A constrained least-squares approach to combine bottom-up and top-down CO2 flux estimates

Terrestrial CO₂ flux estimates are obtained from two fundamentally different methods generally termed bottom-up and top-down approaches. Inventory methods are one type of bottom-up approach which uses various sources of information such as crop production surveys and forest monitoring data to estimate the annual CO₂ flux at locations covering a study region. Top-down approaches are various types of atmospheric inversion methods which use CO₂ concentration measurements from monitoring towers and atmospheric transport models to estimate CO₂ flux over a study region. Both methods can also quantify the uncertainty associated with their estimates. Historically, these two approaches have produced estimates that differ considerably. The goal of this work is to construct a statistical model which sensibly combines estimates from the two approaches to produce a new estimate of CO₂ flux for our study region. The two approaches have complementary strengths and weaknesses, and our results show that certain aspects of the uncertainty associated with each of the approaches are greatly reduced by combining the methods. Our model is purposefully simple and designed to take the two approaches’ estimates and measures of uncertainty at ‘face value’. Specifically, we use a constrained least-squares approach to appropriately weigh the estimates by the inverse of their variance, and the constraint imposes agreement between the two sources. Our application involves nearly 18,000 flux estimates for the upper midwest United States. The constrained dependencies result in a non-sparse covariance matrix, but computation requires only minutes due to the structure of the model.     

A case for quantile regression in behavioral ecology: getting more out of flight initiation distance data

A central goal of behavioral ecology is to quantify and explain variation in behavior. While much previous work has focused on the differences in mean behavior across groups or treatments, we present a complementary approach studying changes in the distribution of the response variable. This is important because changes in the edges of a distribution may be more informative than changes in the mean if behavior at the edges of a distribution better reflects behavioral constraints. Quantile regression estimates the rate of change of conditional quantiles of a response variable and thus allows the study of changes in any part of its distribution. Although quantile regression is gaining popularity in the ecological literature, it is strikingly unused in behavioral ecology. Here, we demonstrate the usefulness of this method by analyzing the relationship between the starting distance (SD) at which an observer approach a focal animal and its flight initiation distance (FID, the distance between the observer and the animal when it decides to flee). In particular, we used a simple model of flight initiation distance to show that in most situations ordinary least-square regression cannot be used to analyse the SD–FID relationship. Quantile regression conducted on the lowest quantiles appears more robust and we applied this approach to data from four bird species. Overall, changes in the lowest FID values appeared to be the most informative to determine if a species displays a “flush early” strategy, a strategy which has been hypothesized to be a general rule. We hope this example will bring quantile regression to the attention of behavioral ecologists as a valuable tool to add to their statistical toolbox.     

Community ecology of invasions: direct and indirect effects of multiple invasive species on aquatic communities

With many ecosystems now supporting multiple nonnative species from different trophic levels, it can be challenging to disentangle the net effects of invaders within a community context. Here, we combined wetland surveys with a mesocosm experiment to examine the individual and combined effects of nonnative fish predators and nonnative bullfrogs on aquatic communities. Among 139 wetlands, nonnative fish (bass, sunfish, and mosquitofish) negatively influenced the probability of occupancy of Pacific treefrogs (Pseudacris regilla), but neither invader correlated strongly with occupancy by California newts (Taricha torosa), western toads (Anaxyrus boreas), or California red-legged frogs (Rana draytonii). In mesocosms, mosquitofish dramatically reduced the abundance of zooplankton and palatable amphibian larvae (P. regilla and T. torosa), leading to increases in nutrient concentrations and phytoplankton (through loss of zooplankton), and rapid growth of unpalatable toad larvae (through competitive release). Bullfrog larvae reduced the growth of native anurans but had no effect on survival. Despite strong effects on natives, invaders did not negatively influence one another, and their combined effects were additive. Our results highlight how the net effects of multiple nonnative species depend on the trophic level of each invader, the form and magnitude of invader interactions, and the traits of native community members.     

Is the Mantel correlogram powerful enough to be useful in ecological analysis? A simulation study

The Mantel correlogram is an elegant way to compute a correlogram for multivariate data. However, recent papers raised concerns about the power of the Mantel test itself. Hence the question: Is the Mantel correlogram powerful enough to be useful? To explore this issue, we compared the performances of the Mantel correlogram to those of other methods, using numerical simulations based on random, normally distributed data. For a single response variable, we compared it to the Moran and Geary correlograms. Type I error rates of the three methods were correct. Power of the Mantel correlogram was nearly as high as that of the univariate methods. For the multivariate case, the test of the multivariate variogram developed in the context of multiscale ordination is in fact a Mantel test, so that the power of the two methods is the same by definition. We devised an alternative permutation test based on the variance, which yielded similar results. Overall, the power of the Mantel test was high, the method successfully detecting spatial correlation at rates similar to the permutation test of the variance statistic in multivariate variograms. We conclude that the Mantel correlogram deserves its place in the ecologist's toolbox.     

Species diversity reduces parasite infection through cross-generational effects on host abundance

With growing interest in the effects of biodiversity on disease, there is a critical need for studies that empirically identify the mechanisms underlying the diversity-disease relationship. Here, we combined wetland surveys of host community structure with mechanistic experiments involving a multi-host parasite to evaluate competing explanations for the dilution effect. Sampling of 320 wetlands in California indicated that snail host communities were strongly nested, with competent hosts for the trematode Ribeiroia ondatrae predominating in low-richness assemblages and unsuitable hosts increasingly present in more diverse communities. Moreover, competent host density was negatively associated with increases in snail species richness. These patterns in host community assembly support a key prerequisite underlying the dilution effect. Results of multigenerational mesocosm experiments designed to mimic field-observed community assemblages allowed us to evaluate the relative importance of host density and diversity in influencing parasite infection success. Increases in snail species richness (from one to four species) had sharply negative effects on the density of infected hosts (-90% reduction). However, this effect was indirect; competition associated with non-host species led to a 95% reduction in host density (susceptible host regulation), owing primarily to a reduction in host reproduction. Among susceptible hosts, there were no differences in infection prevalence as a function of community structure, indicating a lack of support for a direct effect of diversity on infection (encounter reduction). In monospecific conditions, higher initial host densities increased infection among adult hosts; however, compensatory reproduction in the low-density treatments equalized the final number of infected hosts by the next generation, underscoring the relevance of multigenerational studies in understanding the dilution effect. These findings highlight the role of interspecific competition in mediating the relationship between species richness and parasite infection and emphasize the importance of field-informed experimental research in understanding mechanisms underlying the diversity-disease relationship.     

Managing water for life

Water is essential for life. In spite of the entire engineering infrastructure devoted to the treatment, regulation and beneficial uses of water, occasionally sufficient quantities and qualities of water become scarce. When this happens, just how do we decide how much less water to allocate to all of us and the activities we engage in to sustain and enhance our quality of life? This paper addresses some of the complexities of answering such a question, especially as society increasingly recognizes the need to provide flow regimes that will maintain healthy aquatic and floodplain ecosystems that also impact the economic, physical and even the spiritual quality of our lives. For we depend on these ecosystems to sustain our wellbeing. We are indeed a part of our ecosystems. We depend upon on aquatic ecosystems to moderate river flow qualities and quantities, reduce the extremes of floods and droughts, reduce erosion, detoxify and decompose waterborne wastes, generate and preserve flood plain soils and renew their fertility, regulate disease carrying organisms, and to enhance recreational benefits of river systems. This question of deciding just how much water to allocate to each water user and for the maintenance of viable aquatic ecosystems, especially when there is not enough, is a complex, and largely political, issue. This issue is likely to become even more complex and political and contentious in the future as populations grow and as water quantities and their qualities become even more variable and uncertain.     

Multiscale codependence analysis: an integrated approach to analyze relationships across scales

The spatial and temporal organization of ecological processes and features and the scales at which they occur are central topics to landscape ecology and metapopulation dynamics, and increasingly regarded as a cornerstone paradigm for understanding ecological processes. Hence, there is need for computational approaches which allow the identification of the proper spatial or temporal scales of ecological processes and the explicit integration of that information in models. For that purpose, we propose a new method (multiscale codependence analysis, MCA) to test the statistical significance of the correlations between two variables at particular spatial or temporal scales. Validation of the method (using Monte Carlo simulations) included the study of type I error rate, under five statistical significance thresholds, and of type II error rate and statistical power. The method was found to be valid, in terms of type I error rate, and to have sufficient statistical power to be useful in practice. MCA has assumptions that are met in a wide range of circumstances. When applied to model the river habitat of juvenile Atlantic salmon, MCA revealed that variables describing substrate composition of the river bed were the most influential predictors of parr abundance at 0.4-4.1 km scales whereas mean channel depth was more influential at 200-300 m scales. When properly assessed, the spatial structuring observed in nature may be used purposefully to refine our understanding of natural processes and enhance model representativeness.     

Bioreduction of nitrate in groundwater using a pilot-scale hydrogen-based membrane biofilm reactor

A long-term pilot-scale H₂-based membrane biofilm reactor (MBfR) was tested for removal of nitrate from actual groundwater. A key feature of this second-generation pilot MBfR is that it employed lower cost polyester hollow fibers and still achieved high loading rate. The steady-state maximum nitrate surface loading at which the effluent nitrate and nitrite concentrations were below the Maximum Contaminant Level (MCL) was at least 5.9 g·N·(m²·d)^?1, which corresponds to a maximum volumetric loading of at least 7.7 kg·N·(m³·d) ^?1. The steady-state maximum nitrate surface area loading was higher than the highest nitrate surface loading reported in the first-generation MBfRs using composite fibers (2.6 g·N·(m²·d)^?1). This work also evaluated the H₂-utilization efficiency in MBfR. The measured H₂ supply rate was only slightly higher than the stoichiometric H₂-utilization rate. Thus, H₂ utilization was controlled by diffusion and was close to 100% efficiency, as long as biofilm accumulated on the polyester-fiber surface and the fibers had no leaks.     

Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain1

Epps, Thomas H., Daniel R. Hitchcock, Anand D. Jayakaran, Drake R. Loflin, Thomas M. Williams, and Devendra M. Amatya, 2012. Characterization of Storm Flow Dynamics of Headwater Streams in the South Carolina Lower Coastal Plain. Journal of the American Water Resources Association (JAWRA) 1‐14. DOI: 10.1111/jawr.12000 Abstract: Hydrologic monitoring was conducted in two first‐order lower coastal plain watersheds in South Carolina, United States, a region with increasing growth and land use change. Storm events over a three‐year period were analyzed for direct runoff coefficients (ROC) and the total storm response (TSR) as percent rainfall. ROC calculations utilized an empirical hydrograph separation method that partitioned total streamflow into sustained base flow and direct runoff components. ROC ratios ranged from 0 to 0.32 on the Upper Debidue Creek (UDC) watershed and 0 to 0.57 on Watershed 80 (WS80); TSR results ranged from 0 to 0.93 at UDC and 0.01 to 0.74 at WS80. Variability in event runoff generation was attributed to seasonal trends in water table elevation fluctuation as regulated by evapotranspiration. Groundwater elevation breakpoints for each watershed were identified based on antecedent water table elevation, streamflow, ROCs, and TSRs. These thresholds represent the groundwater elevation above which event runoff generation increased sharply in response to rainfall. For effective coastal land use decision making, baseline watershed hydrology must be understood to serve as a benchmark for management goals, based on both seasonal and event‐based surface and groundwater interactions.     

Discussion: “America's Rivers and the American Experiment” by Martin W. Doyle

Doyle cogently describes advantages and concerns related to the system of United States river management in the context of its historical and political development. He rightly asserts the need for flexible, adaptable institutions in order to address changing societal demands. However, river management also requires certain inflexible standards in order to discern and prevent practices that undermine future human needs. Where modern scientific evidence converges with cultural traditions of stewardship, river managers can comfortably assert limits to specific patterns of use and to the malleability of restrictions.