Julian D. Olden

Homogenization of regional river dynamics by dams and global biodiversity implications.

Global biodiversity in river and riparian ecosystems is generated and maintained by geographic variation in stream processes and fluvial disturbance regimes, which largely reflect regional differences in climate and geology. Extensive construction of dams by humans has greatly dampened the seasonal and interannual streamflow variability of rivers, thereby altering natural dynamics in ecologically important flows on continental to global scales. The cumulative effects of modification to regional-scale environmental templates caused by dams is largely unexplored but of critical conservation importance. Here, we use 186 long-term streamflow records on intermediate-sized rivers across the continental United States to show that dams have homogenized the flow regimes on third- through seventh-order rivers in 16 historically distinctive hydrologic regions over the course of the 20th century. This regional homogenization occurs chiefly through modification of the magnitude and timing of ecologically critical high and low flows. For 317 undammed reference rivers, no evidence for homogenization was found, despite documented changes in regional precipitation over this period. With an estimated average density of one dam every 48 km of third- through seventh-order river channel in the United States, dams arguably have a continental scale effect of homogenizing regionally distinct environmental templates, thereby creating conditions that favor the spread of cosmopolitan, nonindigenous species at the expense of locally adapted native biota. Quantitative analyses such as ours provide the basis for conservation and management actions aimed at restoring and maintaining native biodiversity and ecosystem function and resilience for regionally distinct ecosystems at continental to global scales.

Assessing the Effects of Climate Change on Aquatic Invasive Species

Different components of global environmental change are typically studied and managed independently, although there is a growing recognition that multiple drivers often interact in complex and nonadditive ways. We present a conceptual framework and empirical review of the interactive effects of climate change and invasive species in freshwater ecosystems. Climate change is expected to result in warmer water temperatures, shorter duration of ice cover, altered streamflow patterns, increased salinization, and increased demand for water storage and conveyance structures. These changes will alter the pathways by which non-native species enter aquatic systems by expanding fish-culture facilities and water gardens to new areas and by facilitating the spread of species during floods. Climate change will influence the likelihood of new species becoming established by eliminating cold temperatures or winter hypoxia that currently prevent survival and by increasing the construction of reservoirs that serve as hotspots for invasive species. Climate change will modify the ecological impacts of invasive species by enhancing their competitive and predatory effects on native species and by increasing the virulence of some diseases. As a result of climate change, new prevention and control strategies such as barrier construction or removal efforts may be needed to control invasive species that currently have only moderate effects or that are limited by seasonally unfavorable conditions. Although most researchers focus on how climate change will increase the number and severity of invasions, some invasive coldwater species may be unable to persist under the new climate conditions. Our findings highlight the complex interactions between climate change and invasive species that will influence how aquatic ecosystems and their biota will respond to novel environmental conditions.

Illuminating the ''black box'': a randomization approach for understanding variable contributions in artificial neural networks

Abstract With the growth of statistical modeling in the ecological sciences, researchers are using more complex methods, such as artificial neural networks (ANNs), to address problems associated with pattern recognition and prediction. Although in many studies ANNs have been shown to exhibit superior predictive power compared to traditional approaches, they have also been labeled a “black box” because they provide little explanatory insight into the relative influence of the independent variables in the prediction process. This lack of explanatory power is a major concern to ecologists since the interpretation of statistical models is desirable for gaining knowledge of the causal relationships driving ecological phenomena. In this study, we describe a number of methods for understanding the mechanics of ANNs (e.g. Neural Interpretation Diagram, Garsons algorithm, sensitivity analysis). Next, we propose and demonstrate a randomization approach for statistically assessing the importance of axon connection weights and the contribution of input variables in the neural network. This approach provides researchers with the ability to eliminate null-connections between neurons whose weights do not significantly influence the network output (i.e. predicted response variable), thus facilitating the interpretation of individual and interacting contributions of the input variables in the network. Furthermore, the randomization approach can identify variables that significantly contribute to network predictions, thereby providing a variable selection method for ANNs. We show that by extending randomization approaches to ANNs, the “black box” mechanics of ANNs can be greatly illuminated. Thus, by coupling this new explanatory power of neural networks with its strong predictive abilities, ANNs promise to be a valuable quantitative tool to evaluate, understand, and predict ecological phenomena.

Functional trait niches of North American lotic insects: traits-based ecological applications in light of phylogenetic relationships

Abstract The use of species traits to characterize the functional composition of benthic invertebrate communities has become well established in the ecological literature. This approach holds much potential for predicting changes of both species and species assemblages along environmental gradients in terms of traits that are sensitive to local environmental conditions. Further, in the burgeoning field of biomonitoring, a functional approach provides a predictive basis for understanding community-level responses along gradients of environmental alteration caused by humans. Despite much progress in recent years, the full potential of the functional traits-based approach is currently limited by several factors, both conceptual and methodological. Most notably, we lack adequate understanding of how individual traits are intercorrelated and how this lack of independence among traits reflects phylogenetic (evolutionary) constraint. A better understanding is needed if we are to make the transition from a largely univariate approach that considers single-trait responses along single environmental gradients to a multivariate one that more realistically accounts for the responses of many traits across multiple environmental gradients characteristic of most human-dominated landscapes. Our primary objective in this paper is to explore the issue of inter-trait correlations for lotic insects and to identify opportunities and challenges for advancing the theory and application of traits-based approaches in stream community ecology. We created a new database on species-trait composition of North American lotic insects. Using published accounts and expert opinion, we collected information on 20 species traits (in 59 trait states) that fell into 4 broad categories: life-history, morphological, mobility, and ecological. First, we demonstrate the importance of considering how the linkage of specific trait states within a taxon is critical to developing a more-robust traits-based community ecology. Second, we examine the statistical correlations among traits and trait states for the 311 taxa to identify trait syndromes and specify which traits provide unique (uncorrelated) information that can be used to guide trait selection in ecological studies. Third, we examine the evolutionary associations among traits by mapping trait states onto a phylogentic tree derived from morphological and molecular analyses and classifications from the literature. We examine the evolutionary lability of individual traits by assessing the extent to which they are unconstrained by phylogenic relationships across the taxa. By focusing on the lability of traits within lotic genera of Ephemeroptera, Plecoptera, and Trichoptera, taxa often used as water-quality indicators, we show how a traits-based approach can allow a priori expectations of the differential response of these taxa to specific environmental gradients. We conclude with some ideas about how specific trait linkages, statistical correlations among traits, and evolutionary lability of traits can be used in combination with a mechanistic understanding of trait response along environmental gradients to select robust traits useful for a more predictive community ecology. We indicate how these new insights can direct the research in statistical modeling that is necessary to achieve the full potential of models that can predict how multiple traits will respond along multiple environmental gradients.

The potential conservation value of non-native species.

Non-native species can cause the loss of biological diversity (i.e., genetic, species, and ecosystem diversity) and threaten the well-being of humans when they become invasive. In some cases, however, they can also provide conservation benefits. We examined the ways in which non-native species currently contribute to conservation objectives. These include, for example, providing habitat or food resources to rare species, serving as functional substitutes for extinct taxa, and providing desirable ecosystem functions. We speculate that non-native species might contribute to achieving conservation goals in the future because they may be more likely than native species to persist and provide ecosystem services in areas where climate and land use are changing rapidly and because they may evolve into new and endemic taxa. The management of non-native species and their potential integration into conservation plans depends on how conservation goals are set in the future. A fraction of non-native species will continue to cause biological and economic damage, and substantial uncertainty surrounds the potential future effects of all non-native species. Nevertheless, we predict the proportion of non-native species that are viewed as benign or even desirable will slowly increase over time as their potential contributions to society and to achieving conservation objectives become well recognized and realized.

Process-based Principles for Restoring River Ecosystems

Process-based restoration aims to reestablish normative rates and magnitudes of physical, chemical, and biological processes that sustain river and floodplain ecosystems. Ecosystem conditions at any site are governed by hierarchical regional, watershed, and reach-scale processes controlling hydrologic and sediment regimes; floodplain and aquatic habitat dynamics; and riparian and aquatic biota. We outline and illustrate four process-based principles that ensure river restoration will be guided toward sustainable actions: (1) restoration actions should address the root causes of degradation, (2) actions must be consistent with the physical and biological potential of the site, (3) actions should be at a scale commensurate with environmental problems, and (4) actions should have clearly articulated expected outcomes for ecosystem dynamics. Applying these principles will help avoid common pitfalls in river restoration, such as creating habitat types that are outside of a sites natural potential, attempting to build static habitats in dynamic environments, or constructing habitat features that are ultimately overwhelmed by unconsidered system drivers.

Machine Learning Methods Without Tears: A Primer for Ecologists

Machine learning methods, a family of statistical techniques with origins in the field of artificial intelligence, are recognized as holding great promise for the advancement of understanding and prediction about ecological phenomena. These modeling techniques are flexible enough to handle complex problems with multiple interacting elements and typically outcompete traditional approaches (e.g., generalized linear models), making them ideal for modeling ecological systems. Despite their inherent advantages, a review of the literature reveals only a modest use of these approaches in ecology as compared to other disciplines. One potential explanation for this lack of interest is that machine learning techniques do not fall neatly into the class of statistical modeling approaches with which most ecologists are familiar. In this paper, we provide an introduction to three machine learning approaches that can be broadly used by ecologists: classification and regression trees, artificial neural networks, and evolutionary computation. For each approach, we provide a brief background to the methodology, give examples of its application in ecology, describe model development and implementation, discuss strengths and weaknesses, explore the availability of statistical software, and provide an illustrative example. Although the ecological application of machine learning approaches has increased, there remains considerable skepticism with respect to the role of these techniques in ecology. Our review encourages a greater understanding of machine learning approaches and promotes their future application and utilization, while also providing a basis from which ecologists can make informed decisions about whether to select or avoid these approaches in their future modeling endeavors.

Dam invaders: impoundments facilitate biological invasions into freshwaters

Freshwater ecosystems are at the forefront of the global biodiversity crisis, with more declining and extinct species than in terrestrial or marine environments. Hydrologic alterations and biological invasions represent two of the greatest threats to freshwater biota, yet the importance of linkages between these drivers of environmental change remains uncertain. Here, we quantitatively test the hypothesis that impoundments facilitate the introduction and establishment of aquatic invasive species in lake ecosystems. By combining data on boating activity, water body physicochemistry, and geographical distribution of five nuisance invaders in the Laurentian Great Lakes region, we show that non-indigenous species are 2.4 to 300 times more likely to occur in impoundments than in natural lakes, and that impoundments frequently support multiple invaders. Furthermore, comparisons of the contemporary and historical landscapes revealed that impoundments enhance the invasion risk of natural lakes by increasing their...

Toward a Mechanistic Understanding and Prediction of Biotic Homogenization

The widespread replacement of native species with cosmopolitan, nonnative species is homogenizing the global fauna and flora. While the empirical study of biotic homogenization is substantial and growing, theoretical aspects have yet to be explored. Consequently, the breadth of possible ecological mechanisms that can shape current and future patterns and rates of homogenization remain largely unknown. Here, we develop a conceptual model that describes 14 potential scenarios by which species invasions and/or extinctions can lead to various trajectories of biotic homogenization (increased community similarity) or differentiation (decreased community similarity); we then use a simulation approach to explore the model’s predictions. We found changes in community similarity to vary with the type and number of nonnative and native species, the historical degree of similarity among the communities, and, to a lesser degree, the richness of the recipient communities. Homogenization is greatest when similar species invade communities, causing either no extinction or differential extinction of native species. The model predictions are consistent with current empirical data for fish, bird, and plant communities and therefore may represent the dominant mechanisms of contemporary homogenization. We present a unifying model illustrating how the balance between invading and extinct species dictates the outcome of biotic homogenization. We conclude by discussing a number of critical but largely unrecognized issues that bear on the empirical study of biotic homogenization, including the importance of spatial scale, temporal scale, and data resolution. We argue that the study of biotic homogenization needs to be placed in a more mechanistic and predictive framework in order for studies to provide adequate guidance in conservation efforts to maintain regional distinctness of the global biota.

Ecological Impacts of Nonnative Freshwater Fishes

Abstract There is a long history of introduction of non-native fishes in fresh waters and the introduction rate has accelerated greatly over time. Although not all introduced fishes have appreciable effects on their new ecosystems, many exert significant ecological, evolutionary, and economic impacts. For researchers, managers, and policy makers interested in conserving freshwater diversity, understanding the magnitude and array of potential impacts of non-native fish species is of utmost importance. The present study provides an illustrative conspectus of the most recent literature reporting ecological impacts of non-native freshwater fishes from a wide range of species and geographic locations and concludes with a prospectus of needed areas of scientific inquiry. Both directly and indirectly, invasive fishes affect a wide range of native organisms from zooplankton to mammals across multiple levels of biological organizations ranging from the genome to the ecosystem. Although a great deal of knowledge ha...