The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.     

Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks. To build a model, a user selects components from the library, and then writes new components as needed. Some of these components represent specific ecological processes, such as how environmental factors influence the growth of individual trees. Other components provide simulation support such as reading and writing files in various formats to allow inter-operability with other software. The framework manages components and variables, the order of operations, and spatial interactions. The framework provides only simulation support; it does not include ecological functions or assumptions. This separation allows biologists to build models without becoming computer scientists, while computer scientists can improve the framework without becoming ecologists. The framework is designed to operate on multiple platforms and be used across networks via a World Wide Web-based user interface. ECLPSS is designed for use with both single processor computers for small models, and multiple processors in order to simulate large regions with complex interactions among many individuals or ecological compartments. To test Version 1.0 of ECLPSS, we created a model to evaluate the effect of tropospheric ozone on forest ecosystem dynamics. This model is a reduced-form version of two existing models: , which represents an individual tree, and , which represents forest stand growth and succession. This model demonstrates key features of ECLPSS, such as the ability to examine the effects of cell size and model structure on model predictions.     

Evaluating China's Slope Land Conversion Program as sustainable management in Tianquan and Wuqi Counties

Increased soil erosion on sloped land has become a significant environmental concern in China that has been attributed to human activities such as deforestation, over-cultivation, and over-grazing of livestock. In order to reduce soil erosion on sloped lands, the Chinese government has responded by implementing large-scale, ecological rehabilitation programs, including the "Grain for Green" reforestation project. This program involves financial incentives to transition farmers into other economic activities with the goal of reducing ecological pressures and degradation. Because of the scope and potential impacts from these programs, detailed research is needed to understand their social and ecological effects. This paper reports on research conducted in Tianquan County, Sichuan Province, and Wuqi County, Shaanxi Province, that evaluates the effects of the program upon local economies and household livelihood systems. The paper argues that the successful conversion of farmland under "Grain for Green" depends upon local government involvement, local economic development, and funding for local projects. Without economic development within rural economies, we conclude that farmers will remain dependent upon continued subsidy assistance to meet the policy's ambitious environmental restrictions, thereby undermining the program's long-term sustainability.     

Heavy metals in soils in north Somerset,England, with special reference to contamination from base metal mining in the Mendips

A 2 × 2 km grid survey of surface soils was conducted over 600 km of North Somerset, England, to investigate the role of pollution from former base metai mines on soil heavy metal content. Soil contents of Pb, Zn, Cu and Cd were determined by atomic absorption spectrometry after extraction in hot, concentrated nitric acid. Most of the soils were contaminated by lead, zinc and cadmium. Isoline maps and perspective block diagrams showed this contamination to be most severe on the Mendip plateau, especially in the vicinity of Shipham, Wells and Priddy districts. Resurgences, polluted from mine drainage, also contaminated soils at the base of the Mendip slopes and, over the lowlands, trace element enriched Liassic shales caused significant local anomalies.     

The evolution of large and small-scale structures in Kelvin–Helmholtz instabilities

To better understand the dynamics of Kelvin–Helmholtz instabilities in environmental flows, their evolution is investigated using direct numerical simulations (DNS). Two-dimensional DNS is used to examine the large-scale and small-scale structures of the instability at high Reynolds and Prandtl numbers that represent real environmental flows. The semi-analytical model of Corcos and Sherman (J Fluid Mech 73:241–264, 1976) is used to explain the physics of these simulations prior to saturation of the KH billow, and also provide a computationally efficient prediction of the vortex dynamics of the instability. The DNS results show that the large-scale structure of the billow does not depend on the Reynolds number for sufficiently high Reynolds numbers. The billow structure reveals a less straightforward dependence on the Prandtl number. Predictions of the model of Corcos and Sherman (J Fluid Mech 73:241–264, 1976) improve as Reynolds number and Prandtl number increase. The small-scale structure of the vorticity and density fields vary with both Reynolds and Prandtl numbers. Three-dimensional DNS of KH flows and their transition to turbulence are used to study small length scales. Based on the thickness of the braid, a simple method is introduced to estimate the Batchelor scale, which can be used as a guide for the resolution required for the direct numerical simulation of two and three-dimensional Kelvin–Helmholtz flow fields.     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Cover crop effects on nitrous oxide emission from a manure-treated Mollisol

Agriculture contributes 40–60% of the total annual N₂O emissions to the atmosphere. Development of management practices to reduce these emissions would have a significant impact on greenhouse gas levels. Non-leguminous cover crops are efficient scavengers of residual soil NO₃, thereby reducing leaching losses. However, the effect of a grass cover crop on N₂O emissions from soil receiving liquid swine manure has not been evaluated. This study investigated: (i) the temporal patterns of N₂O emissions following addition of swine manure slurry in a laboratory setting under fluctuating soil moisture regimes; (ii) assessed the potential of a rye (Secale cereale L.) cover crop to decrease N₂O emissions under these conditions; and (iii) quantified field N₂O emissions in response to either spring applied urea ammonium nitrate (UAN) or different rates of fall-applied liquid swine manure, in the presence or absence of a rye/oat winter cover crop. Laboratory experiments investigating cover crop effects N₂O emissions were performed in a controlled environment chamber programmed for a 14 h light period, 18 °C day temperature, and 15 °C night temperature. Treatments with or without a living rye cover crop were treated with either: (i) no manure; (ii) a phosphorus-based manure application rate (low manure): or (iii) a nitrogen-based manure application rate (high manure). We observed a significant reduction in N₂O emissions in the presence of the rye cover crop. Field experiments were performed on a fine-loamy soil in Central Iowa from October 12, 2005 to October 2, 2006. We observed no significant effect of the cover crop on cumulative N₂O emissions in the field. The primary factor influencing N₂O emission was N application rate, regardless of form or timing. The response of N₂O emission to N additions was non-linear, with progressively more N₂O emitted with increasing N application. These results indicate that while cover crops have the potential to reduce N₂O emissions, N application rate may be the overriding factor.     

Forecasting municipal solid waste generation in a fast-growing urban region with system dynamics modeling

Both planning and design of municipal solid waste management systems require accurate prediction of solid waste generation. Yet achieving the anticipated prediction accuracy with regard to the generation trends facing many fast-growing regions is quite challenging. The lack of complete historical records of solid waste quantity and quality due to insufficient budget and unavailable management capacity has resulted in a situation that makes the long-term system planning and/or short-term expansion programs intangible. To effectively handle these problems based on limited data samples, a new analytical approach capable of addressing socioeconomic and environmental situations must be developed and applied for fulfilling the prediction analysis of solid waste generation with reasonable accuracy. This study presents a new approach--system dynamics modeling--for the prediction of solid waste generation in a fast-growing urban area based on a set of limited samples. To address the impact on sustainable development city wide, the practical implementation was assessed by a case study in the city of San Antonio, Texas (USA). This area is becoming one of the fastest-growing regions in North America due to the economic impact of the North American Free Trade Agreement (NAFTA). The analysis presents various trends of solid waste generation associated with five different solid waste generation models using a system dynamics simulation tool--Stella. Research findings clearly indicate that such a new forecasting approach may cover a variety of possible causative models and track inevitable uncertainties down when traditional statistical least-squares regression methods are unable to handle such issues.     

On estimating the exponent of power-law frequency distributions

Power-law frequency distributions characterize a wide array of natural phenomena. In ecology, biology, and many physical and social sciences, the exponents of these power laws are estimated to draw inference about the processes underlying the phenomenon, to test theoretical models, and to scale up from local observations to global patterns. Therefore, it is essential that these exponents be estimated accurately. Unfortunately, the binning-based methods traditionally used in ecology and other disciplines perform quite poorly. Here we discuss more sophisticated methods for fitting these exponents based on cumulative distribution functions and maximum likelihood estimation. We illustrate their superior performance at estimating known exponents and provide details on how and when ecologists should use them. Our results confirm that maximum likelihood estimation outperforms other methods in both accuracy and precision. Because of the use of biased statistical methods for estimating the exponent, the conclusions of several recently published papers should be revisited.