Assessing the relative impacts of the factors affecting MIS adoption process

Micro-irrigation systems (MIS) have been at the forefront of policy-making and social research in exploring determinants that could potentially impact the adoption of MIS technologies in the field to fulfil the basic aim of enhanced agricultural productivity and enriched nutritional quality of the produce with optimal adoption of natural resources. Therefore, this study was undertaken to determine why MIS technologies have not been adopted to the extent anticipated, so that suitable policy schemes, promotional schemes and socio-technical frameworks could be formulated for their enhanced adoption to enhance the socio-economic status of the farming community in the Dahod district of Gujarat State, India. A study of 350 non-MIS (NMIS) and 350 MIS farmers was conducted to identify factors affecting the MIS adoption process. The logit model was fitted using XLSTAT software (XLSTAT 2014.1.04) to the explanatory variables (determinants) of the MIS adoption process. Type III analysis and ANOVA were conducted to test the relative significance of the explanatory variables adopted. It was found that total income had the highest weight (or beta coefficient, i.e. 0.625) followed by total land area (0.546), motor horsepower (0.499), dependency ratio (0.397), and education (0.295) and age of household head (0.207). Furthermore, to assess the efficacy of the logit model, the ROC curve was also developed and the AUC was found to be 0.881, and therefore the model was considered to discriminate well in identifying the factors affecting the MIS adoption process. The study found that higher total income and education level increase the likelihood of MIS adoption and agricultural water management, and therefore special training programmes on installation, as well as repair and maintenance, of MIS systems and agricultural water management can be planned at the institutional/organisation level. The total cultivable area is also one of the important determinants in MIS adoption, and therefore the adoption of MIS schemes should not be restricted to large farmers only, but rather should be extended to both small and marginal farmers.     

Understanding the functional principles of nature—Proposing another type of ecosystem services

Ecosystem services are usually interpreted as a free of charge “favour” provided to us and our society by nature. In other words, nature supplies us with a functionality that we would otherwise have to pay for. Our cost would be to provide resources either (1) to ensure the necessary inputs to drive our society, or (2) to assist in counteracting, absorbing or remediating unwanted effects that are results of our societal activities. Through ecosystem studies it has been found that a substantial part of the functionality of nature is laid out in all types of components—the compartments of the ecosystems together with the transactional interrelations (flows) and controls between them. Eventually, many so-called indicators have been proposed during the last decades. Such measures are dedicated to tell us about the quality side of ecosystem functionality, e.g. to tell us how well the system performs relatively to a theoretical maximum efficiency possible. As an additional hypothesis, such functions are thought to orient the systems and thus increase through time development, i.e. to be optimised under the given the constraints, through the evolution of the system. Recently is has been pointed out that natural and societal systems share the feature of being complex in their organisation. Meanwhile, it was remarked that societal systems in many ways evolved in opposite direction of how natural evolution would drive an ecosystem. Many philosophers of biology have stated that biological systems posses information and memory functions which improve their long-term capability to survive. This information is believed to be contained in the organisational structures of the system as much as in its gene pool. If we accept such arguments it means that studies of organisation and function of natural systems will provide us with another type of ecosystem services. This would namely give us information about in what direction to drive society in order to achieve a more sustainable system.     

Social network effects on the adoption of sustainable natural resource management practices in Ethiopia

Soil loss, nutrient depletion and land degradation contribute to the skimpy performance of smallholder agriculture and pose serious policy challenges in developing countries. Surprisingly, natural resource management practices that enhance sustainability while improving productivity have not been fully adopted despite continuous efforts of promotion. Using data collected from 2901 farm households in the Farmers Innovation Fund (FIF) of the World Bank, this study examines factors delaying adoption of resource management and farming practices from the perspective of social learning and network size. Specifically, the study aims at identifying the extent to which differences in network structure matter in providing opportunities to learn about new ways of sustainable resource management practices using regression analysis. The result confirms that social network size plays a significant role in enhancing adoption of natural resource management practices. Moreover, external sources of information such as extension provision play a crucial role in enhancing adoption of resource management practices. Thus, future endeavours should link extension services to informal networks to enhance adoption of sustainable natural resource management practices.     

农户参与三氯杀螨醇替代技术培训积极性的影响因素分析

病虫害综合防治（1PM）技术旨在结合生物、农学及物理防治方法,合理使用化学农药,降低农业生产成本,保护农业劳动者健康和生态环境.以联合国开发计划署（UNDP）、环境保护部对外合作中心和全国农业技术推广中心联合启动实施的“中国含滴滴涕三氯杀螨醇生产控制及IPM技术替代全额示范项目”为例,系统分析影响农户参与IPM培训积极性的主要因素.结果表明,农户种植规模对农户参与IPM培训的积极性影响显著,学员性别和年龄不是影响其参加培训积极性的显著因素;学员参加培训的次数越多,其对IPM技术的采纳率越高.农民田间学校应更多地吸收老人和妇女参加三氯杀螨醇替代技术及IPM培训     

Dynamics and driving forces of agricultural landscapes in Southern Ethiopia – a case study of the Chencha and Arbaminch areas

Agricultural landscapes in Ethiopia have undergone unprecedented changes. The direction of change, however, is unsustainable as manifested in land degradation, biodiversity loss, and low agricultural productivity. The objective of this study is to examine the patterns and trends of agricultural landscape development and responses of the local people within the framework of the dynamics of demography, socioeconomic conditions, politics, and natural resources in the Chencha and Arbaminch areas, Southern Ethiopia, during the last century. Information on cultivated and grazing land areas was acquired by satellite image interpretation. Interviews and group discussions provided important information on agricultural land use systems. A review and an analysis of secondary sources and documents of past studies were also used for trend analysis as a baseline and a supplement to oral history. The results show that cultivated land was expanded by 39% from 1973 until 2006, but per capita farming land holdings decreased enormously. In the same period of time, grassland shrank by 69% thus causing a significant decrease in livestock. Cultivated land scarcity can mostly be related to demographic pressure, which was exacerbated by government policy, land tenure, and the nature of subsistence agriculture. The farmers, however, were resourceful and developed skills over millennia to cope with the problems associated with population density and scarce resources. However, these traditional land use activities and land management practices have been deteriorating recently. Land use planners and environmental managers should take local knowledge and innovation into account in order to make sound decisions for the future.     

A Standard Lexicon for Biodiversity Conservation: Unified Classifications of Threats and Actions

Abstract: An essential foundation of any science is a standard lexicon. Any given conservation project can be described in terms of the biodiversity targets, direct threats, contributing factors at the project site, and the conservation actions that the project team is employing to change the situation. These common elements can be linked in a causal chain, which represents a theory of change about how the conservation actions are intended to bring about desired project outcomes. If project teams want to describe and share their work and learn from one another, they need a standard and precise lexicon to specifically describe each node along this chain. To date, there have been several independent efforts to develop standard classifications for the direct threats that affect biodiversity and the conservation actions required to counteract these threats. Recognizing that it is far more effective to have only one accepted global scheme, we merged these separate efforts into unified classifications of threats and actions, which we present here. Each classification is a hierarchical listing of terms and associated definitions. The classifications are comprehensive and exclusive at the upper levels of the hierarchy, expandable at the lower levels, and simple, consistent, and scalable at all levels. We tested these classifications by applying them post hoc to 1191 threatened bird species and 737 conservation projects. Almost all threats and actions could be assigned to the new classification systems, save for some cases lacking detailed information. Furthermore, the new classification systems provided an improved way of analyzing and comparing information across projects when compared with earlier systems. We believe that widespread adoption of these classifications will help practitioners more systematically identify threats and appropriate actions, managers to more efficiently set priorities and allocate resources, and most important, facilitate cross‐project learning and the development of a systematic science of conservation.     

Landscape constraints on functional diversity of birds and insects in tropical agroecosystems

In this paper, we analyzeatabases on birds and insects to assess patterns of functional diversity in human-dominated landscapes in the tropics. A perspective from developed landscapes is essential for understanding remnant natural ecosystems, because most species experience their surroundings at spatial scales beyond the plot level, and spillover between natural and managed ecosystems is common. Agricultural bird species have greater habitat and diet breadth than forest species. Based on a global data base, bird assemblages in tropical agroforest ecosystems were composed of disproportionately more frugivorous and nectarivorous, but fewer insectivorous bird species compared with forest. Similarly, insect predators of plant-feeding arthropods were more diverse in Ecuadorian agroforest and forest compared with rice and pasture, while, in Indonesia, bee diversity was also higher in forested habitats. Hence, diversity of insectivorous birds and insect predators as well as bee pollinators declined with agricultural transformation. In contrast, with increasing agricultural intensification, avian pollinators and seed dispersers initially increase then decrease in proportion. It is well established that the proximity of agricultural habitats to forests has a strong influence on the functional diversity of agroecosystems. Community similarity is higher among agricultural systems than in natural habitats and higher in simple than in complex landscapes for both birds and insects, so natural communities, low-intensity agriculture, and heterogeneous landscapes appear to be critical in the preservation of beta diversity. We require a better understanding of the relative role of landscape composition and the spatial configuration of landscape elements in affecting spillover of functionally important species across managed and natural habitats. This is important for data-based management of tropical human-dominated landscapes sustaining the capacity of communities to reorganize after disturbance and to ensure ecological functioning.     

Past desertification processes of Minqin Oasis in arid China

Irrigated farming has affected most natural oases in western China since the Han Dynasty employed advanced agricultural techniques in dryland areas. To date, little is documented about the process through which these oases were modified by human systems. In this study, a multi-disciplinary approach incorporating analysis of historical documents, archaeological field surveys, satellite imagery, and GIS data was used to understand desertification processes in the Minqin Basin in Gansu Province, China, over the historical period. Results suggest that initial reclamation efforts around the Minqin Oasis were launched in the Han Dynasty (220–121 BC) and culminated in the Wei and Jin Dynasty (220–420). During the following 800 years from the Southern and Northern Dynasties (420–581) to the Yuan Dynasty (1271–1368), farmland disappeared and became desert when the region was taken over by nomadic people. The second period of intense development occurred in the Ming Dynasty (1368–1644) and was followed by another more aggressive development in the Qing Dynasty (1644–1911), which resulted in the largest reclaimed area in history. Oases were constantly reclaimed and subsequently abandoned and desertified over the whole historical period. The causes were complex, but the major cause was related to dynastic transition that often resulted in changes in national policies.     

辽西大凌河流域土地利用变化及驱动力分析

从政策、流域综合治理、经济发展和技术进步、农民认知态度等4方面对影响大凌河流域土地利用变化的驱动力进行了分析。同时运用农户问卷调查和驱动力分析结果,选取影响耕地变化的社会经济和人口因子,运用主成分分析和多元迭代回归分析确定影响耕地变化的主要因子,并拟合出耕地变化的最优度模型。研究结果表明:在1987—2002年期间,农田和未利用荒地面积在不断减小,而林地、果园、草地在不断增加,但1995年后变化边际度大大减小;主成分分析表明影响土地利用变化主要影响因子是农业人口(A-POP)、总人口(T-POP)、农村经济收入(TIRE)、农林牧渔收入(IAFAF)和第三产业总产值(GTI);多元迭代回归分析表明耕地面积变化的最优回归模型中主变量是农业人口(A-POP)、总人口(T-POP)、农村经济收入(TIRE),这些变量能够解释95.1%的耕地变化。     

Marine Ecological Research in New Zealand: Developing Predictive Models through the Study of No-Take Marine Reserves

Abstract:  New Zealand established its first no-take marine reserve more than 25 years ago. Twenty no-take marine reserves have now been created, although few of these are considered comparable. We considered whether existing conceptual models of population and community structure based only on data from exploited systems lack the baseline information of natural states necessary to make accurate predictions for new reserves. Three of the oldest and best-studied reserves are situated on the northeastern coast of New Zealand. These reserves are considered broadly comparable replicates, and research has shown the recovery of previously exploited predator populations and the reestablishment of trophic controls over community structure and productivity. None of the major changes was predicted when the reserves were created. All the observations from and experimental tests of hypotheses in these three ecologically comparable reserves have provided predictive models for future reserves. Recent surveys in newly created reserves, however, suggest that these models are bioregion and habitat specific. In these new reserves the recovery of previously exploited predators was predicted but did not always occur. Where trends were correctly predicted, the speed and amplitude of the changes were not accurately predicted. Research in New Zealand suggests that it is not yet possible to predict explicit outcomes for newly created reserves and less possible to predict detailed results for systems of reserves. Results from a representative system of reserves, including all major habitats within all bioregions and broadly comparable reserves, are needed. Such a system will enable the range and variety of natural ecosystem dynamics to be investigated and provide the controls necessary to measure the effects of exploitation.     

Past desertification processes of Minqin Oasis in arid China

Irrigated farming has affected most natural oases in western China since the Han Dynasty employed advanced agricultural techniques in dryland areas. To date, little is documented about the process through which these oases were modified by human systems. In this study, a multi-disciplinary approach incorporating analysis of historical documents, archaeological field surveys, satellite imagery, and GIS data was used to understand desertification processes in the Minqin Basin in Gansu Province, China, over the historical period. Results suggest that initial reclamation efforts around the Minqin Oasis were launched in the Han Dynasty (121 BC–220 AD) and culminated in the Wei and Jin Dynasty (220–420). During the following 800 years from the Southern and Northern Dynasties (420–581) to the Yuan Dynasty (1271–1368), farmland disappeared and became desert when the region was taken over by nomadic people. The second period of intense development occurred in the Ming Dynasty (1368–1644) and was followed by another more aggressive development in the Qing Dynasty (1644–1911), which resulted in the largest reclaimed area in history. Oases were constantly reclaimed and subsequently abandoned and desertified over the whole historical period. The causes were complex, but the major cause was related to dynastic transition that often resulted in changes in national policies.     

A regression tree-based method for integrating land-cover and land-use data collected at multiple scales

As data sets of multiple types and scales proliferate, it will be increasingly important to be able to flexibly combine them in ways that retain relevant information. A case in point is Amazonia, a large, data-poor region where most whole-basin data sets are limited to understanding land cover interpreted through a variety of remote sensing techniques and sensors. A growing body of work, however, indicates that the future state of much of Amazonia depends on the land use to which converted areas are put, but land use in the tropics is difficult to assess from remotely sensed data alone. An earlier paper developed new snapshots of agricultural land use in this region using a statistical fusion of satellite data and agricultural census data, an underutilized ancillary data source available across Amazonia. The creation of these land-use maps, which have the spatial detail of a satellite image and the attribute information of an agricultural census, required the development of a new statistical technique for merging data sets at different scales and of fundamentally different data types. Here we describe and assess this nonlinear technique, which reinterprets existing land cover classifications by determining what categories are most highly related to the polygon land-use data across the study area. Although developed for this region, the technique appears to hold broad promise for the systematic fusion of multiple data sets that are closely related but of different origins. The figures in the printed version of this article appear in black and white. Color figures are available from the author upon request.     

Multiscale advanced raster map analysis system: Definition, design and development

This paper brings together a multidisciplinary initiative to develop advanced statistical and computational techniques for analyzing, assessing, and extracting information from raster maps. This information will provide a rigorous foundation to address a wide range of applications including disease mapping, emerging infectious diseases, landscape ecological assessment, land cover trends and change detection, watershed assessment, and map accuracy assessment. It will develop an advanced map analysis system that integrates these techniques with an advanced visualization toolbox, and use the system to conduct large case studies using rich sets of raster data, primarily from remotely sensed imagery. As a result, it will be possible to study and evaluate raster maps of societal, ecological, and environmental variables to facilitate quantitative characterization and comparative analysis of geospatial trends, patterns, and phenomena. In addition to environmental and ecological studies, these techniques and tools can be used for policy decisions at national, state, and local levels, crisis management, and protection of infrastructure. Geospatial data form the foundation of an information-based society. Remote sensing has been a vastly under-utilized resource involving a multi-million dollar investment at the national levels. Even when utilized, the credibility has been at stake, largely because of lack of tools that can assess, visualize, and communicate accuracy and reliability in timely manner and at desired confidence levels. Consider an imminent 21st century scenario: What message does a multi-categorical map have about the large landscape it represents? And at what scale, and at what level of detail? Does the spatial pattern of the map reveal any societal, ecological, environmental condition of the landscape? And therefore can it be an indicator of change? How do you automate the assessment of the spatial structure and behavior of change to discover critical areas, hot spots, and their corridors? Is the map accurate? How accurate is it? How do you assess the accuracy of the map? How do we evaluate a temporal change map for change detection? What are the implications of the kind and amount of change and accuracy on what matters, whether climate change, carbon emission, water resources, urban sprawl, biodiversity, indicator species, human health, or early warning? And with what confidence? The proposed research initiative is expected to find answers to these questions and a few more that involve multi-categorical raster maps based on remote sensing and other geospatial data. It includes the development of techniques for map modeling and analysis using Markov Random Fields, geospatial statistics, accuracy assessment and change detection, upper echelons of surfaces, advanced computational techniques for geospatial data mining, and advanced visualization techniques.     

The Links between Protected Areas, Faiths, and Sacred Natural Sites

Most people follow and are influenced by some kind of spiritual faith. We examined two ways in which religious faiths can in turn influence biodiversity conservation in protected areas. First, biodiversity conservation is influenced through the direct and often effective protection afforded to wild species in sacred natural sites and in seminatural habitats around religious buildings. Sacred natural sites are almost certainly the world's oldest form of habitat protection. Although some sacred natural sites exist inside official protected areas, many thousands more form a largely unrecognized "shadow" conservation network in many countries throughout the world, which can be more stringently protected than state-run reserves. Second, faiths have a profound impact on attitudes to protection of the natural world through their philosophy, teachings, investment choices, approaches to land they control, and religious-based management systems. We considered the interactions between faiths and protected areas with respect to all 11 mainstream faiths and to a number of local belief systems. The close links between faiths and habitat protection offer major conservation opportunities, but also pose challenges. Bringing a sacred natural site into a national protected-area system can increase protection for the site, but may compromise some of its spiritual values or even its conservation values. Most protected-area managers are not trained to manage natural sites for religious purposes, but many sacred natural sites are under threat from cultural changes and habitat degradation. Decisions about whether or not to make a sacred natural site an "official" protected area therefore need to be made on a case-by-case basis. Such sites can play an important role in conservation inside and outside official protected areas. More information about the conservation value of sacred lands is needed as is more informed experience in integrating these into wider conservation strategies. In addition, many protected-area staff need training in how to manage sensitive issues relating to faiths where important faith sites occur in protected areas.     

Remote sensing of global change: growth in China's Jiangsu Province

SUMMARY

This paper examines how remote-sensing data and regional social and economic data can be used together to identify changes in land-use patterns in particular regions. Study of the spatiotemporal dynamics of remote-sensing data can identify trends in competing uses of land, water and other natural resources for agriculture, industrial development and urban settlements. When combined with information on trends in industrial production, population, agricultural production, pollutant releases, water usage and natural forest coverage, these data reveal patterns of anthropogenic disturbance that can provide early signals of problems in resource decline or land-use management. This study focuses on land-cover changes in southern Jiangsu Province of the People's Republic of China between 1976 and 1984. This region, to the west of Shanghai and to the south of the Yangtze River, experienced unprecedented economic growth after the end of the Cultural Revolution. Remote-sensing imagery reveals the rapid growth of urban centres, commensurate declines in surface water area, and changing patterns of agriculture. The observed changes cast doubt on the ability of the region to sustain such rapid and intense land-use conflicts over a long period.     

Incorporating spatial autocorrelation into cellular automata model: An application to the dynamics of Chinese tamarisk (Tamarix chinensis Lour.)

Spatial autocorrelation (SAC) is frequently encountered in most spatial data in ecology. Cellular automata (CA) models have been widely used to simulate complex spatial phenomena. However, little has been done to examine the impact of incorporating SAC into CA models. Using image-derived maps of Chinese tamarisk (Tamarix chinensis Lour.), CA models based on ordinary logistic regression (OLCA model) and autologistic regression (ALCA model) were developed to simulate landscape dynamics of T. chinensis. In this study, significant positive SAC was detected in residuals of ordinary logistic models, whereas non-significant SAC was found in autologistic models. All autologistic models obtained lower Akaike's information criterion corrected for small sample size (AICc) values than the best ordinary logistic models. Although the performance of ALCA models only satisfied the minimum requirement, ALCA models showed considerable improvement upon OLCA models. Our results suggested that the incorporation of the autocovariate term not only accounted for SAC in model residuals but also provided more accurate estimates of regression coefficients. The study also found that the neglect of SAC might affect the statistical inference on underlying mechanisms driving landscape changes and obtain false ecological conclusions and management recommendations. The ALCA model is statistically sound when coping with spatially structured data, and the adoption of the ALCA model in future landscape transition simulations may provide more precise probability maps on landscape transition, better model performance and more reasonable mechanisms that are responsible for landscape changes.     

Traditional agriculture in transition: examining the impacts of agricultural modernization on smallholder farming in Ghana under the new Green Revolution

Following the renewed effort at achieving a new green revolution for Africa, emphasis has been placed on modernizing smallholder agriculture through the deployment of improved inputs especially mechanized technologies. In Ghana, the government has in the last decade emphasized the provision of subsidized mechanized ploughing services to farmers alongside a rapidly growing private sector tractor service market. While mechanized technology adoption rates have increased rapidly, the deployment of these technologies has been without critical analysis of the impacts on production patterns and local agrarian systems. This paper examines the distributional impacts of agriculture mechanization on cropping patterns and farm sizes of smallholder farmers in northern Ghana using Geographic Information Systems (GIS) techniques, and semi-structured interviews with smallholder farmers (n=60). Specifically, comparative analysis of the field sizes and cropping patterns of participant farmers prior to and after the adoption of mechanized technologies was conducted. In-depth interviews were used to contextualize the experiences of smallholder farmers toward understanding how mechanization may be impacting traditional agriculture. Our findings reveal a mechanization paradox in which farm sizes are expanding, while cropping patterns are shifting away from traditional staple crops (pearl millet and sorghum bicolor) to market-oriented crops (maize, rice and groundnuts). This transition we argue, has adverse implications on the cultural dimension of food security, the organization of social life, and climate change adaptation. We recommend a retooling of the current agricultural policy focus to ensure context sensitivity for a more robust battle against food insecurity.     

On the use of principal component analysis (PCA) for evaluating interannual vegetation anomalies from SPOT/VEGETATION NDVI temporal series

In this work, we discuss the use of principal component analysis (PCA) for evaluating the vegetation interannual anomalies. The analysis was preformed on a temporal series (1999–2002) of the yearly Maximum Value Composit of SPOT/VEGETATION NDVI acquired for Sicily Island. The PCA was used as a data transform to enhance regions of localized change in multi-temporal data sets. This is a direct result of the high correlation that exists among images for regions that do not change significantly and the relatively low correlation associated with regions that change substantially. Both naturally vegetated areas (forest, shrub-land, herbaceous cover) and agricultural lands have been investigated in order to extract the most prominent natural and/or man-induced alterations affecting vegetation behavior. Our findings suggest that PCA can provide valuable information for environmental management policies involving biodiversity preservation and rational exploitation of natural and agricultural resources.