Fine-grain spatial patterning and dynamics of land use and agrobiodiversity amid global changes in the Bolivian Andes

Our research addresses the gap in scientific research on the fine-grain spatial patterns and social–ecological interactions of land use and agrobiodiversity. The spatial dimension of agrobiodiversity dynamics potentially strengthens the social–ecological resilience and food security of smallholders by buffering risk and vulnerability. Our research integrates the scientific theories, concepts, and methods of spatial externalities, social–ecological interactions, geospatial land and global change sciences, and political ecology. We designed a case study of the Arbieto-Tarata landscape in the Bolivian Andes that comprises a globally significant agrobiodiversity hot spot of Andean maize. The Arbieto-Tarata landscape, which contains nearly 8000 fields at 2500–2800 masl, is representative of mixed-use smallholder agri-food systems amid global changes. Our research predicts spatial spillover and edge effects of combined social and environmental factors leading to the clustering of same-crop fields. Findings reveal significant levels of the predicted clustering between 2006 and 2012. The degree of this clustering is found to differ among geographic and environmental sub-areas reflecting fine-grain variation of local causal linkages. Extra-local causal linkages include high levels of migration, water resource shortages, and urbanization. Results show the influences of informal and formal coordination in the spatial clustering of same-crop fields. This field-level coordination improves the efficiency of resource allocations and lowers costs of production. It enables the viability of high-agrobiodiversity Andean maize in smallholder land use and agri-food systems amid global changes. The article discusses the broader policy and scientific implications of these findings including scaling up and support of the social–ecological resilience of agrobiodiversity globally.     

Restoring ecosystems,restoring community: socioeconomic and cultural dimensions of a community-based coral reef restoration project

Environmental restoration projects are commonly touted for their ecological positives, but such projects can also provide significant socioeconomic and cultural benefits to local communities. We assessed the social dimensions of a large-scale coral reef restoration project in Maunalua Bay, O‘ahu, where >1.32 million kg of invasive marine macroalgae was removed from 11 hectares (90,000 m²; 23 acres) of impacted coral reef in an urbanized setting. We interviewed 131 community stakeholders and analyzed both quantitative and qualitative data to assess human uses of the environment, assess perceptions of environmental health, and characterize social dimensions (+/?) associated with the invasive algae removal effort. Results indicate substantial direct economic benefits, including the creation of more than 60+ jobs, benefiting more than 250 individuals and 81 households. The project helped develop a skilled workforce in a local business dedicated to environmental restoration and increased the capacity of community organizations to address other threats to reefs and watersheds. Other major benefits include revitalization of Native Hawaiian cultural practices and traditions and the successful use of harvested invasive algae as compost by local farmers. Our results show the project heightened community awareness and a broader sense of stewardship in the area, creating enabling conditions for collective community action. Our findings show that restoration projects that explicitly incorporate efforts to build community awareness, involvement, and a shared responsibility for a site may ultimately create the long-term capacity for sustainable stewardship programs. We conclude by discussing lessons learned for engaging productively with communities in environmental restoration and stewardship, which remains a central focus in conservation worldwide.     

Legitimacy,access, and the gridlock of tiger conservation: lessons from Melghat and the history of central India

Though tiger conservationists almost ubiquitously acknowledge the necessity of landscape approaches and the involvement of local people for effective tiger conservation, reconciling these two needs presents certain challenges for practitioners. Seeking to address both local exigencies and conservation goals, state-sponsored ecodevelopment initiatives have become commonly associated with Project Tiger reserves in India. However, in this essay I argue that by focusing on the proximate sources of tension between tiger conservation and local people (i.e., human–tiger conflict, habitat degradation, and prey depletion), these programs have reinforced the ultimate causes of such tension: the structural inequalities that exists between local people and state organizations. By linking the historical literature with my own fieldwork in the Melghat Tiger Reserve of the Central Indian Highlands, I show how the current structure of ecodevelopment largely mirrors that of colonial forestry by attempting to enforce natural resource property rights in a way that privileges the state and delegitimizes local relational mechanisms of access to natural resources. In doing so, ecodevelopment reflects the political structure that facilitated the rise of conflicts between tigers and people and reinforces the “gridlock of tiger conservation” (Rastogi et al. 2012). With this political ecology perspective, I advocate solidarity between conservation practitioners, local people, and state organizations in addressing these structural problems to further conservation efforts. Emphasizing co-management’s ability to accommodate multi-scalar forms of authority, I end by offering three lessons for conservation from Melghat’s experience with colonial forestry and ecodevelopment.     

Connecting the dots: mapping habitat connectivity for tigers in central India

Large connected landscapes are paramount to maintain top predator populations. Across their range, tiger (Panthera tigris) populations occur in small fragmented patches of habitat, often isolated by large distances in human-dominated landscapes. We assessed connectivity between 16 protected areas (PAs) in central India, a global priority landscape for tiger conservation, using data on land use and land cover, human population density, and transportation infrastructure. We identified and prioritized movement routes using a combination of least-cost corridor modeling and circuit theory. Our analyses suggest that there are several opportunities to maintain connectivity in this landscape. We mapped a total of thirty-five linkages in the region and calculated metrics to estimate their quality and importance. The highest quality linkages as measured by the ratio of cost-weighted distance to Euclidean distance are Kanha–Phen/Bandhavgarh–SanjayGhasidas/Melghat–Satpura, and cost-weighted distance to least-cost path length are Nawegaon–Tadoba/Achanakmar–SanjayGhasidas/Kanha–Phen. We used current flow centrality to evaluate the contribution of each PA and linkage toward facilitating animal movement. Values are highest for Kanha and Pench tiger reserves, and the linkages between Kanha–Phen, Kanha–Pench, and Pench–Satpura, suggesting that these PAs and linkages play a critical role in maintaining connectivity in central India. In addition, smaller areas such as Bor, Nawegaon, and Phen have high centrality scores relative to their areas and thus may act as important stepping stones. We mapped pinch points, which are sections of the linkages where tiger movement is restricted due to unfavorable habitat, transportation networks, human habitation, or a combination of factors. Currently, very limited data exist on tiger movement outside of PAs to validate model results. Regional-scale connectivity mapping efforts can assist managers and policy makers to develop strategic plans for balancing wildlife conservation and other land uses in the landscape.     

Numerical simulation of an array of fences in Saemangeum reclaimed land

This paper discusses about the quantitative effect of windbreak fences on wind velocity in the reclaimed land at Saemangeum in South Korea. Windbreak fences were constructed in the reclaimed land to reduce the wind velocity to prevent the generation and diffusion of dust. However, up to this time, no in-depth studies were conducted to quantitatively measure the effect of the windbreak fences on wind velocity thus an optimum windbreak structure is not yet determined. Using CFD simulations, the effects of fence porosity, fence height, and the distance between the adjacent fences were investigated. A wind tunnel experiment was initially conducted and data gathered were used to develop the CFD models. From the experiments and CFD simulations, the overall percentage difference of the measured velocities was 7.20% which is generally acceptable to establishing the reliability of the CFD models. The reduction effect on wind velocity was measured in between the adjacent fences up to a height of 0.6 m from the ground surface. In terms of porosity ( = 0, 0.2, 0.4, 0.6), 0.2 was found to be the optimum value. Conversely, the effect of fence height (0.6, 0.8 and 1.0 m) showed no significant difference; therefore, 0.6 m height is recommended. In addition, the reduction effect of distance between the adjacent fences (2, 4 and 6 m) on wind velocity having a 0.2 porosity has decreased to about 75% regardless of the distance. In the case of the reclaimed land in Saemangeum, a decrease of 75% can prevent the generation and diffusion of dusts. However, the source of dusts is very large. Therefore, constructing an array of windbreak with 6 m distance between them is deemed necessary.     

Examining intra-urban variation in fine particle mass constituents using GIS and constrained factor analysis

Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM_2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO₂) and PM_2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM_2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM_2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

A computational study of particulate emissions from an open pit quarry under neutral atmospheric conditions

The extraction of minerals from surface mines and quarries can produce significant fugitive dust emissions as a result of site activities such as blasting, road haulage, loading, crushing and stockpiling. If uncontrolled, these emissions can present serious environmental, health, safety and operational issues impacting both site personnel and the wider community.The dispersion of pollutant emissions within the atmosphere is principally determined by the background wind systems characterized by the atmospheric boundary layer (ABL). This paper presents an overview of the construction and solution of a computational fluid dynamics (CFD) model to replicate the development of the internal ventilation regime within a surface quarry excavation due to the presence of a neutral ABL above this excavation. This model was then used to study the dispersion and deposition of fugitive mineral dust particles generated during rock blasting operations. The paths of the mineral particles were modelled using Lagrangian particle tracking. Particles of four size fractions were released from five blast locations for eight different wind directions.The study concluded that dependent on the location of the bench blast within the quarry and the direction of the wind, a mass fraction of between 0.3 and 0.6 of the emitted mineral particles was retained within the quarry. The retention was largest when the distance from the blast location to the downwind pit boundary was greatest.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

The Value of Linking Mitigation and Adaptation: A Case Study of Bangladesh

There are two principal strategies for managing climate change risks: mitigation and adaptation. Until recently, mitigation and adaptation have been considered separately in both climate change science and policy. Mitigation has been treated as an issue for developed countries, which hold the greatest responsibility for climate change, while adaptation is seen as a priority for the South, where mitigative capacity is low and vulnerability is high. This conceptual divide has hindered progress against the achievement of the fundamental sustainable development challenges of climate change. Recent attention to exploring the synergies between mitigation and adaptation suggests that an integrated approach could go some way to bridging the gap between the development and adaptation priorities of the South and the need to achieve global engagement in mitigation. These issues are explored through a case study analysis of climate change policy and practice in Bangladesh. Using the example of waste-to-compost projects, a mitigation-adaptation-development nexus is demonstrated, as projects contribute to mitigation through reducing methane emissions; adaptation through soil improvement in drought-prone areas; and sustainable development, because poverty is exacerbated when climate change reduces the flows of ecosystem services. Further, linking adaptation to mitigation makes mitigation action more relevant to policymakers in Bangladesh, increasing engagement in the international climate change agenda in preparation for a post-Kyoto global strategy. This case study strengthens the argument that while combining mitigation and adaptation is not a magic bullet for climate policy, synergies, particularly at the project level, can contribute to the sustainable development goals of climate change and are worth exploring.