanisms underlying increased nest predation in natural gas fields: a test of the mesopredator release hypothesis

Anthropogenic activities are changing landscapes and the context in which predator–prey dynamics evolved, thereby altering key ecological processes and community structure. Yet, the specific mechanisms underlying such changes are rarely understood. We tested whether a mesopredator release explained increased rodent density and concomitant predation of songbird nests near natural gas development. From 2015 to 2016, we surveyed apex predators (coyotes, badgers, raptors, and corvids) and measured apparent survival and perceived predation risk of deer mice ( Peromyscus maniculatus ; a primary nest predator), at 12 plots spanning a gradient of surface disturbance caused by energy development in Wyoming, USA. Additionally, we measured densities of three nest predators: deer mice, least chipmunks ( Tamias minimus ), and thirteen-lined ground squirrels ( Ictidomys tridecemlineatus ). Contrary to the mesopredator release hypothesis, counts of apex predators and perceived predation risk of deer mice increased with surface disturbance from energy development, whereas apparent survival of mice decreased. Densities of mice and ground squirrels, however, increased with surface disturbance, despite increased predation pressure. We therefore rejected the mesopredator release hypothesis as a potential mechanism underlying altered trophic dynamics near energy development. Our results suggest that apex predator control measures would not benefit declining songbirds on natural gas fields. Rather, apex predator abundance may be regulated from the bottom-up by rodents in this system. Our results corroborate a pattern showing weakened effects of mesopredator release in habitats modified by humans. Understanding how predator–prey dynamics may be altered in novel environments requires an understanding of how predators and prey alike respond to habitat change under different contexts.

Wyoming↗
USGS2019

Predicting species distributions: unifying model selection and scale optimization for multi-scale occupancy models

Geographic distributions are a basic component of a species’ ecology, and predicting distributions is a fundamental task of conservation and resource management. Reliable prediction depends on identification of appropriate scales of effect for environmental data, and scale-optimization techniques are thus desirable to identify optimal scales for predictor variables. Recent statistical developments have also advanced methods of model selection based explicitly on predictive ability, which differ from commonly-used methods that regulate model structures via anticipated predictive performance. Such methods are beginning to permeate into species distribution models (SDMs), yet there remains no consensus methodology for developing optimally-predictive multi-scale SDMs when covariate data are collected over a range of scales. Thus, we compared the performance of common approaches for scale optimization and model selection in terms of their ability to produce optimally predictive multi-scale Bayesian occupancy models for predicting a species distribution, using models of the breeding distribution for King Rails (Rallus elegans) as a case study. Our results demonstrate sizable gains in predictive performance for hierarchical occupancy models selected explicitly via their ability to predict out-of-sample data using the logarithmic scoring rule, as compared to models selected using information criteria (DIC and WAIC). Information criteria commonly selected individual covariates, as well as scales of effect for those covariates, with suboptimal predictive performance. Performance of models selected using the logarithmic scoring rule was robust across method of scale optimization, which was not true for models selected using DIC and WAIC. Thus, we empirically demonstrate benefits of study designs that enable covariate and scale selection based explicitly on predictive ability. Our results also imply that more careful consideration of what constitutes an optimal scale is warranted in many ecological studies, as the meaning of optimal is not independent of the technique used for scale selection.

Ecosphere↗
USGS2019

Long-term trajectories of fractional component change in the Northern Great Basin, USA

The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the northern Great Basin from 1986 to 2016 using a dense Landsat imagery time-series. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified by climate bin and assess spatial and temporal relationships with climate variables. Finally, we statistically evaluate the minimum time density needed to accurately characterize temporal patterns and relationships with climate drivers. Over the 30-year period shrub cover declined and bare ground increased. While few pixels had > 10% cover change, a large majority had at least some change. All fractional components had significant spatial relationships with water year precipitation (WYPRCP), maximum temperature (WYTMAX), and minimum temperature (WYTMIN) in all years. Shrub and sagebrush cover in particular respond positively to warming WYTMIN, resulting from the largest increases in WYTMIN being in the coolest and wettest areas, and negatively to warming WYTMAX since the largest increases in WYTMAX are in the warmest and driest areas. The trade-off of lowering temporal density against removing cloud-contaminated years is justified as temporal density appears to have only a modest impact on trends and climate relationships until n ≤ 6, but multi-year gaps are proportionally more influential. Gradual change analysis is likely to be less sensitive to n than abrupt change. These data can be used to answer critical questions regarding the influence of climate change and the suitability of management practices.

California, Idaho, Nevada, Oregon, Utah↗
USGS2019

Evaluating mechanisms of plant‐mediated effects on herbivore persistence and occupancy across an ecoregion

Contemporary climate change is rapidly creating one of the greatest challenges for management and conservation during the 21st century. Mountain ecosystems, which have a high degree of spatial heterogeneity and contain numerous habitat specialists, have been identified as particularly vulnerable. We used data from multiple years across sites spanning a >40 million ha ecoregion to test hypotheses regarding how community‐level characteristics of vegetation may affect a mammalian generalist herbivore, the American pika ( Ochotona princeps ). We examined patterns of pika persistence across sites in the hydrographic Great Basin, and occupancy within a subset of these sites. We used mixed‐effects logistic regression models to compare evidence in support of competing explanations for each pattern within an information–theoretic framework (using Akaike's information criterion). Models reflected four hypothesized classes of mechanisms related to nutritional ecology, ecosystem function, indirect indication of climatic effects, and (synergistic) combinations of these three classes. At the site level, models reflecting synergistic effects received the most support. At the within‐site level, support appeared to be split equally among hypotheses containing predictors related to either nutritional ecology or indirect climate effects. Well‐supported predictors included cover of invasive plant species, cover of more‐xeric plant species, species evenness, and proportion of graminoid species. Our results both (1) identify important aspects of vegetation communities that may influence herbivore distribution in mountainous areas across a large, diverse geographic region, and (2) contribute to an improved understanding of how mountain ecosystems may be affected by ongoing climate change, more broadly.

California, Idaho, Nevada, Oregon, Utah, Wyoming↗
USGS2019

Ecosystem scale loss of grazing habitat impacted by abundance of dominant herbivores

Grazing lawns, patches of grazing tolerant plants with high nutrient value, provide important habitat for herbivores, and changes in abundance can impact herbivore populations. Grazing lawns are maintained in quality and quantity by repeated grazing and are a result of a positive feedback since the availability of grazing lawn can increase herbivore populations and increased herbivore populations can result in an increase in grazing lawn extent. We sampled aerial imagery from a long-term dataset (>20 yrs) at an internationally important breeding area for avian herbivores to model changes in grazing lawn abundance over time and identify the possible factors impacting those changes, including numbers of breeding birds, their primary predator, and spring phenology. Our data suggests that avian herbivores and their predators likely exert strong impacts on plant communities and may drive vegetation abundance. Decreases in the number of herbivore nests in our study coincided with an almost complete lack of grazing lawn in the mid-2000s. Any factors dictating the amount of grazing lawn available for avian herbivores could strongly influence breeding success and the maximum size of these populations. Our results demonstrate the importance of studying complex interactions among predators, herbivores and plants, and population moderation by both bottom-up and top-down processes.

Ecosphere↗
USGS2019

Negative impacts of summer heat on Sierra Nevada tree seedlings

Understanding the response of forests to climate change is important for predicting changes in biodiversity and ecosystem services, including carbon storage. Seedlings represent a key demographic stage in these responses, because seedling establishment is necessary for population persistence and spread, and because the conditions allowing seedlings to survive and grow are often more restrictive than those adults can tolerate. However, detailed long‐term data on the responses of individual seedlings to climatic variation are rare. Here, we analyze a decade of seedling growth and survival data collected in 25 long‐term plots located in Sequoia and Yosemite National Parks. The forest types represented range from lower‐elevation mixed conifer, to red fir‐dominated, to high‐elevation western white pine stands. Twelve species, including two oaks and ten conifers, are found across these plots. Survival and transition to larger size classes are modeled within a Bayesian framework as a function of species, size, fire, and various climate variables. We initially expected that precipitation‐related variables would have a strong effect on seedling survival and growth in this Mediterranean‐climate region and that some species might respond positively to higher temperatures if they are adapted to warmer low‐elevation areas or to higher‐than‐average temperatures if they are high‐elevation species whose growing seasons are limited by cold. However, we found that higher July maximum temperature or temperature anomalies were associated with lower survival and growth for most species, while precipitation and snow effects were weaker and more variable. Higher precipitation had a positive effect on survival of most species, but snow effects and precipitation effects on growth could be negative. Given the estimated climate responses, under potential future scenarios of higher summer temperatures and altered precipitation, most species are predicted to have lower survival and reduced growth. This is likely to favor species that have relatively high survival and growth and less negative responses to climatic shift (such as several of the pines) and perhaps lead to a more open forest structure—or potentially transition to non‐forest vegetation types where seedling recruitment does not keep pace with adult mortality.

California↗
USGS2019

Soil characteristics are associated with gradients of big sagebrush canopy structure after disturbance

Reestablishing shrub canopy cover after disturbance in semi-arid ecosystems, such as sagebrush steppe, is essential to provide wildlife habitat and restore ecosystem functioning. While several studies have explored the effects of landscape and climate factors on the success or failure of sagebrush seeding, the influence of soil properties on gradients of shrub canopy structure in successfully seeded areas remains largely unexplored. In this study, we evaluated associations between soil properties and gradients in sagebrush canopy structure in stands that had successfully reestablished after fire and subsequent seeding treatments. Using a dataset collected across the Great Basin, USA, of sagebrush stands that had burned and reestablished between 1986 and 2013, we tested soil depth and texture, soil surface classification, biological soil crusts plus mean historical precipitation, solar heatload, and fire history as modeling variables to explore gradients in sagebrush canopy structure growth in terms of cover, height, and density. Deeper soils were associated with greater sagebrush canopy structure development in terms of plant density and percent cover, coarser textured soils were associated with greater sagebrush cover and density, and more clayey soils were typically associated with greater height. Biological crust presence was also positively associated with enhanced sagebrush canopy growth, but adding more demographically or morphologically explicit descriptions of biocrust communities did not improve explanatory power. Increasing heatload had a negative effect on sagebrush canopy structure growth, and increased mean annual precipitation was only associated with greater sagebrush height. Given that conservation and restoration of the sagebrush steppe ecosystems has become a priority for land managers, the associations we identify between gradients in post-fire sagebrush canopy structure growth and field-identifiable soil characteristics may improve planning of land treatments for sagebrush restoration and the understanding of semi-arid ecosystem functioning and post-disturbance dynamics.

Ecosphere↗
USGS2019

The importance of simulation assumptions when evaluating detectability in population models

Population monitoring is important for investigating a variety of ecological questions, and N-mixture models are increasingly used to model population size (N) and trends (lambda) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and lambda, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system (GPS) data from greater sage-grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and lambda from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N-mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50% whereas N-mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of lambda from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated lambda whereas N-mixture models estimated lambda with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N-mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.

Ecosphere↗
USGS2019

Genetic variation in tree leaf chemistry predicts the abundance and activity of autotrophic soil microorganisms

Genetic variation in the chemistry of plant leaves can have ecosystem-level consequences. Here we address the hypothesis that genetic variation in foliar condensed tannins along a Populus hybridization gradient influence soil ammonia oxidizers, autotrophic microorganisms that perform the first step of nitrification and are not dependent on carbon derived from plant photosynthesis. Evidence that genetically based plant traits influence the abundance and activity of autotrophic soil microbes would greatly expand the concept of extended plant phenotypes. We found that increasing foliar condensed tannin concentration reduced rates of soil nitrification potential by ~ 75%, reduced the abundance of ammonia oxidizing archaea by ~ 66%, but had no effect on ammonia oxidizing bacteria. Other indices that often drive nitrification rates, including soil total nitrogen, foliar nitrogen, and soil pH, were not significant predictors of either the activity or abundance of ammonia oxidizers, suggesting genetic variation in foliar condensed tannins may be the dominant regulating factor. These results demonstrate the condensed tannin phenotypes of two different tree species and their naturally occurring hybrids have extended effects on a key ecosystem process and provide evidence for indirect genetic linkages among autotrophs across at least two domains of life.

Ecosphere↗