Figure 2 - uploaded by Jennifer Maria Olson
Content may be subject to copyright.
The Kite Framework. Source: (Campbell and Olson 1991).
Source publication
Scientists, governments and NGOs have a critical need to understand the reasons behind land degradation, desertification and loss of biodiversity. What is needed is an approach that links biophysical and socio-economic processes with land use and land management practices, which in turn would be linked to landscape or ecosystem dynamics. This appro...
Contexts in source publication
Context 1
... framework for environmental reporting that has been used in Europe and by the UN is DPSIR (Figure 2), which was developed in the early 1970s. It was originally designed for assessing the relationship between three types of “indicators”—environmental pressures (the human activity leading to a problem), the state of the environment (the physical condition affected by the pressure) and responses (policies adopted to resolve the problem). It was later refined to include ...
Context 2
... research has provided a wealth of case studies of land use change spatial patterns and driving forces. IGBP compilations of case studies have produced analyses of spatial and temporal patterns, and typologies of the causes of those changes (Lambin et al. 2001; Geist and Lambin 2002; Lambin, Geist, and Lepers 2003). They have identified complex drivers and patterns of society-environment change. Temporal aspects of the drivers include long-term processes, such as population increases or economic development, and shocks such as policy mandates or drought that trigger new directions or rates of change. Theories or conceptual frameworks have been applied to explain the drivers from different starting points, such as rural communities adapting their land use system to environmental conditions, or high human population densities acting as a stimulant for agricultural intensification, or colonialism or globalisation leading to increased land and labour devoted to commercial agriculture and forestry. Agricultural economists and others have explained land use change as due individuals responding to market opportunities affecting the potential value of the land’s production. These approaches place varying emphasis on the role of individual actors versus the broader socio-economic context (structure versus agency), the importance of population dynamics or technology versus policy or other factors, and the effect of differential power and access to resources (Boserup 1965; Turner, Hyden, and Kates 1993; Cleaver and Schreiber 1994; Tiffin, Mortimore, and Gichugi 1994; Biot et al. 1995; Peet and Watts 1996; Scherr and Yadav 1996; Barbier 1997; Ewel 2001). No matter what the researcher’s disciplinary or theoretical perspective, however, drivers are often site-specific – a driver at point A may act differently at point B – which makes generalizing and up-scaling difficult. There has not yet developed, therefore, a universal theory “explaining” land use change. Rather, a common methodological approach to empirically identify the causes, or driving forces, of land use change has evolved (Lambin et al. 1999; Lambin, Geist, and Lepers 2003). This has been labelled pattern to process (Nagendra, Munroe, and Southworth 2004). The approach differentiates proximate drivers that directly affect land use, such as in-migration, road construction or logging, and underlying or root causes that affect land use via the proximate causes, such as land tenure policies or the international timber market. A causal “chain of explanation” is developed for each case that follows factors from the local land manager to the world economy (Blaikie and Brookfield 1987). Statistical analyses of driving forces of land use change in studies from around the world have resulted in identification of common drivers (Geist and Lambin 2001; Lambin et al. 2001; Geist and Lambin 2002; Lambin, Geist, and Lepers 2003). The causes of land use change are usually multiple and there are feedback mechanisms between the drivers, and between the drivers and land use change. Identifying the significant drivers and their interactions, therefore, can be challenging. The most common proximate driver of deforestation, for example, is agricultural expansion (ranching and/or cultivation), often combined with transportation infrastructure development and timber extraction. By far the most frequent root cause is economic factors, followed by institutional factors such as land policies, technological factors, cultural factors, and finally demographic factors (that tend to be inter-linked with other forces). Identifying specific drivers of land use change leading to land degradation is difficult since land degradation is the result of human combined with natural factors, and occurs at the farm or field level as well as at the landscape scale. It can be associated with agricultural land management, or occur on quasi-natural ecosystems such as grazing land. Developing a common framework to direct LULCC land degradation root causes analysis is thus critical for research results to be comparable across sites and to permit generalization and up-scaling of findings. The LUCID Project selected political ecology as its conceptual framework to assist in identifying the causes of land use change associated with land degradation and change in biodiversity (Blaikie and Brookfield 1987; Campbell and Olson 1991; Zimmerer 1994; Peet and Watts 1996; Rocheleau, Thomas, and Wangari 1996; Olson 1998; McCusker and Weiner 2003; Zimmerer and Bassett 2003; Robbins 2004). Political ecologists use tools of critical theory to shape the process of developing hypotheses and research questions to detect the causes of environmental change. Political ecology is appropriate to the questions posed by LUCID in that its contribution has been to explicitly include the important policy and power dimensions, as well as economic and other factors, that affect different groups and their land use. A frequent starting point of political ecology studies is how rural communities manage and adapt within the changing political and economic system. It was originally articulated as an approach to better understand societal factors leading to land degradation; according to Blaikie and Brookfield (1987:17), “the phrase ‘political ecology’ combines the concerns of ecology and a broadly defined political economy. Together they encompass the constantly shifting dialectic between society and land-based resources, and also within classes and groups within society itself.” The parameters of the approach emphasize that land use change results from interactions between society, reflecting economic, social and political processes, and the physical environment. These interactions occur between different scales, and over time and space (the “Kite”, Figure 2) (Campbell and Olson 1991). While LUCID’s socio-economic analyses were based on the interactions represented in the Kite diagram, LUCID’s biophysical research expanded the Kite’s environmental corner to include biological (especially vegetation, wildlife), soil and climatic factors at various scales (Maitima et al. 2004). The conceptualisation of society-environment interaction reflected in the Kite incorporates the following ...
Similar publications
Analyzing the factors influencing emerging industry land use change is important for promoting industrial transformation and for upgrading and improving the level of intensive use of emerging industry land. In recent years, to solve the problem of land resource shortage and expansion space, Shenzhen has implemented a strategy of promoting urban dev...
The mudflow disaster Lapindo in Sidoarjo Indonesia, that has occurred since 2006, until now still poses a risk of danger to residential settlements in the impacted areas. This study aims to make disaster risk analysis and land use changes in disaster impacted areas since before the disaster occurred until now. This research is expected to be very u...
Purpose: Using Landsat OLI remote sensing images in the two phases of 2015 and 2020. Taking Nanjing as the research area. Based on RS and GIS technology, adopting maximum likelihood method for supervised classification, extracting and producing a land use classification map for the two phases of Nanjing from 2015 to 2020. And further, using the lan...
Life Cycle Greenhouse Gases (GHG) emissions from biofuels can be significantly affected if the effect of indirect Land Use Change (iLUC) is considered, especially in the case of first generation biofuels. This study presents the theoretical concept of iLUC and its relationship with GHG emissions, the different models to quantify this effect and the...
Citations
... El aumento de la población mundial (Monjeau et al., 2015; Gomes da Silva et al., 2020;Smith y Archer, 2020) supone una mayor demanda de recursos como alimentos, agua y energía, además de una expansión de áreas urbanas y agrícolas (Ramankutty et al., 2002;Paruelo et al., 2005;Pimentel y Pimentel, 2006;Cleland, 2013), causando deforestación, degradación del suelo y pérdida de biodiversidad (Scherr y Yadav, 1996;Oldeman, 1998;Reyes y Gandhi, 2003: Olson et al., 2004Giam, 2017;Castro Vélez, 2018;Franco et al., 2019;Ferreira et al., 2022;Cañete et al., 2023), llevando a cambios que afectan a personas y ecosistemas. ...
La necesidad de incrementar los recursos para sostener una población mundial en crecimiento altera el equilibrio de los ecosistemas, especialmente los de uso pastoril. Entre estos se encuentra el ecosistema Campos, que incluye al Campo Natural, ocupando un 57,23% del territorio de Uruguay (30-35°S, 53-58°W). Este ecosistema está compuesto por gramíneas, hierbas, ciperáceas, arbustos y leguminosas, y se dedica a la explotación comercial de ovinos y bovinos. En la búsqueda del mejor balance entre ambos herbívoros para un pastoreo sostenible, se estableció, desde marzo de 2008 hasta septiembre de 2011, un experimento de pastoreo mixto y único, compuesto por tres relaciones ovino-bovino y ambas especies por separado. Los efectos del pastoreo sobre el Campo Natural se registraron en los grupos funcionales que representan la condición de la vegetación, observándose la mejor respuesta con pastoreo mixto, mientras que el pastoreo único produjo un desbalance diferente según se tratara de ovinos o bovinos, lo que se tradujo en una pérdida de condición. Se discuten las implicancias de estos resultados sobre la sostenibilidad del sistema.
... The increasing inadequacy of pastoral land due to restricted livestock mobility and its alienation and appropriation through the change in land tenure have also reduced the capacity of households to raise adequate livestock herds. Land fragmentation and expansion of crop cultivation into pastoral areas have led to a reduction of available pastoral resources and weakened the sustainability and resilience of pastoral systems (Olson et al., 2004;Müller-Mahn, Rettberg and Getachew, 2010). Furthermore, Letai and Lind (2013) established that restricted mobility has heavily impacted herd sizes in the East Africa region. ...
Pastoralism is a complete way of life involving ecological, political, economic and social dimensions, and is dependent on a continuous balance of diverse factors. However, pastoral systems are faced with emerging and accelerating shocks and stresses that challenge their resilience and the ability to meet household livelihood needs sustainably. In response to these pressures, pastoralist socioecological systems in Africa are undergoing a process of rapid transformation that is marked by positive and negative socio-ecological trends. This study, therefore, analyzed the socioecological trends of pastoral systems with a focus on Laikipia County, Kenya. The study used a participatory action research design and multi-stage sampling design. Data collection and analysis were done using the participatory trend analysis method, while Mann-Kendall Z Test and Kendall’s correlation coefficient were used to test the trends and their relationships. This study finds that pastoralists’ culture and lifestyles are changing as shown by the negative trend in observation of cultural practices (Z = - 4.22, P<0.001) and effectiveness of customary governance systems (Z = - 0.401, P<0.001). Secondly, although the total number of livestock is increasing (Z = 3.11, P<0.01), there is a downward trend in the livestock holding per household (Z = -3.83, P<0.001), and, hence increasing diversification to non-pastoral livelihoods (Z = 4.28, P<0.001). These changes are caused by the growing pressure on pastoral resources and ecological stresses due to various factors, including the increasing human population (Z = 4.22, P<0.001), land degradation (Z = 4.17, P<0.001), and climate change and variability (Z = 4.05, P<0.001). Therefore, the study enabled an understanding of pastoralists’ socioecological trends and the underlying drivers. Moreover, the study showed the impacts of the drivers, their feedback on each other, and the responses of the pastoral system. The study will strengthen pastoral development planning and policy-making processes.
... There is growing evidence showing that there has been extensive conversion of rangelands land cover types such as grasslands, woodlands and wetlands into farmlands in Eastern Africa in the past three decades [47,48]. For instance, farmlands increased by 171.2% in Ethiopia's Bale zone [49] and in Borana rangelands of Southern Ethiopia [50]. ...
... The 1990s immigration of people from Lango region into Nakasongola district were linked with exerting pressure on some forests, woodlands and wetlands for settlement and crop farming. This confirms earlier findings showing that most of the woodlands in the rangelands of East Africa have been lost to subsistence farming and collection of wood fuel including charcoal and firewood collection [47]. Similarly, Mwavu and Witkowski [62] reported that population growth and agricultural expansion led to the loss of 8.2% of forested land in Budongo forest to sugarcane cultivation. ...
Sustainable rangeland management requires understanding the nature of human-ecosystem interactions and local communities’ perspectives regarding evolving changes. This study integrated perceptions from the local community and remote sensing to characterize the extent and drivers of land use and land cover (LULC) changes in the rangelands of Nakasongola district in Central Uganda. The aim of the study was to determine the perceived drivers of land use and land cover change in of Nakasongola district in the Central Uganda district to support decision making for present and future rangeland management. Satellite imagery for 1985, 1995, 2005, 2015 and 2021 were obtained from the United States Geological Survey (USGS) and analyzed to determine the LULC dynamics. Key informant interviews and focus group discussions (FGDs) were conducted to obtain perceived drivers of LULC. Results showed that by 1985 grassland covered 31.7%, wetlands 26.4%, woodland 11.5% and farmland 7.2% of the total land area. However, by 2021, farmland covered 35.8% of the total land area, wetland 21.6% and had reduced to grassland 18.5 percent. Future LULC projections using a Markov chain model showed that farmland cover will increase by 13.85% while grassland cover will further decline by 9.89% in 2040. Wood fuel extraction, subsistence farming, population growth and overgrazing were perceived as key drivers of LULC change. Both remote sensing techniques and local perceptions were in agreement with the identification of patterns and perceived drivers revealing the inherent value of tacit knowledge resident within the community. This knowledge in addition to remotely sensed information can thus be tapped by the decision leaders to better guide interventions aimed at securing better rangeland health and management.
... Some areas will experience additional agricultural land, including in the upstream watershed [3]. This event will have a broad impact, especially on biodiversity, decline in ecosystem functions, and even destroy plant and animal ecosystems [4][5][6]. ...
... Over-exploitation of land in national park areas has certainly resulted in a decrease in land productivity. In addition, pressure on forests in national parks will have an impact on biodiversity, even to the point of decreasing ecosystem functions [4,5]. ...
The community has used the land throughout the area without exception in the forest area. The function of forest areas also varies based on the biophysical conditions of a land. The Maros River Basin has a complex forest area function ranging from production forest, protection forest to conservation forest (National Park). In addition, the Maros watershed also has its own uniqueness in the form of a karst ecosystem and biodiversity. This requires information related to activities, and the role of forests for people who use land in forest areas to meet their daily needs. Based on this, this study aims to analyze land use patterns, and socio-economic characteristics of the people in the Maros River Basin. This analysis begins with spot image analysis, and land use interpretation. The second analysis conducts detailed observations of land use in the field based on the results of land use interpretations that indicate community activities in forest areas. The last analysis is the socio-economic conditions, and the influence of the role of the forest on the community in using land in the forest area. The results of the analysis show that each area function is dominated by land use patterns in the form of dry land mixed with shrubs, rice fields, plantations, plantation forests, and secondary forests. Land use in the form of dry land mixed with shrubs is used as seasonal crops such as corn and horticulture. The use of plantation land, the community gets results in the form of candlenut and coffee. The use of plantation forest land is used to obtain pine resin, while the community uses the secondary forest as non-timber forest products such as honey bees and bamboo. The level of education of people who use forest areas is still low and the average income from the use of these areas is Rp. 1,372,679, - lower than the minimum wage in South Sulawesi Province.
... In these regards, soil degradation is defined here as a complex process impacting crop production and resulting in the decline of environmental quality and ecosystem services [54]. The distribution of soil quality is assumed to be spatially heterogeneous, depending on geological, climatic, vegetation, and human factors [64,65]. In recent years, however, climate and land-use changes, population increase, and differential economic growth were also assumed to exacerbate soil sensitivity to degradation. ...
... Taken together, these results refine and corroborate the empirical findings presented in earlier studies [79], outlining the need for more careful identification of local "hotspots" of soil degradation in non-affected regions. Furthermore, our study confirms that the increased sensitivity to soil degradation in Italy depends on the synergic impact of biophysical and socioeconomic factors [64,65,73]. Interestingly enough, the socioeconomic drivers of soil degradation, including changes in land management, crop intensification, population growth, and urban sprawl, explain the larger increase in the degree of land sensitivity especially in the less ecologically "fragile" areas, with definite implications for policies aimed at reducing socioeconomic disparities among regions [83][84][85]. ...
Following an operational framework derived from earlier research, our study research estimates the specific contribution of biophysical and socioeconomic factors to soil sensitivity to degradation at two-time points (Early-1990s and Early-2010s) in Italy, a Mediterranean hotspot for desertification risk. A total of 34 variables associated (directly or, at least, indirectly) with different processes of soil degradation (erosion, salinization, sealing, contamination, and compaction) and climate change were considered here, delineating the predominant (underlying) cause (i.e., biophysical or socioeconomic). This set of variables represented the largest (quantitative) information available from national and international data sources including official statistics at both national and European scale. Contribution of biophysical and socioeconomic dimensions to soil sensitivity to degradation was heterogeneous in Italy, with the level of soil sensitivity to biophysical factors being the highest in less accessible, natural areas mostly located in hilly and mountainous districts. The highest level of soil sensitivity to socioeconomic drivers was instead observed in more accessible locations around large cities and flat rural districts with crop intensification and low (but increasing) population density. All these factors delineated an enlarged divide in environmental quality between (i) flat and upland districts, and between (ii) Northern and Southern Italian regions. These findings suggest the appropriateness of policy strategies protecting soils with a strong place-specific knowledge, i.e., based on permanent monitoring of local (biophysical and socioeconomic) conditions.
... Single and female heads of households have a different outlook and life expectation than those married. The data support earlier studies, such as [19] [20] who found that men and women have different roles and responsibilities in land use and economic systems. Gender greatly impacts land use and land management practices which eventually leads to land degradation. ...
... These findings do not seem to support earlier studies such as [19] and [34] who found that the distribution of land between households may greatly influence local land use patterns. They further observed that farmers with larger farm sizes are more capable of undertaking investments because they can spare land areas for fallow, and for planting trees, while putting larger portions of their lands under cultivation. ...
... In addition, they assert that a large farm is often correlated with wealth and this helps to motivate farmers to invest in land conservation measures as they expect to earn a larger income from the farm and this releases pressure from wetlands. However, [19] argues that the impact of wealth on land use may be very visible if the land is consolidated, e.g., a plantation or ranch, but may be less obvious if farms are fragmented which is the case in the two study catchments. Limited size of land farmed may change livelihood strategies and lead to higher dependence on wetlands and off-farm income. ...
... Changes in forest cover in plantations are not categorized as deforested areas because changes in cover do not occur permanently [12]. Accuracy and Kappa accuracy tests are used to assess the reliability of image classification [12,[20][21][22] ...
Deforestation is an activity or process that converts forest cover into non-forest land cover with a certain pattern. Palopo and East Luwu are two districts in South Sulawesi deforested due to the demand of the human need to convert the land into settlements, infrastructure and timber harvesting. This research was conducted to find out the temporal spatial pattern in dealing with deforestation. Analysis of spatial patterns using fragstat software with input data i.e. land cover shapefile data in 1990, 2000, 2010, and 2016 that produced contour in metrics, and its subdivision in metrics. Temporal spatial patterns of deforestation are built by combining three spatial metric values. Based on the description of deforestation analysis in Palopo Municipality covering 852,96 ha and East Luwu with 86,963,46 ha, Palopo Municipality experienced the highest deforestation from 1990 to 2000 amounted to 451.69 ha and continued to decline in the period of 2000-2010 and 2010-2016. Deforestation in East Luwu Regency is the highest in the 1990-2000 period which is 38.655,05 ha. Deforestation in East Luwu Regency has higher contiguity than deforestation occurring in Palopo Municipality indicating that the occurrence of deforestation occurring in East Luwu Regency occurred directly from previously degraded areas to adjacent forest areas. Palopo and East Luwu Regency show fragmentation rates that tend to decrease due to the decreasing number of fillings that are formed the largest combination of spatial patterns occurring during the observation period was the spatial pattern of deforestation grouped, with high density (not fragmented) in 50 villages (61.72%).
... Lambin et al. (2001) argue that myths about the causes for land change have been propagated through simplification in line with prevalent worldviews. Olson et al. (2004) agree that the socio-economic dimensions of land-use change are often analysed in simplistic ways that fail to capture the causal processes behind changing land management and land-use practices. The analysis of land degradation often focuses on simplified single-factor causes, and misses the fact that land degradation is usually the result of multiple drivers ( . ...
... The number of locational studies applying multidisciplinary, multi-scalar approaches to the study of land change are increasing and improving understanding of land issues. These have identified a wide range of interconnected economic, demographic, technological, institutional and cultural drivers from local to global scales that interact over time to shape land-use trajectories ( Olson et al. 2004). They have identified feedback mechanisms between the drivers and shown how land changes can also have feedback effects on the drivers. ...
... Various theoretical positions and concepts can and have been applied to studies of land change drivers, and as they have quite different starting points they can lead to quite different conclusions. They differ in the emphasis they place on the role ascribed to actors versus the wider socio-economic context (agency versus structure), the importance of demographic and technological factors versus policy or other factors, and how differential power affects access to resources ( Olson et al. 2004). No universally accepted theory of land change has emerged. ...
https://pub.iges.or.jp/system/files/publication_documents/pub/book/6911/NRE%20Flagship%20all_Web%20Final%20May2019.pdf
The Asia-Pacific region faces a fundamental dilemma. Over recent decades the region has achieved tremendous economic growth that has lifted millions of its people out of poverty and raised living standards, but in many places the way land is being used to generate this growth is unsustainable. Land has been exploited – growing economies regardless of the costs to biodiversity and ecosystem services. For biodiversity, the impacts are alarming – almost 25% of the region’s endemic species are at risk – and threats are growing. For ecosystem services, the impacts are no less severe: over 2,500 million ha of land are degraded, four fifths of rivers are polluted and the region is quickly losing its major terrestrial sinks and stores of greenhouse gases, namely its forests and peat lands. If the causes of unsustainable land use are not addressed with a greater sense of urgency, the consequences will become increasingly severe. Unsustainable land use is driving climate change, and simultaneously increasing the region’s vulnerability by decreasing options for adaptation.
This report – “Asia-Pacific landscape transformations – Solutions for sustainability” – was motivated by the stark and rapid changes in landscapes that can be observed across the region and their consequences. It was also motivated by a lack of appropriate visions of sustainable landscapes in policy and decision-making, and the need for better understanding of integrative approaches that can help realise these visions. It argues that a vision of sustainable landscapes can guide policymaking and administration towards more effective cross-boundary management of interdependent ecosystems.
... Deforestation is a global environmental problem followed by issues of land degradation, biodiversity, food security, and environmental sustainability [11,12]. Deforestation has an impact on climate change, increased weather, the occurrence of forest fires, the increasing incidence of natural disasters, and threats to biodiversity. ...
Deforestation is an event of loss of forest cover to another cover. Sulawesi forests have the potential to be deforested as with Sumatra and Kalimantan. This study aims to provide information on deforestation events in Sulawesi from 1990 to 2018. The data used in this study are (1) land cover in 1990, 2000, 2010; (2) Landsat 8 imagery in 2018; (3) administrative map of BIG in 2018. The methods used are (1) image classification with on-screen digitation techniques following the PPIK land cover classification guidelines, Forestry Planning Agency (2008) using ArcGIS Desktop 10.6 from ESRI; (2) overlapping maps; (3) analysis of deforestation; (4) analysis of deforestation profiles, (5) vulnerability analysis; and (6) analysis of distribution patterns of deforestation. The results showed that the profile of deforestation occurring on Sulawesi Island in the 1990–2018 observation period was dominated by profile 3-1-1 (the proportion of large forest area, the highest incidence of deforestation early stage at the beginning, at a low rate) in 13 districts. The level of vulnerability to deforestation is a non-vulnerable category (37 districts) which is directed to become a priority in handling deforestation in Sulawesi. Spatial patterns of the deforestation that occurred randomly and were scattered are dominated by shrubs, dryland agricultural activities, and small-scale plantations.
... Mapping of LULC changes using remote sensing gives quantitative descriptions of the transformation. But, it fails to explain or provide an understanding of the relationship between the cause of change and their driving forces (Kindu & Schneider, 2015;Olson, Misana, Campbell, Mbonile, & Mugisha, 2004). Studies of rates, extents, patterns, causes, and implications of LULC dynamics at watershed level can then provide an opportunity to design appropriate land management practices, strategies, policies and also to implicate the consequential hazards on the natural ecosystem. ...
Unprecedented pace and magnitude of land use/land cover (LULC) change in the Ethiopian highlands is a key problem threatening the natural ecosystem and creates vulnerability to an environmental hazard. A combination of remote sensing, field observations and focus group discussions were used to analyze the dynamics and drivers of LULC change from 1985 to 2011 in the Keleta watershed, Ethiopia. Supervised image classification was used to map LULC classes. Focus group discussions and ranking were used to explain the drivers and causes linked to the changes. The result showed rapid expansion of farmland and settlement (36%), shrublands cover shrinking by 50%, while the size of degraded land increased by 45%. Rapid population growth, rainfall variability and soil fertility decline, lack of fuelwood and shortage of cultivation land were ranked as the main causes of LULC change in the watershed according to the focus group discussion. Further effort is needed to improve the creation of new job opportunity, promotion of improved technologies to boost productivity and soil fertility, provide credit facility, extra push on irrigation infrastructure development and soil, water and natural ecosystem conservation practices. Generally, better community-based land resource management will need to ensure sustainable rural livelihoods.
