Geology topics

James B. Grace

Publications and source records attributed to James B. Grace.

At least 73 records · Page 4Linked to original sources

USGS2014

Functional diversity supports the physiological tolerance hypothesis for plant species richness along climatic gradients

1. The physiological tolerance hypothesis proposes that plant species richness is highest in warm and/or wet climates because a wider range of functional strategies can persist under such conditions. Functional diversity metrics, combined with statistical modeling, offer new ways to test whether diversity-environment relationships are consistent with this hypothesis. 2. In a classic study by R. H. Whittaker (1960), herb species richness declined from mesic (cool, moist, northerly) slopes to xeric (hot, dry, southerly) slopes. Building on this dataset, we measured four plant functional traits (plant height, specific leaf area, leaf water content and foliar C:N) and used them to calculate three functional diversity metrics (functional richness, evenness, and dispersion). We then used a structural equation model to ask if ‘functional diversity’ (modeled as the joint responses of richness, evenness, and dispersion) could explain the observed relationship of topographic climate gradients to species richness. We then repeated our model examining the functional diversity of each of the four traits individually. 3. Consistent with the physiological tolerance hypothesis, we found that functional diversity was higher in more favorable climatic conditions (mesic slopes), and that multivariate functional diversity mediated the relationship of the topographic climate gradient to plant species richness. We found similar patterns for models focusing on individual trait functional diversity of leaf water content and foliar C:N. 4. Synthesis. Our results provide trait-based support for the physiological tolerance hypothesis, suggesting that benign climates support more species because they allow for a wider range of functional strategies.

Oregon↗

USGS2014

Resilience and resistance of sagebrush ecosystems: implications for state and transition models and management treatments

In sagebrush ecosystems invasion of annual exotics and expansion of piñon ( Pinus monophylla Torr. and Frem.) and juniper ( Juniperus occidentalis Hook., J. osteosperma [Torr.] Little) are altering fire regimes and resulting in large-scale ecosystem transformations. Management treatments aim to increase resilience to disturbance and enhance resistance to invasive species by reducing woody fuels and increasing native perennial herbaceous species. We used Sagebrush Steppe Treatment Evaluation Project data to test predictions on effects of fire vs. mechanical treatments on resilience and resistance for three site types exhibiting cheatgrass ( Bromus tectorum L.) invasion and/or piñon and juniper expansion: 1) warm and dry Wyoming big sagebrush (WY shrub); 2) warm and moist Wyoming big sagebrush (WY PJ); and 3) cool and moist mountain big sagebrush (Mtn PJ). Warm and dry (mesic/aridic) WY shrub sites had lower resilience to fire (less shrub recruitment and native perennial herbaceous response) than cooler and moister (frigid/xeric) WY PJ and Mtn PJ sites. Warm (mesic) WY Shrub and WY PJ sites had lower resistance to annual exotics than cool (frigid to cool frigid) Mtn PJ sites. In WY shrub, fire and sagebrush mowing had similar effects on shrub cover and, thus, on perennial native herbaceous and exotic cover. In WY PJ and Mtn PJ, effects were greater for fire than cut-and-leave treatments and with high tree cover in general because most woody vegetation was removed increasing resources for other functional groups. In WY shrub, about 20% pretreatment perennial native herb cover was necessary to prevent increases in exotics after treatment. Cooler and moister WY PJ and especially Mtn PJ were more resistant to annual exotics, but perennial native herb cover was still required for site recovery. We use our results to develop state and transition models that illustrate how resilience and resistance influence vegetation dynamics and management options.

Rangeland Ecology and Management↗

USGS2014

Connecting the dots: a collaborative USGS-NPS effort to expand the utility of monitoring data

The Natural Resource Challenge (National Park Service 1999) was a call to action. It constituted a mandate for monitoring based on the twin premises that (1) natural resources in national parks require active management and stewardship if we are to protect them from gradual degradation, and (2) we cannot protect what we do not understand. The intent of the challenge was embodied in its original description: We must expand existing inventory programs and develop efficient ways to monitor the vital signs of natural systems. We must enlist others in the scientific community to help, and also facilitate their inquiry. Managers must have and apply this information to preserve our natural resources. In this article, we report on ongoing collaborative work between the National Park Service (NPS) and the US Geological Survey (USGS) that seeks to add to our scientific understanding of the ecological processes operating behind vital signs monitoring data. The ultimate goal of this work is to provide insights that can facilitate an understanding of the systems and identify potential opportunities for active stewardship by NPS managers (Bennetts et al. 2007; Mitchell et al. 2014). The bulk of the work thus far has involved Acadia and Rocky Mountain national parks, but there are plans for extending the work to additional parks. Our story stats with work designed to consider ways of assessing the status and condition of natural resources and the potential for historical or ongoing influences of human activities. In the 1990s, the concept of "biotic integrity" began to take hold as an aspiration for developing quantitative indices describing how closely the conditions at a site resemble those found at pristine, unimpacted sites. Quantitative methods for developing indices of biotic integrity (IBIs) and elaborations of that idea (e.g., ecological integrity) have received considerable attention and application of these methods to natural resources has become widespread (Karr 1991; Barbour et al. 1999; Stoddard et al. 2008). Despite widespread use, many questions remain about how metrics are combined to form effective indices and about how to interpret both. Scientists and natural resource specialists within NPS and USGS have joined forces to critique the current analysis methods, with the collaboration involving the Rocky Mountain and Northeast Temperate NPS Inventory and Monitoring (I & M) networks, along with others, and USGS scientists from the National Wetlands Research Center and Patuxent Wildlife Research Center. Funding that initiated the project was from a joint-partnership fund managed by the USGS Ecosystems Program for National Park Monitoring research and the work was focused at Acadia National Park and Rocky Mountain National Park. Here we present synopses of two major issues addressed by the group.

The George Wright Forum↗

USGS2013

Resilience to stress and disturbance, and resistance to Bromus tectorum L. invasion in cold desert shrublands of western North America

Alien grass invasions in arid and semi-arid ecosystems are resulting in grass–fire cycles and ecosystem-level transformations that severely diminish ecosystem services. Our capacity to address the rapid and complex changes occurring in these ecosystems can be enhanced by developing an understanding of the environmental factors and ecosystem attributes that determine resilience of native ecosystems to stress and disturbance, and resistance to invasion. Cold desert shrublands occur over strong environmental gradients and exhibit significant differences in resilience and resistance. They provide an excellent opportunity to increase our understanding of these concepts. Herein, we examine a series of linked questions about (a) ecosystem attributes that determine resilience and resistance along environmental gradients, (b) effects of disturbances like livestock grazing and altered fire regimes and of stressors like rapid climate change, rising CO 2 , and N deposition on resilience and resistance, and (c) interacting effects of resilience and resistance on ecosystems with different environmental conditions. We conclude by providing strategies for the use of resilience and resistance concepts in a management context. At ecological site scales, state and transition models are used to illustrate how differences in resilience and resistance influence potential alternative vegetation states, transitions among states, and thresholds. At landscape scales management strategies based on resilience and resistance—protection, prevention, restoration, and monitoring and adaptive management—are used to determine priority management areas and appropriate actions.

Ecosystems↗

USGS2013

Evidence that acidification-induced declines in plant diversity and productivity are mediated by changes in below-ground communities and soil properties in a semi-arid steppe

Anthropogenic acid deposition–induced soil acidification is one of the major threats to biodiversity, ecosystem functioning and services. Few studies, however, have explored in detail how above-ground changes in plant species richness and productivity resulting from soil acidification are mediated by effects on below-ground biota and soil properties. To increase our understanding of this linkage, we collected data on below- and above-ground communities and soil properties in a 3-year field experiment with seven levels of acid addition rate to build-up broad intensities of soil acidification in the semi-arid Inner Mongolian grassland. Acid addition directly elevated concentrations of soil Al 3+ ions, decreased the base cations Ca 2+ , Mg 2+ and Na + , and increased soil moisture and available phosphorus. Acid addition also appears to have altered the soil microbial community via changes in H + and Al 3+ ions and altered the nematode community via changes in H + ions and soil moisture. The observed changes in soil N availability (i.e. net N mineralization, NO 3 - -N and NH 4 + -N) could be explained by mediating changes in the H + and Al 3+ ions, microbial community (i.e. community structure, bacteria and fungi/bacteria as indicated by phospholipid fatty acids analysis) and the nematode community (i.e. total abundance, taxa richness and maturity index). Declines in plant species richness and productivity were greater at high intensities of soil acidification in the second sampling year than in the first sampling year. The changes in plant community observed were mostly explained by soil nutrient pathways (e.g. N availability or base mineral cations), which were in turn regulated by the soil microbial or nematode communities as well as by the direct effects of the increase in H + or Al 3+ ions. Synthesis. Our results suggest that the below-ground microbial and nematode communities are more sensitive to soil acidification than the plant communities are, and further that soil acidification–induced changes in plants are mediated by changes in below-ground communities and soil nutrients. These findings improve our understanding of the links between below- and above-ground communities in the Inner Mongolia grassland, especially in the context of anthropogenic acid enrichment.

Inner Mongolia↗

USGS2013

Conditions favouring Bromus tectorum dominance of endangered sagebrush steppe ecosystems

1. Ecosystem invasibility is determined by combinations of environmental variables, invader attributes, disturbance regimes, competitive abilities of resident species and evolutionary history between residents and disturbance regimes. Understanding the relative importance of each factor is critical to limiting future invasions and restoring ecosystems. 2. We investigated factors potentially controlling Bromus tectorum invasions into Artemisia tridentata ssp. wyomingensis communities across 75 sites in the Great Basin. We measured soil texture, cattle grazing intensity, gaps among perennial plants and plant cover including B. tectorum, biological soil crusts (BSCs) and bare soil. Using a priori knowledge, we developed a multivariate hypothesis of the susceptibility of Artemisia ecosystems to B. tectorum invasion and used the model to assess the relative importance of the factors driving the magnitude of such invasions. 3. Model results imply that bunchgrass community structure, abundance and composition, along with BSC cover, play important roles in controlling B. tectorum dominance. Evidence suggests abundant bunchgrasses limit invasions by limiting the size and connectivity of gaps between vegetation, and BSCs appear to limit invasions within gaps. Results also suggest that cattle grazing reduces invasion resistance by decreasing bunchgrass abundance, shifting bunchgrass composition, and thereby increasing connectivity of gaps between perennial plants while trampling further reduces resistance by reducing BSC. 4. Synthesis and applications. Grazing exacerbates Bromus tectorum dominance in one of North America's most endangered ecosystems by adversely impacting key mechanisms mediating resistance to invasion. If the goal is to conserve and restore resistance of these systems, managers should consider maintaining or restoring: (i) high bunchgrass cover and structure characterized by spatially dispersed bunchgrasses and small gaps between them; (ii) a diverse assemblage of bunchgrass species to maximize competitive interactions with B. tectorum in time and space; and (iii) biological soil crusts to limit B. tectorum establishment. Passive restoration by reducing cumulative cattle grazing may be one of the most effective means of achieving these three goals.

Journal of Applied Ecology↗

USGS2013

Predicting ecosystem stability from community composition and biodiversity

As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species’ responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22–75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability.

Ecology Letters↗

USGS2013

Combined effects of compact cevelopment, transportation investments, and road user pricing on vehicle miles traveled in urbanized areas

Vehicle miles traveled (VMT) is the primary determinant of traffic congestion, vehicle crashes, greenhouse gas emissions, and other effects of transportation. Two previous studies have sought to explain VMT levels in urbanized areas. This study updates and expands on previous work with more recent data, additional metrics, and structural equation modeling (SEM) to explain VMT levels in 315 urbanized areas. According to SEM, population, income, and gasoline prices are primary exogenous drivers of VMT. Development density is a primary endogenous driver. Urbanized areas with more freeway capacity are significantly less dense and have significantly higher VMT per capita. Areas with more transit service coverage and service frequency have higher development densities and per capita transit use, which leads to lower VMT per capita. The indirect effect of transit on VMT through land use, the so-called land use multiplier, is more than three times greater than the direct effect through transit ridership.

Transportation Research Record↗

USGS2013

An algorithmic and information-theoretic approach to multimetric index construction

The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified 4 metrics that combined to produce a -0.88 correlation with the human disturbance index. When compared to other methods, we find this algorithmic approach resulted in MMIs that were more predictive and comprise fewer metrics.

Ecological Indicators↗

USGS2013

A causal examination of the effects of confounding factors on multimetric indices

The development of multimetric indices (MMIs) as a means of providing integrative measures of ecosystem condition is becoming widespread. An increasingly recognized problem for the interpretability of MMIs is controlling for the potentially confounding influences of environmental covariates. Most common approaches to handling covariates are based on simple notions of statistical control, leaving the causal implications of covariates and their adjustment unstated. In this paper, we use graphical models to examine some of the potential impacts of environmental covariates on the observed signals between human disturbance and potential response metrics. Using simulations based on various causal networks, we show how environmental covariates can both obscure and exaggerate the effects of human disturbance on individual metrics. We then examine from a causal interpretation standpoint the common practice of adjusting ecological metrics for environmental influences using only the set of sites deemed to be in reference condition. We present and examine the performance of an alternative approach to metric adjustment that uses the whole set of sites and models both environmental and human disturbance effects simultaneously. The findings from our analyses indicate that failing to model and adjust metrics can result in a systematic bias towards those metrics in which environmental covariates function to artificially strengthen the metric–disturbance relationship resulting in MMIs that do not accurately measure impacts of human disturbance. We also find that a “whole-set modeling approach” requires fewer assumptions and is more efficient with the given information than the more commonly applied “reference-set” approach.

Ecological Indicators↗

USGS2013

How does pedogenesis drive plant diversity?

Some of the most species-rich plant communities occur on ancient, strongly weathered soils, whereas those on recently developed soils tend to be less diverse. Mechanisms underlying this well-known pattern, however, remain unresolved. Here, we present a conceptual model describing alternative mechanisms by which pedogenesis (the process of soil formation) might drive plant diversity. We suggest that long-term soil chronosequences offer great, yet largely untapped, potential as 'natural experiments' to determine edaphic controls over plant diversity. Finally, we discuss how our conceptual model can be evaluated quantitatively using structural equation modeling to advance multivariate theories about the determinants of local plant diversity. This should help us to understand broader-scale diversity patterns, such as the latitudinal gradient of plant diversity.

Trends in Ecology and Evolution↗

USGS2013

Temporal shifts in top-down vs. bottom-up control of epiphytic algae in a seagrass ecosystem

In coastal marine food webs, small invertebrate herbivores (mesograzers) have long been hypothesized to occupy an important position facilitating dominance of habitat-forming macrophytes by grazing competitively superior epiphytic algae. Because of the difficulty of manipulating mesograzers in the field, however, their impacts on community organization have rarely been rigorously documented. Understanding mesograzer impacts has taken on increased urgency in seagrass systems due to declines in seagrasses globally, caused in part by widespread eutrophication favoring seagrass overgrowth by faster-growing algae. Using cage-free field experiments in two seasons (fall and summer), we present experimental confirmation that mesograzer reduction and nutrients can promote blooms of epiphytic algae growing on eelgrass ( Zostera marina ). In this study, nutrient additions increased epiphytes only in the fall following natural decline of mesograzers. In the summer, experimental mesograzer reduction stimulated a 447% increase in epiphytes, appearing to exacerbate seasonal dieback of eelgrass. Using structural equation modeling, we illuminate the temporal dynamics of complex interactions between macrophytes, mesograzers, and epiphytes in the summer experiment. An unexpected result emerged from investigating the interaction network: drift macroalgae indirectly reduced epiphytes by providing structure for mesograzers, suggesting that the net effect of macroalgae on seagrass depends on macroalgal density. Our results show that mesograzers can control proliferation of epiphytic algae, that top-down and bottom-up forcing are temporally variable, and that the presence of macroalgae can strengthen top-down control of epiphytic algae, potentially contributing to eelgrass persistence.

Ecology↗

USGS2013

Streams in the urban heat island: spatial and temporal variability in temperature

Streams draining urban heat islands tend to be hotter than rural and forested streams at baseflow because of warmer urban air and ground temperatures, paved surfaces, and decreased riparian canopy. Urban infrastructure efficiently routes runoff over hot impervious surfaces and through storm drains directly into streams and can lead to rapid, dramatic increases in temperature. Thermal regimes affect habitat quality and biogeochemical processes, and changes can be lethal if temperatures exceed upper tolerance limits of aquatic fauna. In summer 2009, we collected continuous (10-min interval) temperature data in 60 streams spanning a range of development intensity in the Piedmont of North Carolina, USA. The 5 most urbanized streams averaged 21.1°C at baseflow, compared to 19.5°C in the 5 most forested streams. Temperatures in urban streams rose as much as 4°C during a small regional storm, whereas the same storm led to extremely small to no changes in temperature in forested streams. Over a kilometer of stream length, baseflow temperature varied by as much as 10°C in an urban stream and as little as 2°C in a forested stream. We used structural equation modeling to explore how reach- and catchment-scale attributes interact to explain maximum temperatures and magnitudes of storm-flow temperature surges. The best predictive model of baseflow temperatures (R 2 = 0.461) included moderately strong pathways directly (extent of development and road density) and indirectly, as mediated by reach-scale factors (canopy closure and stream width), from catchment-scale factors. The strongest influence on storm-flow temperature surges appeared to be % development in the catchment. Reach-scale factors, such as the extent of riparian forest and stream width, had little mitigating influence (R 2 = 0.448). Stream temperature is an essential, but overlooked, aspect of the urban stream syndrome and is affected by reach-scale habitat variables, catchment-scale urbanization, and stream thermal regimes.

Freshwater Science↗

USGS2012

Direct and indirect effects of land use on floral resources and flower-visiting insects across an urban landscape

Although urban areas are often considered to have uniformly negative effects on biodiversity, cities are most accurately characterized as heterogeneous mosaics of buildings, streets, parks, and gardens that include both ‘good’ and ‘bad’ areas for wildlife. However, to date, few studies have evaluated how human impacts vary in direction and magnitude across a heterogeneous urban landscape. In this study, we assessed the distribution of floral resources and flower-visiting insects across a variety of land uses in New York City. We visited both green spaces (e.g. parks, cemeteries) and heavily developed neighborhood blocks (e.g. with high or low density residential zoning) and used structural equation modeling (SEM) to evaluate the direct and indirect effects of median income, vegetation, and development intensity on floral resources and insects in both settings. Abundance and taxonomic richness of flower-visiting insects was significantly greater in green spaces than neighborhood blocks. The SEM results indicated that heavily-developed neighborhoods generally had fewer flower-visiting insects consistent with reductions in floral resources. However, some low-density residential neighborhoods maintained high levels of floral resources and flower-visiting insects. We found that the effects of surrounding vegetation on floral resources, and thus indirect effects on insects, varied considerably between green spaces and neighborhood blocks. Along neighborhood blocks, vegetation consisted of a mosaic of open gardens and sparsely distributed trees and had a positive indirect effect on flower-visiting insects. In contrast, vegetation in urban green spaces was associated with increased canopy cover and thus had a negative indirect effect on flower-visiting insects through reductions in floral resources. In both neighborhood blocks and green spaces, vegetation had a positive direct effect on flower-visiting insects independent of the influence of vegetation on floral resources. Our results demonstrate how inter-related components of an urban ecosystem can vary with respect to one another across a heterogeneous urban landscape, suggesting that it is inappropriate to generalize about urban systems as a whole without first addressing differences among component land use types.

Oikos↗

USGS2012

Guidelines for a graph-theoretic implementation of structural equation modeling

Structural equation modeling (SEM) is increasingly being chosen by researchers as a framework for gaining scientific insights from the quantitative analyses of data. New ideas and methods emerging from the study of causality, influences from the field of graphical modeling, and advances in statistics are expanding the rigor, capability, and even purpose of SEM. Guidelines for implementing the expanded capabilities of SEM are currently lacking. In this paper we describe new developments in SEM that we believe constitute a third-generation of the methodology. Most characteristic of this new approach is the generalization of the structural equation model as a causal graph. In this generalization, analyses are based on graph theoretic principles rather than analyses of matrices. Also, new devices such as metamodels and causal diagrams, as well as an increased emphasis on queries and probabilistic reasoning, are now included. Estimation under a graph theory framework permits the use of Bayesian or likelihood methods. The guidelines presented start from a declaration of the goals of the analysis. We then discuss how theory frames the modeling process, requirements for causal interpretation, model specification choices, selection of estimation method, model evaluation options, and use of queries, both to summarize retrospective results and for prospective analyses. The illustrative example presented involves monitoring data from wetlands on Mount Desert Island, home of Acadia National Park. Our presentation walks through the decision process involved in developing and evaluating models, as well as drawing inferences from the resulting prediction equations. In addition to evaluating hypotheses about the connections between human activities and biotic responses, we illustrate how the structural equation (SE) model can be queried to understand how interventions might take advantage of an environmental threshold to limit Typha invasions. The guidelines presented provide for an updated definition of the SEM process that subsumes the historical matrix approach under a graph-theory implementation. The implementation is also designed to permit complex specifications and to be compatible with various estimation methods. Finally, they are meant to foster the use of probabilistic reasoning in both retrospective and prospective considerations of the quantitative implications of the results.

Ecosphere↗

USGS2012

Biodiversity loss and its impact on humanity

The most unique feature of Earth is the existence of life, and the most extraordinary feature of life is its diversity. Approximately 9 million types of plants, animals, protists and fungi inhabit the Earth. So, too, do 7 billion people. Two decades ago, at the first Earth Summit, the vast majority of the world's nations declared that human actions were dismantling the Earth's ecosystems, eliminating genes, species and biological traits at an alarming rate. This observation led to the question of how such loss of biological diversity will alter the functioning of ecosystems and their ability to provide society with the goods and services needed to prosper.

Nature↗

USGS2012

A general theory of multimetric indices and their properties

1. Stewardship of biological and ecological resources requires the ability to make integrative assessments of ecological integrity. One of the emerging methods for making such integrative assessments is multimetric indices (MMIs). These indices synthesize data, often from multiple levels of biological organization, with the goal of deriving a single index that reflects the overall effects of human disturbance. Despite the widespread use of MMIs, there is uncertainty about why this approach can be effective. An understanding of MMIs requires a quantitative theory that illustrates how the properties of candidate metrics relates to MMIs generated from those metrics. 2. We present the initial basis for such a theory by deriving the general mathematical characteristics of MMIs assembled from metrics. We then use the theory to derive quantitative answers to the following questions: Is there an optimal number of metrics to comprise an index? How does covariance among metrics affect the performance of the index derived from those metrics? And what are the criteria to decide whether a given metric will improve the performance of an index? 3. We find that the optimal number of metrics to be included in an index depends on the theoretical distribution of signal of the disturbance gradient contained in each metric. For example, if the rank-ordered parameters of a metric-disturbance regression can be described by a monotonically decreasing function, then an optimum number of metrics exists and can often be derived analytically. We derive the conditions by which adding a given metric can be expected to improve an index. 4. We find that the criterion defining such conditions depends nonlinearly of the signal of the disturbance gradient, the noise (error) of the metric and the correlation of the metric errors. Importantly, we find that correlation among metric errors increases the signal required for the metric to improve the index. 5. The theoretical framework presented in this study provides the basis for understanding the properties of MMIs. It can also be useful throughout the index construction process. Specifically, it can be used to aid understanding of the benefits and limitations of combining metrics into indices; it can inform selection/collection of candidate metrics; and it can be used directly as a decision aid in effective index construction.

Methods in Ecology and Evolution↗

USGS2012

Response to comments on "Productivity is a poor predictor of plant species richness"

Pan et al. claim that our results actually support a strong linear positive relationship between productivity and richness, whereas Fridley et al. contend that the data support a strong humped relationship. These responses illustrate how preoccupation with bivariate patterns distracts from a deeper understanding of the multivariate mechanisms that control these important ecosystem properties.

Science↗