Agricultural Land Abandonment in the Hill Agro-ecological Region of Nepal: Analysis of Extent, Drivers and Impact of Change.

Despite widely reported trends of agricultural land abandonment across many parts of the globe, this land use change phenomenon is relatively new in the context of Nepal. In recent years, rural farming communities in the hill region are gradually reducing the intensity of farming, leading to underutilisation and abandonment of agricultural lands. Adopting a mixed methods research approach, this study investigated the extent of agricultural land abandonment, its underlying causal drivers and perceived impacts in the hill agro-ecological region of Nepal. A structured survey of 374 households and six focus group discussions were carried out in three districts. The study revealed that around 40% of agricultural lands in the hill agro-ecological region have been abandoned and 60% of farmers have left at least one parcel of agricultural land abandoned. It was found that biophysical drivers (distance from homestead to parcel, slope of the parcel, land fragmentation, land quality and irrigation availability) and socio-demographic drivers (family size, higher education of the household members, domestic migration and out-migration) were responsible for agricultural land abandonment. Negative impacts of land abandonment were observed on the rural landscape, human-made farm structures, socio-economic systems, local food production and food security. In line with global studies, this research suggest that marginal land quality, demographic changes and rising alternative economic opportunities elsewhere contribute to farmland abandonment. This study also discusses land management approaches and policy implications to address the issue of agricultural land abandonment.

Cost effectiveness in site selection to protect native plant communities from the weed, bitou bush, in New South Wales, Australia.

Government funding to protect native plant communities is usually limited. For cost effectiveness, priority sites for conservation must therefore be identified and funds allocated to protect these sites according to the quantity of communities conserved per dollar of cost. In 1999, invasion of coastal vegetation in New South Wales (NSW) by bitou bush was listed as a key threatening process under the NSW Threatened Species Conservation Act 1995. In accordance with the Act, a Threat Abatement Plan (TAP) was prepared to reduce the impacts of the weed to threatened biodiversity at priority sites. In the present study, data collected for the TAP were analysed by linear programming to determine the feasibility of achieving cost effectiveness in identifying sites and allocating funds, and to explore the impact of associated economic issues on the quantity of native plant communities that are protected. In addition to the total funds and costs per site, the quantity was influenced by alternative funding policies and different site selection strategies. Allocations that recognise these issues can enhance protection outcomes, and promote the cost effectiveness of weed management.

Finding needles (or ants) in haystacks: predicting locations of invasive organisms to inform eradication and containment.

To eradicate or effectively contain a biological invasion, all or most reproductive individuals of the invasion must be found and destroyed. To help find individual invading organisms, predictions of probable locations can be made with statistical models. We estimated spread dynamics based on time-series data and then used model-derived predictions of probable locations of individuals. We considered one of the largest data sets available for an eradication program: the campaign to eradicate the red imported fire ant (Solenopsis invicta) from around Brisbane, Australia. After estimating within-site growth (local growth) and intersite dispersal (saltatory spread) of fire ant nests, we modeled probabilities of fire ant presence for >600000 1-ha sites, including uncertainties about fire ant population and spatial dynamics. Such a high level of spatial detail is required to assist surveillance efforts but is difficult to incorporate into common modeling methods because of high computational costs. More than twice as many fire ant nests would have been found in 2008 using predictions made with our method rather than those made with the method currently used in the study region. Our method is suited to considering invasions in which a large area is occupied by the invader at low density. Improved predictions of such invasions can dramatically reduce the area that needs to be searched to find the majority of individuals, assisting containment efforts and potentially making eradication a realistic goal for many invasions previously thought to be ineradicable.