Effects of Short- and Long-Term Disturbance Resulting from Military Maneuvers on Vegetation and Soils in a Mixed Prairie Area

Loss of grassland species resulting from activities such as off-road vehicle use increases the need for models that predict effects of anthropogenic disturbance. The relationship of disturbance by military training to plant species richness and composition on two soils (Foard and Lawton) in a mixed prairie area was investigated. Track cover (cover of vehicle disturbance to the soil) and soil organic carbon were selected as measures of short- and long-term disturbance, respectively. Soil and vegetation data, collected in 1-m² quadrats, were analyzed at three spatial scales (60, 10, and 1 m²). Plant species richness peaked at intermediate levels of soil organic carbon at the 10-m² and 1-m² spatial scales on both the Lawton and Foard soils, and at intermediate levels of track cover at all three spatial scales on the Foard soil. Species composition differed across the disturbance gradient on the Foard soil but not on the Lawton soil. Disturbance increased total plant species richness on the Foard soil. The authors conclude that disturbance up to intermediate levels can be used to maintain biodiversity by enriching the plant species pool.     

A Comparison of Campfire Impacts and Policies in Seven Protected Areas

Using resource-monitoring data from seven protected areas, the effectiveness of three campfire policies—campfire ban, designated campfires, and unregulated campfires—were assessed based on the number of fire sites and the amount of tree damage. Results indicate that unregulated campfire policies permitted substantial numbers of fire sites and tree damage in campsites, although fire bans did not eliminate or even substantially decrease these problems. A designated campfire policy was effective in decreasing number of fire sites, but little difference was found among policies regarding tree damage. Given the importance of campfires to visitor experiences, campfire prohibitions could be viewed as unnecessarily restrictive based on their limited success in preventing resource damage. Conclusions encourage protected-area managers to consider designated campfire policies and prohibitions on axes, hatchets, and saws to better meet resource protection and visitor experience mandates.     

Spatial variability of soil phosphorus in relation to the topographic index and critical source areas: sampling for assessing risk to water quality

A measure of soil P status in agricultural soils is generally required for assisting with prediction of potential P loss from agricultural catchments and assessing risk for water quality. The objectives of this paper are twofold: (i) investigating the soil P status, distribution, and variability, both spatially and with soil depth, of two different first-order catchments; and (ii) determining variation in soil P concentration in relation to catchment topography (quantified as the "topographic index") and critical source areas (CSAs). The soil P measurements showed large spatial variability, not only between fields and land uses, but also within individual fields and in part was thought to be strongly influenced by areas where cattle tended to congregate and areas where manure was most commonly spread. Topographic index alone was not related to the distribution of soil P, and does not seem to provide an adequate indicator for CSAs in the study catchments. However, CSAs may be used in conjunction with soil P data for help in determining a more "effective" catchment soil P status. The difficulties in defining CSAs a priori, particularly for modeling and prediction purposes, however, suggest that other more "integrated" measures of catchment soil P status, such as baseflow P concentrations or streambed sediment P concentrations, might be more useful. Since observed soil P distribution is variable and is also difficult to relate to nationally available soil P data, any assessment of soil P status for determining risk of P loss is uncertain and problematic, given other catchment physicochemical characteristics and the sampling strategy employed.     

Green roof stormwater retention: effects of roof surface, slope, and media depth

Urban areas generate considerably more stormwater runoff than natural areas of the same size due to a greater percentage of impervious surfaces that impede water infiltration. Roof surfaces account for a large portion of this impervious cover. Establishing vegetation on rooftops, known as green roofs, is one method of recovering lost green space that can aid in mitigating stormwater runoff. Two studies were performed using several roof platforms to quantify the effects of various treatments on stormwater retention. The first study used three different roof surface treatments to quantify differences in stormwater retention of a standard commercial roof with gravel ballast, an extensive green roof system without vegetation, and a typical extensive green roof with vegetation. Overall, mean percent rainfall retention ranged from 48.7% (gravel) to 82.8% (vegetated). The second study tested the influence of roof slope (2 and 6.5%) and green roof media depth (2.5, 4.0, and 6.0 cm) on stormwater retention. For all combined rain events, platforms at 2% slope with a 4-cm media depth had the greatest mean retention, 87%, although the difference from the other treatments was minimal. The combination of reduced slope and deeper media clearly reduced the total quantity of runoff. For both studies, vegetated green roof systems not only reduced the amount of stormwater runoff, they also extended its duration over a period of time beyond the actual rain event.     

Source identification and apportionment of PM2.5 and PM2.5−10 in iron and steel scrap smelting factory environment using PMF,PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM_2.5 and PM_2.5?10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m³ for PM_2.5 and 331.36, 190.01, and 184.60 μg/m³ for PM_2.5?10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM_2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM_2.5?10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM_2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM_2.5?10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.     

Perceived stressors of climate vulnerability across scales in the Savannah zone of Ghana: a participatory approach

Smallholder farmers in sub-Saharan Africa are confronted with climatic and non-climatic stressors. Research attention has focused on climatic stressors, such as rainfall variability, with few empirical studies exploring non-climatic stressors and how these interact with climatic stressors at multiple scales to affect food security and livelihoods. This focus on climatic factors restricts understanding of the combinations of stressors that exacerbate the vulnerability of farming households and hampers the development of holistic climate change adaptation policies. This study addresses this particular research gap by adopting a multi-scale approach to understand how climatic and non-climatic stressors vary, and interact, across three spatial scales (household, community and district levels) to influence livelihood vulnerability of smallholder farming households in the Savannah zone of northern Ghana. This study across three case study villages utilises a series of participatory tools including semi-structured interviews, key informant interviews and focus group discussions. The incidence, importance, severity and overall risk indices for stressors are calculated at the household, community, and district levels. Results show that climatic and non-climatic stressors were perceived differently; yet, there were a number of common stressors including lack of money, high cost of farm inputs, erratic rainfall, cattle destruction of crops, limited access to markets and lack of agricultural equipment that crossed all scales. Results indicate that the gender of respondents influenced the perception and severity assessment of stressors on rural livelihoods at the community level. Findings suggest a mismatch between local and district level priorities that have implications for policy and development of agricultural and related livelihoods in rural communities. Ghana’s climate change adaptation policies need to take a more holistic approach that integrates both climatic and non-climatic factors to ensure policy coherence between national climate adaptation plans and District development plans.     

Vetoing the future: political constraints and renewable energy

Despite the increased importance of and attention to renewable energy, its share in the overall energy mix has varied significantly across countries and over time. There are many determinants of clean energy transitions; this study focuses on political constraints. Here it is argued that political systems that have fewer political constraints have fewer access points through which powerful status quo veto players can slow the progress of clean energy reforms. To test the theory, a hierarchical model is applied on a dataset of 125 countries over four decades. The results provide significant support for the theory. Furthermore, the effects for political constraints hold even when we distinguish between hydro and non-hydro renewable sources and control for regime type. This study builds on research that recognizes the importance of politics in understanding the challenges and opportunities of clean energy reform.     

US exposure to multiple landscape stressors and climate change

Regional Environmental Change - We examined landscape exposure to wildfire potential, insects and disease risk, and urban and exurban development for the conterminous US (CONUS). Our analysis...