Key factors that influence households’ tree planting behaviour

Despite a decrease in indigenous forests and a growing demand for tree products in developing countries, tree planting activities are not considerably expanding in Tanzania. In this paper, we analyse factors that influence households’ tree planting behaviour, as well as the number of trees planted. Coast and Morogoro regions in the east of Tanzania were selected as the case, and data was gathered from 202 households in 11 villages in these regions where tree planting programmes have been or still are active. A Heckman model is used to analyse the factors that drive tree planting behaviour. Results indicate that households get wood energy from forest reserves (57%), in addition to their own planted trees (9.1%). Emperical findings show that the most important factors have significantly positive effects on households’ tree planting behaviour, as well as the extent to which it was implemented. These factors include households’ land sizes, households’ awareness of tree planting programmes, tree planting for wood energy, and the age of the head of the household. The right/freedom to harvest and transport tree products, households’ attitudes towards tree planting, and family size have significantly negative effects on households’ tree planting behaviour. This paper is perhaps the first comprehensive study to analyse the factors that influence households’ tree planting behaviour in Tanzania, and it uncovers results that are useful, even for other developing countries with similar conditions.     

Carbon emission reduction and cost–benefit of methane digester systems on hog farms in China

Three different sizes of hog farms were selected to analyze the carbon emissions reduction and the cost–benefit of three methane digester systems. The sizes of the digesters are 2,200, 2,200 and 800 m³, respectively. The sales of slaughter hogs from them are 50,000, 35,000 and 10,000 head, respectively. The carbon emissions reductions were 5,237, 4,017, and 1,334 tons, respectively. The results show that while the methane digester systems have a significant effect on carbon emissions reduction, it is difficult to operate the systems sustainably. If the carbon emissions reduction can be traded at high enough prices in the carbon offset markets, then the systems will be profitable and sustainable. Newly established China's domestic carbon offset market could provide this possibility, but more government support is needed. In addition, this study shows that scale economies make the digester adoption relatively more profitable for larger farms than smaller ones.     

Are national biodiversity strategies and action plans appropriate for building responsibilities for mainstreaming biodiversity across policy sectors? The case of Finland

The Convention on Biological Diversity's national biodiversity strategies and action plans (NBSAPs) are major mechanisms for mainstreaming biodiversity into national policies. This article examines whether and how the NBSAPs contribute to mainstreaming biodiversity across policy sectors in Finland in order to halt biodiversity loss. We have developed an innovative analytical framework where the concept of responsibility addresses how motivations for mainstreaming can be built, and the concept of social learning outcomes addresses the extent of institutional changes for biodiversity. The Finnish NBSAP processes have been able to build diverse forms of responsibility (liability, accountability, responsiveness and care) in different policy sectors by providing new knowledge, careful process design and developing institutional linkages. Despite pro-biodiversity outcomes in the targeted policy sectors, the responsibilities do not diffuse from the environmental administration to other policy sectors to a sufficient extent. Closing this ‘responsibility gap’ is a key challenge for building effective environmental policies.     

Characterizing Drought in Irrigated Agricultural Systems: The Surface Water Delivery Index (SWDI)

Quantifying surface water shortages in arid and semiarid agricultural regions is challenging because limited water supplies are distributed over long distances based on complex water management systems constrained by legal, economic, and social frameworks that evolve with time. In such regions, the water supply is often derived in a climate dramatically different from where the water is diverted to meet agricultural demand. The existing drought indices which rely on local climate do not portray the complexities of the economic and legal constraints on water delivery. Nor do these indices quantify the shortages that occur in drought. Therefore, this research proposes a methodological approach to define surface water shortages in irrigated agricultural systems using a newly developed index termed the Surface Water Delivery Index (SWDI). The SWDI can be used to uniformly quantify surface water deficits/shortages at the end of the irrigation season. Results from the SWDI clearly illustrate how water shortages in droughts identified by the existing indices (e.g., SPI and PDSI) vary strongly both within and between basins. Some surface water entities are much more prone to water shortages than other entities based both on their source of water supply and water right portfolios.     

Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Temporal Trends in the Spatial Distribution of Impervious Cover Relative to Stream Location

Use of impervious cover is transitioning from an indicator of surface water condition to one that also guides and informs watershed planning and management, including Clean Water Act (33 U.S.C. §1251 et seq.) reporting. Whether it is for understanding surface water condition or planning and management, impervious cover is most commonly expressed as summary measurement (e.g., percentage watershed in impervious cover). We use the National Land Cover Database to estimate impervious cover in the vicinity of surface waters for three time periods (2001, 2006, 2011). We also compare impervious cover in the vicinity of surface waters to watershed summary estimates of impervious cover for classifying the spatial pattern of impervious cover. Between 2001 and 2011, surface water shorelines (streams and water bodies) in the vicinity of impervious cover increased nearly 10,000 km. Across all time periods, approximately 27% of the watersheds in the continental United States had proximally distributed impervious cover, i.e., the percentage of impervious cover in the vicinity of surface waters was higher than its watershed summary expression. We discuss how impervious cover spatial pattern can be used to inform watershed planning and management, including reporting under the Clean Water Act.     

Emerging Tools for Continuous Nutrient Monitoring Networks: Sensors Advancing Science and Water Resources Protection

Sensors and enabling technologies are becoming increasingly important tools for water quality monitoring and associated water resource management decisions. In particular, nutrient sensors are of interest because of the well‐known adverse effects of nutrient enrichment on coastal hypoxia, harmful algal blooms, and impacts to human health. Accurate and timely information on nutrient concentrations and loads is integral to strategies designed to minimize risk to humans and manage the underlying drivers of water quality impairment. Using nitrate sensors as the primary example, we highlight the types of applications in freshwater and coastal environments that are likely to benefit from continuous, real‐time nutrient data. The concurrent emergence of new tools to integrate, manage, and share large datasets is critical to the successful use of nutrient sensors and has made it possible for the field of continuous monitoring to rapidly move forward. We highlight several near‐term opportunities for federal agencies, as well as the broader scientific and management community, that will help accelerate sensor development, build and leverage sites within a national network, and develop open data standards and data management protocols that are key to realizing the benefits of a large‐scale, integrated monitoring network. Investing in these opportunities will provide new information to guide management and policies designed to protect and restore our nation's water resources.