Effects of productivity on biodiversity in forest ecosystems across the United States and China

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem‐wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground‐sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump‐shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity–biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.     

Linking Nitrogen Export to Landscape Heterogeneity: The Role of Infrastructure and Storm Flows in a Mediterranean Urban System

Urban ecosystems are often sources of nonpoint source (NPS) nitrogen (N) pollution to aquatic ecosystems. However, N export from urban watersheds is highly variable. Examples of densely urbanized watersheds are not well studied, and these may have comparatively low export rates. Commonly used metrics of landscape heterogeneity may obscure our ability to discern relationships among landscape characteristics that can explain these lower export rates. We expected that differences not often captured by these metrics in the relative cover of vegetation, structures, and impervious surfaces would better explain observed variation in N export. We examined these relationships during storms in residential watersheds. Contrary to expectations, land cover did not directly predict variation in N or water export. Instead, N export was strongly linked to drainage infrastructure density. Our research highlights the role of fine‐scaled landscape attributes, mainly infrastructure, in explaining patterns of N export from densely urbanized watersheds. Changes to hydrologic flow paths by infrastructure explained more variation in N export than land cover. Our findings support further development of landscape ecological models of urban N export that focus on hydrologic modification by infrastructure rather than traditional landscape measures such as land use, as indicators for evaluating patterns of NPS nitrogen pollution in densely urbanized watersheds.     

A review of potential physical impacts on harbours in the Mediterranean Sea under climate change

Regional Environmental Change - The potential impact of climate change on port operations and infrastructures has received much less attention than the corresponding impact for beach systems....     

Religion and environmental politics in the US House of Representatives

Does religion affect legislators’ behavior on environmental policy in the US? Studies of environmental policy making have not examined this question, although the literature suggests that religion might affect legislative behavior on environmental policy. This study examines the relationship between US House members’ religion and roll-call voting on environmental legislation from 1973 to 2009. It finds significant differences across religious traditions. Legislators’ party and characteristics of constituencies relevant to environmental politics increasingly, but not entirely, mediate these differences.     

Utilizing international networks for accelerating research and learning in transformational sustainability science

A promising approach for addressing sustainability problems is to recognize the unique conditions of a particular place, such as problem features and solution capabilities, and adopt and adapt solutions developed at other places around the world. Therefore, research and teaching in international networks becomes critical, as it allows for accelerating learning by sharing problem understandings, successful solutions, and important contextual considerations. This article identifies eight distinct types of research and teaching collaborations in international networks that can support such accelerated learning. The four research types are, with increasing intensity of collaboration: (1) solution adoption; (2) solution consultation; (3) joint research on different problems; and (4) joint research on similar problems. The four teaching types are, with increasing intensity of collaboration: (1) adopted course; (2) course with visiting faculty; (3) joint course with traveling faculty; and (4) joint course with traveling students. The typology is illustrated by extending existing research and teaching projects on urban sustainability in the International Network of Programs in Sustainability, with partner universities from Europe, North America, Asia, and Africa. The article concludes with challenges and strategies for extending individual projects into collaborations in international networks.     

Latent effects of early life stage exposure to triclosan on survival in fathead minnows,Pimephales promelas

The objective of this study was to evaluate the effects of early life stage triclosan (5-chloro-2-(2,4, dichlorophenoxy)phenol, TCS) exposure on hatching, development, and survival in the fathead minnow, Pimephales promelas. Embryonic minnows were exposed to TCS (50 and 100 µg L^?1) for 10 days followed by 6 weeks depuration. Mortality and morphological deformities were recorded and quantified during exposure and at the end of depuration. No significant effects on embryonic survival, time to reach the eyed stage, or hatching were found. However, at the conclusion of the depuration period, survival was significantly reduced in TCS exposed fish depending on the concentration. Visual inspection of the exposed fish suggests that mortality is related to spinal deformities, emaciation, and reduced foraging ability. Triclosan exhibits deleterious effects in fish at lower concentrations over longer durations than previously reported. Further, mortality in exposed fish 6 weeks after exposure demonstrates the need for various exposure assays to evaluate effects of TCS.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.