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James B. Grace

Publications and source records attributed to James B. Grace.

At least 55 records · Page 3Linked to original sources
USGS2016

Disentangling vegetation diversity from climate–energy and habitat heterogeneity for explaining animal geographic patterns

Broad-scale animal diversity patterns have been traditionally explained by hypotheses focused on climate–energy and habitat heterogeneity, without considering the direct influence of vegetation structure and composition. However, integrating these factors when considering plant–animal correlates still poses a major challenge because plant communities are controlled by abiotic factors that may, at the same time, influence animal distributions. By testing whether the number and variation of plant community types in Europe explain country-level diversity in six animal groups, we propose a conceptual framework in which vegetation diversity represents a bridge between abiotic factors and animal diversity. We show that vegetation diversity explains variation in animal richness not accounted for by altitudinal range or potential evapotranspiration, being the best predictor for butterflies, beetles, and amphibians. Moreover, the dissimilarity of plant community types explains the highest proportion of variation in animal assemblages across the studied regions, an effect that outperforms the effect of climate and their shared contribution with pure spatial variation. Our results at the country level suggest that vegetation diversity, as estimated from broad-scale classifications of plant communities, may contribute to our understanding of animal richness and may be disentangled, at least to a degree, from climate–energy and abiotic habitat heterogeneity.

Ecology and Evolution↗
USGS2016

Integrative modelling reveals mechanisms linking productivity and plant species richness

How ecosystem productivity and species richness are interrelated is one of the most debated subjects in the history of ecology . Decades of intensive study have yet to discern the actual mechanisms behind observed global patterns . Here, by integrating the predictions from multiple theories into a single model and using data from 1,126 grassland plots spanning five continents, we detect the clear signals of numerous underlying mechanisms linking productivity and richness. We find that an integrative model has substantially higher explanatory power than traditional bivariate analyses. In addition, the specific results unveil several surprising findings that conflict with classical models . These include the isolation of a strong and consistent enhancement of productivity by richness, an effect in striking contrast with superficial data patterns. Also revealed is a consistent importance of competition across the full range of productivity values, in direct conflict with some (but not all) proposed models. The promotion of local richness by macroecological gradients in climatic favourability, generally seen as a competing hypothesis , is also found to be important in our analysis. The results demonstrate that an integrative modelling approach leads to a major advance in our ability to discern the underlying processes operating in ecological systems.

Nature↗
USGS2016

Does urban sprawl hold down upward mobility?

Contrary to the general perception, the United States has a much more class-bound society than other wealthy countries. The chance of upward mobility for Americans is just half that of the citizens of the Denmark and many other European countries. In addition to other influences, the built environment may contribute to the low rate of upward mobility in the U.S. This study tests the relationship between urban sprawl and upward mobility for commuting zones in the U.S. We examine potential pathways through which sprawl may have an effect on mobility. We use structural equation modeling to account for both direct and indirect effects of sprawl on upward mobility. We find that upward mobility is significantly higher in compact areas than sprawling areas. The direct effect, which we attribute to better job accessibility in more compact commuting zones, is stronger than the indirect effects. Of the indirect effects, only one, through the mediating variable income segregation, is significant.

Landscape and Urban Planning↗
USGS2016

Comment on "Worldwide evidence of a unimodal relationship between productivity and plant species richness"

Fraser et al . (Reports, 17 July 2015, p. 302) report a unimodal relationship between productivity and species richness at regional and global scales, which they contrast with the results of Adler et al . (Reports, 23 September 2011, p. 1750). However, both data sets, when analyzed correctly, show clearly and consistently that productivity is a poor predictor of local species richness.

Science↗
USGS2015

Beyond just sea-level rise: Considering macroclimatic drivers within coastal wetland vulnerability assessments to climate change

Due to their position at the land-sea interface, coastal wetlands are vulnerable to many aspects of climate change. However, climate change vulnerability assessments for coastal wetlands generally focus solely on sea-level rise without considering the effects of other facets of climate change. Across the globe and in all ecosystems, macroclimatic drivers (e.g., temperature and rainfall regimes) greatly influence ecosystem structure and function. Macroclimatic drivers have been the focus of climate-change related threat evaluations for terrestrial ecosystems, but largely ignored for coastal wetlands. In some coastal wetlands, changing macroclimatic conditions are expected to result in foundation plant species replacement, which would affect the supply of certain ecosystem goods and services and could affect ecosystem resilience. As examples, we highlight several ecological transition zones where small changes in macroclimatic conditions would result in comparatively large changes in coastal wetland ecosystem structure and function. Our intent in this communication is not to minimize the importance of sea-level rise. Rather, our overarching aim is to illustrate the need to also consider macroclimatic drivers within vulnerability assessments for coastal wetlands.

Global Change Biology↗
USGS2015

Taking a systems approach to ecological systems

Increasingly, there is interest in a systems-level understanding of ecological problems, which requires the evaluation of more complex, causal hypotheses. In this issue of the Journal of Vegetation Science, Soliveres et al. use structural equation modeling to test a causal network hypothesis about how tree canopies affect understorey communities. Historical analysis suggests structural equation modeling has been under-utilized in ecology.

Journal of Vegetation Science↗
USGS2015

Compact development and VMT: environmental determinism, self-selection, or some of both?

There is a long-running debate in the planning literature about the effects of the built environment on travel behavior and the degree to which apparent effects are due to the tendency of households to self-select into neighborhoods that reinforce their travel preferences. Those who want to walk will choose walkable neighborhoods, and those who want to use transit will choose transit-served neighborhoods. These households might have walked or used transit more than their neighbors wherever they lived. Most previous studies have shown that individual attitudes attenuate the relationship between the residential environment and travel choices, and so the effect of the built environment on travel may be overestimated. But there are other researchers who argue the reverse, claiming that residential preferences reinforce built environmental influences. This study assesses the relative importance of the built environment and residential preferences/travel attitudes for a sample of 962 households in the Greater Salt Lake region using structural equation modeling. For the sake of simplicity, we extracted two factors using principal component analysis, one representing the built environment and the other representing residential preferences/attitudes. Our findings are consistent with the view that the neighborhood built environment and residential preferences both influence household’s travel, that the built environment is the stronger influence, and that the built environment affects travel through two causal pathways, one direct and the other indirect, through attitudes.

Environment and Planning B: Planning and Design↗
USGS2015

Do shrubs reduce the adverse effects of grazing on soil properties?

Increases in the density of woody plants are a global phenomenon in drylands, and large aggregations of shrubs, in particular, are regarded as being indicative of dysfunctional ecosystems. There is increasing evidence that overgrazing by livestock reduces ecosystem functions in shrublands, but that shrubs may buffer the negative effects of increasing grazing. We examined changes in water infiltration and nutrient concentrations in soils under shrubs and in their interspaces in shrublands in eastern Australia that varied in the intensity of livestock grazing. We used structural equation modelling to test whether shrubs might reduce the negative effects of overgrazing on infiltration and soil carbon and nitrogen (henceforth ‘soil nutrients’). Soils under shrubs and subject to low levels of grazing were more stable and had greater levels of soil nutrients. Shrubs had a direct positive effect on soil nutrients; but, grazing negatively affected nutrients by increasing soil bulk density. Structural equation modelling showed that shrubs had a direct positive effect on water flow under ponded conditions but also enhanced water flow, indirectly, through increased litter cover. Any positive effects of shrubs on water flow under low levels of grazing waned at high levels of grazing. Our results indicate that shrubs may reduce the adverse effects of grazing on soil properties. Specifically, shrubs could restrict access to livestock and therefore protect soils and plants beneath their canopies. Low levels of grazing are likely to ensure the retention of soil water and soil carbon and nitrogen in shrubland soils.

Cobar↗
USGS2015

From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

Pedobiologia↗
USGS2015

Landscape structure affects specialists but not generalists in naturally fragmented grasslands

Understanding how biotic communities respond to landscape spatial structure is critically important for conservation management as natural landscapes become increasingly fragmented. However, empirical studies of the effects of spatial structure on plant species richness have found inconsistent results, suggesting that more comprehensive approaches are needed. In this study, we asked how landscape structure affects total plant species richness and the richness of a guild of specialized plants in a multivariate context. We sampled herbaceous plant communities at 56 dolomite glades (insular, fire-adapted grasslands) across the Missouri Ozarks, and used structural equation modeling (SEM) to analyze the relative importance of landscape structure, soil resource availability, and fire history for plant communities. We found that landscape spatial structure-defined as the area-weighted proximity of glade habitat surrounding study sites (proximity index)-had a significant effect on total plant species richness, but only after we controlled for environmental covariates. Richness of specialist species, but not generalists, was positively related to landscape spatial structure. Our results highlight that local environmental filters must be considered to understand the influence of landscape structure on communities, and that unique species guilds may respond differently to landscape structure than the community as a whole. These findings suggest that both local environment and landscape context should be considered when developing management strategies for species of conservation concern in fragmented habitats.

Ecology↗
USGS2015

Structural equation modeling: Building and evaluating causal models

Scientists frequently wish to study hypotheses about causal relationships, rather than just statistical associations. This chapter addresses the question of how scientists might approach this ambitious task. Here we describe structural equation modeling (SEM), a general modeling framework for the study of causal hypotheses. Our goals are to (a) concisely describe the methodology, (b) illustrate its utility for investigating ecological systems, and (c) provide guidance for its application. Throughout our presentation, we rely on a study of the effects of human activities on wetland ecosystems to make our description of methodology more tangible. We begin by presenting the fundamental principles of SEM, including both its distinguishing characteristics and the requirements for modeling hypotheses about causal networks. We then illustrate SEM procedures and offer guidelines for conducting SEM analyses. Our focus in this presentation is on basic modeling objectives and core techniques. Pointers to additional modeling options are also given.

Book chapter↗
USGS2014

Urban sprawl as a risk factor in motor vehicle crashes

A decade ago, compactness/sprawl indices were developed for metropolitan areas and counties which have been widely used in health and other research. In this study, we first update the original county index to 2010, then develop a refined index that accounts for more relevant factors, and finally seek to test the relationship between sprawl and traffic crash rates using structural equation modelling. Controlling for covariates, we find that sprawl is associated with significantly higher direct and indirect effects on fatal crash rates. The direct effect is likely due to the higher traffic speeds in sprawling areas, and the indirect effect is due to greater vehicle miles driven in such areas. Conversely, sprawl has negative direct relationships with total crashes and non-fatal injury crashes, and these offset (and sometimes overwhelm) the positive indirect effects of sprawl on both types of crashes through the mediating effect of increased vehicle miles driven. The most likely explanation is the greater prevalence of fender benders and other minor accidents in the low speed, high conflict traffic environments of compact areas, negating the lower vehicle miles travelled per capita in such areas.

Urban Studies↗
USGS2014

Long-term effects of seeding after wildfire on vegetation in Great Basin shrubland ecosystems

1. Invasive annual grasses alter fire regimes in shrubland ecosystems of the western USA, threatening ecosystem function and fragmenting habitats necessary for shrub-obligate species such as greater sage-grouse. Post-fire stabilization and rehabilitation treatments have been administered to stabilize soils, reduce invasive species spread and restore or establish sustainable ecosystems in which native species are well represented. Long-term effectiveness of these treatments has rarely been evaluated. 2. We studied vegetation at 88 sites where aerial or drill seeding was implemented following fires between 1990 and 2003 in Great Basin (USA) shrublands. We examined sites on loamy soils that burned only once since 1970 to eliminate confounding effects of recurrent fire and to assess soils most conducive to establishment of seeded species. We evaluated whether seeding provided greater cover of perennial seeded species than burned–unseeded and unburned–unseeded sites, while also accounting for environmental variation. 3. Post-fire seeding of native perennial grasses generally did not increase cover relative to burned–unseeded areas. Native perennial grass cover did, however, increase after drill seeding when competitive non-natives were not included in mixes. Seeding non-native perennial grasses and the shrub Bassia prostrata resulted in more vegetative cover in aerial and drill seeding, with non-native perennial grass cover increasing with annual precipitation. Seeding native shrubs, particularly Artemisia tridentata , did not increase shrub cover or density in burned areas. Cover of undesirable, non-native annual grasses was lower in drill seeded relative to unseeded areas, but only at higher elevations. 4. Synthesis and applications. Management objectives are more likely to be met in high-elevation or precipitation locations where establishment of perennial grasses occurred. On lower and drier sites, management objectives are unlikely to be met with seeding alone. Intensive restoration methods such as invasive plant control and/or repeated sowings after establishment failures due to weather may be required in subsequent years. Managers might consider using native-only seed mixtures when establishment of native perennial grasses is the goal. Post-fire rehabilitation provides a land treatment example where long-term monitoring can inform adaptive management decisions to meet future objectives, particularly in arid landscapes where recovery is slow.

Great Basin↗
USGS2014

Causal networks clarify productivity-richness interrelations, bivariate plots do not

Perhaps no other pair of variables in ecology has generated as much discussion as species richness and ecosystem productivity, as illustrated by the reactions by Pierce (2013) and others to Adler et al.'s (2011) report that empirical patterns are weak and inconsistent. Adler et al. (2011) argued we need to move beyond a focus on simplistic bivariate relationships and test mechanistic, multivariate causal hypotheses. We feel the continuing debate over productivity–richness relationships (PRRs) provides a focused context for illustrating the fundamental difficulties of using bivariate relationships to gain scientific understanding. Pierce (2013) disputes Adler et al.'s (2011) conclusion that bivariate productivity–richness relationships (PRRs) are ‘weak and variable’. He argues, instead, that relationships in the Adler et al. data are actually strong and, further, that failure to adhere to the humped-back model (HBM; sensu Grime 1979) threatens scientists' ability to advise conservationists. Here, we show that Pierce's reanalyses are invalid, that statistically significant boundary relations in the Adler et al. data are difficult to detect when proper methods are used and that his advice neither advances scientific understanding nor provides the quantitative forecasts actually needed by decision makers. We begin by examining Grimes' HBM through the lens of causal networks. We first translate the ideas contained in the HBM into a causal diagram, which shows explicitly how multiple processes are hypothesized to control biomass production and richness and their interrelationship. We then evaluate the causal diagram using structural equation modelling and example data from a published study of meadows in Finland. Formal analysis rejects the literal translation of the HBM and reveals additional processes at work. This exercise shows how the practice of abstracting systems as causal networks (i) clarifies possible hypotheses, (ii) permits explicit testing and (iii) provides more powerful and useful predictions. Building on the Finnish meadow example, we contrast the utility of bivariate plots compared with structural equation models for investigating underlying processes. Simulations illustrate the fallibility of bivariate analysis as a means of supporting one theory over another, while models based on causal networks can quantify the sensitivity of diversity patterns to both management and natural constraints. A key piece of Pierce's critique of Adler et al.'s conclusions relies on upper boundary regression which he claims to reveal strong relationships between production and richness in Adler et al.'s original data. We demonstrate that this technique shows strong associations in purely random data and is invalid for Adler et al.'s data because it depends on a uniform data distribution. We instead perform quantile regression on both the site-level summaries of the data and the plot-level data (using mixed-model quantile regression). Using a variety of nonlinear curve-fitting approaches, we were unable to detect a significant humped-shape boundary in the Adler et al. data. We reiterate that the bivariate productivity–richness relationships in Adler et al.'s data are weak and variable. We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.

Functional Ecology↗
USGS2014

Quantifying restoration effectiveness using multi-scale habitat models: implications for sage-grouse in the Great Basin

A recurrent challenge in the conservation of wide-ranging, imperiled species is understanding which habitats to protect and whether we are capable of restoring degraded landscapes. For Greater Sage-grouse (Centrocercus urophasianus), a species of conservation concern in the western United States, we approached this problem by developing multi-scale empirical models of occupancy in 211 randomly located plots within a 40 million ha portion of the species' range. We then used these models to predict sage-grouse habitat quality at 826 plots associated with 101 post-wildfire seeding projects implemented from 1990 to 2003. We also compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe prevalence, and negatively associated with non-native plants and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.09) and not substantially different from burned areas that had not been treated. Restoration sites with quality habitat tended to occur at higher elevation locations with low annual temperatures, high spring precipitation, and high plant diversity. Of 313 plots seeded after fire, none met all sagebrush guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This pattern was similar for summer habitat. Less than 2% of treated plots met winter habitat guidelines. Restoration actions did not increase the probability of burned areas meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, climate, and topography. Our results suggest that sage-grouse are relatively unlikely to use many burned areas within 20 years of fire, regardless of treatment. Understory habitat conditions are more likely to be adequate than overstory conditions, but in most climates, establishing forbs and reducing cheatgrass dominance is unlikely. Reestablishing sagebrush cover will require more than 20 years using past restoration methods. Given current fire frequencies and restoration capabilities, protection of landscapes containing a mix of dwarf sagebrush and big sagebrush steppe, minimal human development, and low non-native plant cover may provide the best opportunity for conservation of sage-grouse habitats.

Ecosphere↗
USGS2014

Structural equation models of VMT growth in US urbanised areas.

Vehicle miles travelled (VMT) is a primary performance indicator for land use and transportation, bringing with it both positive and negative externalities. This study updates and refines previous work on VMT in urbanised areas, using recent data, additional metrics and structural equation modelling (SEM). In a cross-sectional model for 2010, population, income and freeway capacity are positively related to VMT, while gasoline prices, development density and transit service levels are negatively related. Findings of the cross-sectional model are generally confirmed in a more tightly controlled longitudinal study of changes in VMT between 2000 and 2010, the first model of its kind. The cross-sectional and longitudinal models together, plus the transportation literature generally, give us a basis for generalising across studies to arrive at elasticity values of VMT with respect to different urban variables.

Urban Studies↗
USGS2014

Getting the message across: using ecological integrity to communicate with resource managers

This chapter describes and illustrates how concepts of ecological integrity, thresholds, and reference conditions can be integrated into a research and monitoring framework for natural resource management. Ecological integrity has been defined as a measure of the composition, structure, and function of an ecosystem in relation to the system’s natural or historical range of variation, as well as perturbations caused by natural or anthropogenic agents of change. Using ecological integrity to communicate with managers requires five steps, often implemented iteratively: (1) document the scale of the project and the current conceptual understanding and reference conditions of the ecosystem, (2) select appropriate metrics representing integrity, (3) define externally verified assessment points (metric values that signify an ecological change or need for management action) for the metrics, (4) collect data and calculate metric scores, and (5) summarize the status of the ecosystem using a variety of reporting methods. While we present the steps linearly for conceptual clarity, actual implementation of this approach may require addressing the steps in a different order or revisiting steps (such as metric selection) multiple times as data are collected. Knowledge of relevant ecological thresholds is important when metrics are selected, because thresholds identify where small changes in an environmental driver produce large responses in the ecosystem. Metrics with thresholds at or just beyond the limits of a system’s range of natural variability can be excellent, since moving beyond the normal range produces a marked change in their values. Alternatively, metrics with thresholds within but near the edge of the range of natural variability can serve as harbingers of potential change. Identifying thresholds also contributes to decisions about selection of assessment points. In particular, if there is a significant resistance to perturbation in an ecosystem, with threshold behavior not occurring until well beyond the historical range of variation, this may provide a scientific basis for shifting an ecological assessment point beyond the historical range. We present two case studies using ongoing monitoring by the US National Park Service Vital Signs program that illustrate the use of an ecological integrity approach to communicate ecosystem status to resource managers. The Wetland Ecological Integrity in Rocky Mountain National Park case study uses an analytical approach that specifically incorporates threshold detection into the process of establishing assessment points. The Forest Ecological Integrity of Northeastern National Parks case study describes a method for reporting ecological integrity to resource managers and other decision makers. We believe our approach has the potential for wide applicability for natural resource management.

Book chapter↗