Geology topics

James Grace

Publications and source records attributed to James Grace.

At least 19 recordsLinked to original sources

USGS2025

Causal interpretations can be based on mechanistic knowledge

There exists a long-standing disconnect between statistical and mechanistic approaches to the development of causal understanding. Statistical approaches, which have dominated the literature, have focused on the need to obtain perfectly unbiased estimates of causal effects often using either experimental, quasi-experimental or other methods. Mechanistic approaches have instead focused on investigating how systems work by elucidating the structures and processes whereby variations in one system property can propagate to other system properties. Explicit references to ‘causal effects’ have tended to require adherence to statistical methods and standards, inadvertently downplaying the suitability of mechanistic knowledge for that purpose. It has been recently demonstrated that both mechanistic and statistical approaches can contribute to the long-term goal of developing causal knowledge and understanding. Proponents of statistical causal inference have seldom recommended that mechanistic evidence be relied upon to support causal interpretations. This paper provides a clear and thorough example where a causal interpretation can be supported based on mechanistic knowledge. Arguing for a causal interpretation based on knowledge of mechanisms has typically been an informal process and one that has thus far infrequently led to explicit declarations of causal knowledge by scientists. To overcome this problem, we illustrate a recently described procedure referred to as ‘causal knowledge analysis’ to summarize explicit support for causal interpretations. In this paper, we first clarify the basis of the long-standing disagreement by describing the crux of the problem as viewed from a statistical perspective and by describing how it can be overcome when there is sufficient mechanistic knowledge. We then offer a proof-of-concept example based on robust documentation and description of the mechanisms whereby plants causally regulate the responses of coastal marsh elevation to changes in sea level. Synthesis —The evidential requirements for declaring a relationship to be causal have been obscured until very recently, leading to a long neglect of this issue by scientists. Meanwhile, subject matter experts have accumulated a vast body of undeclared causal knowledge that we now need to recognize in order to position scientists as essential players in defending causal interpretations.

Journal of Ecology↗

USGS2025

Causal effects verses causal mechanisms: Two traditions with different requirements and contributions towards causal understanding

The scientific aspiration of building causal knowledge has received little explicit discussion in ecology despite its fundamental importance. When methods are described as ‘causal’, emphasis is increasingly placed on statistical techniques for isolating associations so as to quantify causal effects. In contrast, natural scientists have historically approached the pursuit of causal knowledge through the investigation of mechanisms that interconnect the components of systems. In this paper, we first summarise a recently published multievidence paradigm for causal studies meant to reconcile conflicting viewpoints. We then describe some of the basic principles of causal statistics and the challenge of estimating pure causal effects. We follow that by describing basic principles related to causal mechanistic investigations, which focus on characterising the structures and processes conveying causal effects. While causal statistics focuses on estimating effect sizes, mechanistic investigations focus on characterising the attributes of the underlying structures and processes linking causative agents to responses. There are important differences between how one approaches each endeavour, as well as differences in what is obtained from each type of investigation. Finally, the case is made that an explicit assessment of existing mechanistic knowledge should be an initial step in causal investigations.

Florida, Louisiana, Texas↗

USGS2025

Nature-based solutions could offset coastal squeeze of tidal wetlands from sea-level rise on the U.S. Pacific coast

In this study, we explored the opportunities for tidal wetland landward migration in response to sea-level rise on the Pacific Coast of the United States. By employing a systematic spatial approach, we quantified the available space for wetland migration with sea-level rise across 61 estuarine drainage areas. Although many of the existing tidal wetlands are small patches, our analyses show that 63% of the estuaries lacked the landward migration space needed to replace current tidal wetland extent, thereby threatening a wide range of protected species and ecosystem services. Developed lands and steep topography represent common barriers to migration along the Pacific coast, especially in central and southern California. The available wetland migration space consists primarily of agriculture, pasture, and freshwater wetlands, with most of the area available for migration occurring in just a few watersheds. In most watersheds tidal wetland migration would only occur with human intervention or facilitation. The greatest amount of area available for wetland migration was in the San Francisco Bay-Delta and Columbia River estuaries, together accounting for 58% of all available migration space on the Pacific Coast. Nature-based solutions to reduce tidal wetland loss from sea-level rise can include restoration in suitable areas, removal of barriers to tidal wetland migration, and elevation building approaches. Tidal wetland restoration opportunities could increase area by 59%, underscoring it as a plausible approach to prevent tidal wetland loss in those estuaries and a viable Nature-based solution. 54% of estuaries building elevations of existing tidal wetlands may be the most feasible approach needed. Our analyses illustrate the importance of management efforts that use Nature-based approaches to prevent tidal wetland ecosystem and species loss over the coming decades from sea-level rise.

Pacific Coast↗

USGS2024

An integrative paradigm for building causal knowledge

A core aspiration of the ecological sciences is to determine how systems work, which implies the challenge of developing a causal understanding. Causal inference has long been approached from a statistical perspective, which can be limited and restrictive for a variety of reasons. Ecologists and other natural scientists have historically pursued mechanistic knowledge as an alternative approach to causal understanding, though without explicit reference to the requirements of causal statistics. In this paper, I describe the premises of an expanded paradigm for causal studies, the Integrative Causal Investigation Paradigm, that subsumes causal statistics and mechanistic investigation into a multi-evidence approach. This paradigm is distinct from the one articulated by causal statistics in that it (1) focuses its attention on the long-term goal of building causal knowledge across multiple studies and (2) recognizes the essential role of mechanistic investigations in establishing a causal understanding. The Integrative Paradigm, consequentially, proposes that there are multiple methodological routes to building causal knowledge and thus represents a pluralistic perspective. This paper begins by describing the crux of the problem faced by causal statistics. To understand this problem, it should be recognized that the word causal has multiple meanings and a variety of evidential standards. An expanded vocabulary is developed so as to reduce ambiguities and clarify critical issues. I further show by example that there is an important ingredient typically omitted from consideration in causal statistics, which is the known information related to the mechanisms underlying relationships being evaluated. To address this issue, I describe a procedure, Causal Knowledge Analysis, that involves an evaluation and compilation of existing evidence indicative of causal content and the features of mechanisms. Causal Knowledge Analysis is applied to three example situations to illustrate the process and its potential for contributing to the development of causal knowledge. The implications of adopting the proposed paradigm and associated procedures are discussed and include the potential for advancing ecology, the potential for clarifying causal methodology, and the potential for contributing to predictive forecasting.

Ecological Monographs↗

USGS2024

A conterminous United States–Wide validation of relative tidal elevation products

Recent large-scale spatial products have been developed to assess wetland position in the tidal frame, but nationwide comparisons and validations are missing for these products. Wetland position within the tidal frame is a commonly used characteristic to compare wetlands across biogeomorphic gradients and factors heavily into wetland vulnerability models. We utilize a dataset of 365 surface elevation table stations across the conterminous USA containing ground-surveyed tidal datum and elevation data to validate two gridded, conterminous USA–wide relative tidal elevation products. We identified substantial differences between our ground-surveyed dataset and the gridded products, with the Gulf coast exhibiting the greatest error ( p < 0.0001, n = 140). Error in relative tidal elevation products varied by coast, tidal range, and latitude. These differences in errors indicate that gridded relative tidal elevation products may be more accurate in coastal wetlands with larger tidal ranges (> 30 cm) and are less accurate in freshwater wetlands near the coast. This paper makes advances in understanding why relative tidal elevation differences occur among national datasets and identifies areas of future work that could support more robust vulnerability models.

Estuaries and Coasts↗

USGS2023

Observing coastal wetland transitions using national land cover products

Over the coming century, climate change and sea-level rise are predicted to cause widespread change to coastal wetlands. Estuarine vegetated wetlands can adapt to sea-level rise through both vertical development (i.e., biophysical feedbacks and sedimentation) and upslope/horizontal migration. Quantifying changes to estuarine vegetated wetlands over time can help to inform current and future decisions regarding land management and resource stewardship. In this study, we show how coastal land cover maps readily available in the US can be used to assess and understand estuarine vegetated wetland changes. This assessment involves two steps: (1) identifying the net gain/loss of estuarine vegetated wetlands and (2) determining which land cover types contribute to the net gain/loss. From this information, we developed estuarine vegetated wetland change scenarios that evaluate whether estuarine vegetated wetland gain kept up with loss and whether the contribution was from: (1) estuarine vegetated wetland migration or tidal restoration; (2) land building (i.e., development); or (3) both. We assessed changes from 1996 to 2016 for: (1) the conterminous US; (2) each major US coastline; and (3) focal estuaries with the most change per coast. We found that the change scenario (1, 2, or 3) varied across coastlines. Moving forward, national coastal land cover programs can be informed by utilizing methodologies that leverage contemporary information for delineating the estuarine zone from upslope/adjacent wetlands. We highlight approaches that could be used to address this challenge and provide complementary information related to wetland condition changes.

Progress in Physical Geography: Earth and Environm↗

USGS2023

Nonlinear patterns of surface elevation change in coastal wetlands: The value of generalized additive models for quantifying rates of change

In the face of accelerating climate change and rising sea levels, quantifying surface elevation change dynamics in coastal wetlands can help to develop a more complete understanding of the implications of sea-level rise on coastal wetland stability. The surface elevation table-marker horizon (SET-MH) approach has been widely used to quantify and characterize surface elevation change dynamics in coastal marshes and mangrove forests. Whereas past studies that utilized the SET-MH approach have most often quantified rates of surface elevation change using simple linear regression analyses, several recent studies have shown that elevation patterns can include a diverse combination of linear and non-linear patterns. Generalized additive models (GAMs) are an extension of generalized linear models (GLMs) that have previously been used to analyze a variety of complex ecological processes such as cyclical changes in water quality, species distributions, long-term patterns in wetland area change, and palaeoecological time series. Here, we use long-term SET data to demonstrate the value of generalized additive models for analyzing non-linear patterns of surface elevation change in coastal wetlands. Additionally, we illustrate how the GAM approach can be used to effectively quantify rates of elevation change at both landscape- and local site-level scales.

Estuaries and Coasts↗

USGS2023

Perspectives on the scientific legacy of J. Philip Grime

Perhaps as much as any other scientist in the 20th century, J.P. Grime transformed the study of plant ecology and helped shepherd the field toward international prominence as a nexus of ideas related to global environmental change. Editors at the Journal of Ecology asked a group of senior plant ecologists to comment on Grime's scientific legacy. This commentary piece includes individual responses of 14 scientists from around the world attesting to Grime's foundational role in plant functional ecology, including his knack for sparking controversy, his unique approach to theory formulation involving clever experiments and standardized trait measurements of large numbers of species, and the continued impact of his work on ecological science and policy.

Journal of Ecology↗

USGS2023

Integrated analysis shows how the effects of extreme flooding events propagate through fish communities to impact amphibians

Research Highlight: Davis, C. L., Walls, S. C., Barichivich, W. J., Brown, M. E., & Miller, D. A. (2022). Disentangling direct and indirect effects of extreme events on coastal wetland communities. Journal of Animal Ecology , https://doi.org/10.1111/1365-2656.13874 . Catastrophic events such as floods, hurricanes, winter storms, droughts and wildfires increasingly touch our lives either directly or indirectly. These events draw our attention to the seriousness of changes in climate not only to human well-being but also to the integrity of ecological systems upon which we depend. Understanding the impacts of extreme events on ecological systems requires the ability to characterize the cascading effects of environmental changes on the environments in which organisms live and the altered biological interactions produced. This scientific ambition represents no small challenge for the study of animal communities, which are typically difficult to census as well as dynamic in time and space. Davis et al. (2022) in a recent study in the Journal of Animal Ecology examined the amphibian and fish communities found in depressional coastal wetlands to better understand how they respond to major rainfall and flooding events. Data from the U.S. Geological Survey's Amphibian Research and Monitoring Initiative provided an 8-year record of observations as well as environmental measurements. For this study, the authors integrated techniques for assessing the dynamics of animal populations with a Bayesian implementation of structural equation modelling. Using their integrated methodological approach permitted the authors to reveal the direct and indirect effects of extreme weather events on co-occurring amphibian and fish communities while accounting for observational uncertainty and temporal variation in population-level processes. Their findings indicate that the most prominent effects of flooding on the amphibian community were caused by changes in the fish community that led to increased predation and resource competition. In their conclusions, the authors emphasize the importance of understanding networks of abiotic and biotic effects if we are to predict and mitigate the influence of extreme weather events.

Journal of Animal Ecology↗

USGS2023

From bottom-up to top-down control of invertebrate herbivores in a retrogressive chronosequence

In the long-term absence of disturbance, ecosystems often enter a decline or retrogressive phase which leads to reductions in primary productivity, plant biomass, nutrient cycling and foliar quality. However, the consequences of ecosystem retrogression for higher trophic levels such as herbivores and predators, are less clear. Using a post-fire forested island-chronosequence across which retrogression occurs, we provide evidence that nutrient availability strongly controls invertebrate herbivore biomass when predators are few, but that there is a switch from bottom-up to top-down control when predators are common. This trophic flip in herbivore control probably arises because invertebrate predators respond to alternative energy channels from the adjacent aquatic matrix, which were independent of terrestrial plant biomass. Our results suggest that effects of nutrient limitation resulting from ecosystem retrogression on trophic cascades are modified by nutrient-independent variation in predator abundance, and this calls for a more holistic approach to trophic ecology to better understand herbivore effects on plant communities.

Lake Hornavan, Lake Uddjaure↗

USGS2022

Piñon and juniper tree removal increases available soil water, driving understory response in a sage-steppe ecosystem

Over the past century, piñon and juniper trees have encroached into sagebrush steppe lands of the interior United States, and managers have for many years removed trees to stimulate the favored understory. While consistent understory response to tree removal in these semiarid lands suggests that trees outcompete other plants for water, no studies have linked increased soil water to understory response after tree removal. We tested the hypothesis that tree removal at six sagebrush steppe sites increased soil water, leading to increased understory plant cover. Using a structural equation model, we found that before tree removal, trees suppressed shrubs (standardized coefficient [SC] = −0.87), perennial deep-rooted (SC = −0.50) and shallow-rooted bunchgrasses (SC = −0.36), but had no influence on cheatgrass. The model explained between 2% (cheatgrass) and 40% (shrubs) of pretreatment cover variation. Measurement of the same plots six years post-treatment showed that most cover variation was due directly to plant growth, with standardized coefficients between 0.51 (perennial shallow-rooted grasses) and 0.72 (cheatgrass). Competition between cheatgrass and perennial deep-rooted grasses was evident, with perennials having twice the influence on cheatgrass than vice-versa (SC = −0.24 vs. −0.11). Spring soil water (wet-degree days) increased significantly after tree removal, measured as cumulative over 6 years (SC = 0.30), and in the early Spring of year six (SC = 0.16). Treatment-induced increase of cumulative Spring wet degree-days explained variation in shrub cover at year 6 (SC = 0.12) and the increase of early Spring wet degree-days at year 6 led to increases in perennial deep-rooted grasses (SC = 0.24) and cheatgrass (SC = 0.23). We detected no influence of Spring wet degree-days on perennial shallow-rooted grasses. The post-treatment model explained between 34% (shallow-rooted perennial grasses) and 69% (deep-rooted perennial grasses) of variation in understory cover. Most variation was explained by re-measurement of the same populations, followed by treatment effects mediated through increased soil water availability, soil factors, and direct effects of the treatment itself. In conclusion, our model is consistent with the a priori hypothesis that additional wet degree-days due to tree removal is a significant mechanism behind observed increases in understory cover.

California, Idaho, Nevada, Oregon, Utah↗

USGS2022

Surface elevation change dynamics in coastal marshes along the northwestern Gulf of Mexico: Anticipating effects of rising sea-level and intensifying hurricanes

Accelerated sea-level rise and intensifying hurricanes highlight the need to better understand surface elevation change in coastal wetlands. We used the surface elevation table-marker horizon approach to measure surface elevation change in 14 coastal marshes along the northwestern Gulf of Mexico, within five National Wildlife Refuges in Texas (USA). During the 2014–2019 study period, the mean rate of surface elevation change was 1.96 ± 0.87 mm yr −1 (range: -1.57 to 8.37 mm yr −1 ). Vertical accretion rates varied due to landscape proximity relative to sediment inputs from Hurricane Harvey. At most sites, vertical accretion offset subsurface losses due to shallow subsidence. However, net elevation gains were often lower than recent relative sea-level rise rates, and much lower than rates expected under future sea-level rise. Because these marshes are not keeping pace with recent sea-level rise, it is unlikely that they will be able to adjust to future accelerations. Climate change threatens these Texas coastal wetlands and the ecological and economic services they provide. By characterizing the status and prospective loss of coastal marshes, our study reinforces the value of identifying local and landscape-level adaptation mechanisms that can enhance the ability of coastal marshes to adapt to threats posed by climate change.

Texas↗

USGS2022

Migration and transformation of coastal wetlands in response to rising seas

Coastal wetlands are not only among the world’s most valued ecosystems but also among the most threatened by high greenhouse gas emissions that lead to accelerated sea level rise. There is intense debate regarding the extent to which landward migration of wetlands might compensate for seaward wetland losses. By integrating data from 166 estuaries across the conterminous United States, we show that landward migration of coastal wetlands will transform coastlines but not counter seaward losses. Two-thirds of potential migration is expected to occur at the expense of coastal freshwater wetlands, while the remaining one-third is expected to occur at the expense of valuable uplands, including croplands, forests, pastures, and grasslands. Our analyses underscore the need to better prepare for coastal transformations and net wetland loss due to rising seas.

Science Advances↗

USGS2021

Biodiversity effects on grape quality depend on variety and management intensity

Interactions between plants can be beneficial, detrimental or neutral. In agricultural systems, competition between crop and spontaneous vegetation is a major concern. We evaluated the relative support for three non-exclusive ecological hypotheses about interactions between crop and spontaneous plants based on competition, complementarity or facilitation. The study was conducted in Swiss vineyards with different vegetation management intensities. In all, 33 vineyards planted with two different grape varieties were studied over 3 years to determine whether low-intensity vegetation management might provide benefits for grape quality parameters. Management intensity varied with the degree of control of spontaneous inter-row vegetation. Features of spontaneous vegetation measured included total cover, total species richness and abundance of nitrogen-fixing plants. Grape quality parameters of known importance to wine making (yeast assimilable nitrogen, sugars, tartaric acid and malic acid) were determined by Fourier-transform infrared spectroscopy (FTIR). Using structural equation modelling, we evaluated hypotheses about the multivariate responses of grape quality parameters as well as the direct and indirect (plant-mediated) effects of management. Observed effects of management differed between grape varieties. Management intensity and abundance of N-fixing plants significantly influenced grape quality parameters while total richness of spontaneous plants did not have detectable effects. Abundance of N-fixing plants was enhanced by low-intensity management resulting in increased N content in the red grape variety Pinot noir , potentially enhancing grape quality, while measured soil N content did not explain the increase. Synthesis and applications . Our study shows that crop quality can be enhanced by spontaneous plants, in this case by the abundance of a key functional group (N-fixers), most likely through plant–plant or plant–microbe facilitation. However, beneficial interactions may have a high specificity in terms of facilitation partners and may have contrasting effects at low taxonomic resolutions such as crop varieties. Generally, increasing plant biodiversity in agricultural systems may increase competition with crops. Thus, the identification of suitable interaction partners and a careful balance between crop variety and spontaneous plant species may be necessary to utilize beneficial interactions and to reduce the trade-off between agricultural production and biodiversity to achieve a sustainable ecological benefit in agricultural systems.

Canton of Valais↗

USGS2021

Instrumental variable methods in structural equation models

Instrumental variable regression (RegIV) provides a means for detecting and correcting parameter bias in causal models. Widely used in economics, recently several papers have highlighted its potential utility for ecological applications. Little attention has thus far been paid to the fact that IV methods can also be implemented within structural equation models (SEMIV). In this paper I present the motivations, requirements and basic procedures for using SEMIV. I first consider causal inference and IVs from the perspective of a randomized experiment with partial control of the cause of interest. I consider common sources of bias, the role of randomization and limits to its capacity to exclude bias. Sources of bias include omitted confounders, reciprocal causation, reverse causation and measurement error, all of which can all be seen as a single problem—endogeneity. The approach to estimating IV models most commonly used in econometric practice, two-stage least squares regression (2SLS), is explained, followed by a brief exposition of the covariance modelling approach used in SEM. Using data from an ecological field experiment, I illustrate the use of the treatment variable as an IV and then illustrate procedures for evaluating candidate variables that might serve as additional IVs. IV methods are shown to be useful for both detecting endogeneity and removing its influences. I illustrate some of the ways that bias can be generated, as well as diagnostic capabilities and means for remedy embedded within SEM. Procedures for screening and evaluating additional IVs reveal valuable lessons regarding the theoretical requirements and empirical standards for IVs. SEMIV provides a useful way to detect and control for bias. I suggest that the use of IVs within the SEM framework can support the simultaneous pursuit of causal inference and explanatory modelling, a common pair of aspirations for ecologists. Moving forward, there is a need for a better understanding of the capabilities of SEMIV and requirements for successful application.

Methods in Ecology and Evolution↗

USGS2020

Hurricane Sandy effects on coastal marsh elevation change

High-magnitude storm events such as Hurricane Sandy are powerful agents of geomorphic change in coastal marshes, potentially altering their surface elevation trajectories. But how do a storm’s impacts vary across a large region spanning a variety of wetland settings and storm exposures and intensities. We determined the short-term impacts of Hurricane Sandy at 223 surface elevation table–marker horizon stations in estuarine marshes located across the northeast region of the United States by comparing post-storm surface elevation change with pre-storm elevation trends. We hypothesized that the storm’s effect on marsh elevation trends would be influenced by position relative to landfall (right or left) and distance from landfall. The structural equation model presented predicts that marshes located to the left of landfall were more likely to experience an elevation gain greater than expected, and this positive deviation from pre-storm elevation trends tended to have a greater magnitude than those experiencing negative deviations (elevation loss), potentially due to greater sediment deposition. The magnitude of negative deviations from elevation change in marshes to the right of landfall was greater than for positive deviations, with a greater effect in marshes within 200 km of landfall, potentially from the extent and magnitude of storm surge. Overall, results provide an integrated picture of how storm characteristics combined with the local wetland setting are important to a storm’s impact on surface elevation, and that the surface elevation response can vary widely among sites across a region impacted by the same storm.

Connecticut, Delaware, Maine, Maryland, Massachuse↗

USGS2019

The importance of natural versus human factors for ecological conditions of streams and rivers

Streams are influenced by watershed-scale factors, such as climate, geology, topography, hydrology, and soils, which mostly vary naturally among sites, as well as human factors, agriculture and urban development. Thus, natural factors could complicate assessment of human disturbance. In the present study, we use structural equation modeling and data from the 2008-2009 United States National Rivers and Streams Assessment to quantify the relative importance of watershed-scale natural and human factors for in-stream conditions. We hypothesized that biological condition, represented using a diatom multimetric index (MMI), is directly affected by in-stream physicochemical environment, which in turn is regulated by natural and human factors. We evaluated this hypothesis at both national and ecoregion scales to understand how influences vary among regions. We found that direct influences of in-stream environment on diatom MMIs were greater than natural and human factors at the national scale and in all but one ecoregion. Meanwhile, in-stream environments were jointly explained by natural variations in precipitation, base flow index, hydrological stability, % volcanic rock, soil water table depth, and soil depth and by human factors measured as % crops, % other agriculture, and % urban land use. The explained variance of in-stream environment by natural and human factors ranged from 0.30 to 0.75, for which natural factors independently accounted for the largest proportion of explained variance at the national scale and in seven ecoregions. Covariation between natural and human factors accounted for a higher proportion of explained variance of in-stream environment than unique effects of human factors in most ecoregions. Ecoregions with relatively weak effects by human factors had relatively high levels of covariance, high levels of human disturbance, or small ranges in human disturbance. We conclude that accounting for effects of natural factors and their covariation with human factors will be important for accurate ecological assessments.

Science of the Total Environment↗

USGS2014

A synopsis of short-term response to alternative restoration treatments in sagebrush-steppe: the SageSTEP project

The Sagebrush Steppe Treatment Evaluation Project (SageSTEP) is an integrated long-term study that evaluates ecological effects of alternative treatments designed to reduce woody fuels and to stimulate the herbaceous understory of sagebrush steppe communities of the Intermountain West. This synopsis summarizes results through 3 yr posttreatment. Woody vegetation reduction by prescribed fire, mechanical treatments, or herbicides initiated a cascade of effects, beginning with increased availability of nitrogen and soil water, followed by increased growth of herbaceous vegetation. Response of butterflies and magnitudes of runoff and erosion closely followed herbaceous vegetation recovery. Effects on shrubs, biological soil crust, tree cover, surface woody fuel loads, and sagebrush-obligate bird communities will take longer to be fully expressed. In the short term, cool wet sites were more resilient than warm dry sites, and resistance was mostly dependent on pretreatment herbaceous cover. At least 10 yr of posttreatment time will likely be necessary to determine outcomes for most sites. Mechanical treatments did not serve as surrogates for prescribed fire in how each influenced the fuel bed, the soil, erosion, and sage-obligate bird communities. Woody vegetation reduction by any means resulted in increased availability of soil water, higher herbaceous cover, and greater butterfly numbers. We identified several trade-offs (desirable outcomes for some variables, undesirable for others), involving most components of the study system. Trade-offs are inevitable when managing complex natural systems, and they underline the importance of asking questions about the whole system when developing management objectives. Substantial spatial and temporal heterogeneity in sagebrush steppe ecosystems emphasizes the point that there will rarely be a “recipe” for choosing management actions on any specific area. Use of a consistent evaluation process linked to monitoring may be the best chance managers have for arresting woodland expansion and cheatgrass invasion that may accelerate in a future warming climate.

Rangeland Ecology and Management↗