Rate-Induced Transitions in Networked Complex Adaptive Systems: Exploring Dynamics and Management Implications Across Ecological, Social, and Socioecological Systems

Complex adaptive systems (CASs), from ecosystems to economies, are open systems and inherently dependent on external conditions. While a system can transition from one state to another based on the magnitude of change in external conditions, the rate of change -- irrespective of magnitude -- may also lead to system state changes due to a phenomenon known as a rate-induced transition (RIT). This study presents a novel framework that captures RITs in CASs through a local model and a network extension where each node contributes to the structural adaptability of others. Our findings reveal how RITs occur at a critical environmental change rate, with lower-degree nodes tipping first due to fewer connections and reduced adaptive capacity. High-degree nodes tip later as their adaptability sources (lower-degree nodes) collapse. This pattern persists across various network structures. Our study calls for an extended perspective when managing CASs, emphasizing the need to focus not only on thresholds of external conditions but also the rate at which those conditions change, particularly in the context of the collapse of surrounding systems that contribute to the focal system's resilience. Our analytical method opens a path to designing management policies that mitigate RIT impacts and enhance resilience in ecological, social, and socioecological systems. These policies could include controlling environmental change rates, fostering system adaptability, implementing adaptive management strategies, and building capacity and knowledge exchange. Our study contributes to the understanding of RIT dynamics and informs effective management strategies for complex adaptive systems in the face of rapid environmental change.Comment: 25 pages, 4 figures, 1 box, supplementary informatio

Crop booms in forest frontiers: Zooming in and out

Agricultural expansion into large forested and extensively-used areas, so-called forest frontiers, is a process with a long history and which is expected to continue in the future, driven by increasing global trade, affluence, and urbanization processes. A large part of this transition from extensive to intensive land use is taking place in montane areas where traditional “shifting cultivation”, the production of crops interspersed with long fallow periods, is being replaced with perennial plantations or annual crops aimed for export, also called cash crops. Agricultural transitions present important opportunities for rural development by raising household incomes, freeing up household labor, and enabling farmers to send their children to school. The construction of schools, as well as hospitals and other services, also hinges on the development of transport infrastructure, which in turn connects rural areas to regional and global markets. Such economic development can lift rural populations out of poverty, increase access to services, and expand the range of livelihood options. However, agricultural transitions can also have wide-ranging negative ecological and social implications. The loss of biodiversity in primary and secondary forests is compounded by the erosion, water pollution, and soil depletion that are frequently associated with intensive agricultural production. Land tenure regimes change from collective, shared, and informal, to private ownership associated with growing high-value crops. This process can result in an inequitable allocation of land, and in the emergence of a class of dispossessed persons in rural areas. The result can be a net loss of livelihood options, an increase in livelihood vulnerability, and a decrease in the ability to recover from shocks. The negative and positive outcomes frequently happen concurrently. When assessed at a local or regional level, rural areas are, on average, better off than before if they are better connected to services and markets, and average household incomes are higher. However, at the tail end of the income probability distribution are those who lose out. Agricultural transitions not only bring about vast socioecological changes, but frequently also happen abruptly in the form of so-called crop booms. Such booms are localized instances of very rapid agricultural expansion. The speed, abruptness, and intensity of change makes crop booms difficult to predict and understand. At the same time, it is precisely because of these characteristics that it is important to gain an understanding of these dynamics, since rapid change is known to compound negative socioecological outcomes. In northern Laos, the renewal of economic and political cooperation between Laos and China in the 1990s, coupled with new land use policies aimed at rural development and forest protection, as well as government-driven rural village relocations, created a conjuncture that has profoundly changed agricultural landscapes. The traditional system of shifting cultivation has been partially or entirely replaced by cash crop plantations in some areas, and rice production for household consumption has significantly decreased. Northern Laos’ Luang Namtha Province, bordering on China’s Yunnan Province, has seen a number of successive crop booms in the last decades, including the sugarcane boom in the late 1990s, the rubber boom starting around 2003, and the banana boom in 2011-2016. Importantly, these booms have largely been driven by smallholders and not by large scale agribusiness companies. Ethnic minority villages in these montane areas are seeing unprecedented levels of development and have now improved access to education, healthcare, and to larger and more distant markets. The reliance on cash crops for household income, which has been described as a dependence, makes households vulnerable to market volatility, especially if they rely on cash to buy food. However, prior to the advent of cash crops, traditional subsistence-oriented livelihoods were also subject to large risks and harvest failures. The aim of this work is two-fold. First, it aims to explain why crop booms happen. Second, it analyzes the impact of agricultural transitions on livelihoods. It focuses on two cases study areas and eleven villages in Luang Namtha Province. Empirical analysis is based on household surveys (n=110) and interviews with villagers, government officials, and investors, carried out between 2016 and 2017. Data collection focuses on household land use and socioeconomic trajectories since the late 1990s, and the reasons for those changes, including historical, institutional, economic, and biophysical. Within these spatial and temporal boundaries, this work aims to understand the causes of cash crop booms – with a focus on the rubber boom – and the implications of cash crop uptake on livelihood vulnerability. This work thus contributes to the field of Land System Science (LSS) by analyzing the dynamics and effects of land systems change. Chapter 2 uses a mix of qualitative and quantitative analysis to “tell the story” of the northern Laos rubber boom. The two case study areas under analysis underwent different trajectories of change. Whereas one experienced a full-fledged boom, rubber uptake was slower and lower in the other area, where other cash crops were planted as well, including cardamom, which is less lucrative but also less costly to plant. The comparison between the two case study areas offers insights about the triggers, drivers, and hindering factors that affected rubber adoption and expansion by smallholder farmers. By framing crop booms as land regime shifts, I explore the set of preconditions, triggers, and self-reinforcing factors that help explain the timing and the intensity of the boom. I focus on the decision-making processes underlying rubber adoption and expansion decisions. The household survey offers insight into the motivations for adoption and the influence of external factors, such as social relations and crop price information. The analysis is based, on the one hand, on descriptive statistics, for instance showing the proportion of the population that adopted rubber based on information versus imitation. On the other hand, it uses regression analysis to take into consideration, or control for, household characteristics and biophysical factors that affected rubber uptake. Chapter 3 is based on the insights generated in Chapter 2 and presents a more quantitative approach to the same question of rubber boom dynamics. Its aim is to elucidate the relative importance of drivers and hindering factors affecting rubber expansion, such as prices, imitation dynamics, accessibility, or protected area status. I define a price signal and a rubber conversion signal to represent the influence of commodity prices and imitation on land use decisions. I develop a model of land use change, which uses a probabilistic approach based on Bayesian Networks (BN), which allow the graphic representation of interlinked and correlated variables. In addition, regression analysis provides insights about such correlations, and about changes in relationships over time. Chapter 4 is focuses on livelihood vulnerability and explores the livelihood impacts of cash crop production compared to subsistence agriculture. A further aim is to analyze whether agricultural diversification reduces vulnerability, as is commonly proposed. The methodology applied is also based on a BN. BNs are well-suited for the analysis of risk and vulnerability because they quantify variables as probability distributions. Similarly, one way to quantify livelihood vulnerability is to analyze the probability distribution of a measure of well-being (e.g., income), in order to assess its mean and standard deviation, which influence how likely it is that a household will fall under a well-being threshold. By expressing all variables as probability distributions, this methodology allows to reflect “stressors” such as harvest failures or price drops. This is an innovative approach to measure household vulnerability, although the conceptual definition and calculation of vulnerability as a function of mean and standard deviation of a measure of well-being is not new. The model is run for different household types in both case study areas, comparing better off and poor households, as well as households with different levels of crop diversification. The limitations of this approach in terms of capturing the complexity of household vulnerability are discussed at length. Chapter 5 presents a discussion that goes back to the original questions: why do crop booms happen, and what is their implication for livelihood vulnerability. It analyzes crop booms as regime shifts but also as outcomes of relational processes, such as social relations and trade relations. It zooms in on the specific market dynamics that characterize crop booms, which are at the same time processes of agricultural and market expansion. The chapter also contrasts the findings from Chapter 4 with other work that has analyzed changing vulnerabilities in agricultural transition contexts. Finally, I discuss the suitability and the limitations of the methodology applied in the previous three chapters. Chapter 6 contains a reflection on the relevance of this work to society, including the research community and society at large. It also presents an outlook for future work – from low-hanging to exotic fruits – that could build on this research and address further questions

Assessing livelihood vulnerability using a Bayesian network: a case study in northern Laos

ABSTRACT. Agricultural transitions from subsistence to export-oriented production make households more reliant on volatile agricultural commodity markets and can increase households’ exposure to crop price and yield shocks. At the same time, subsistence farming is also highly vulnerable to crop failures. In this work, we define household livelihood vulnerability as the probability of falling under an income threshold. We propose the use of a Bayesian network (BN) to calculate the income distribution based on household and community-level variables. BNs reflect relationships of dependence between variables and represent all variables as probability distributions, which allows for the explicit propagation of variability and uncertainty between variables. We focus on two agricultural frontier case study areas (CSAs) in northern Lao PDR that are at different stages in the transition from subsistence to export-oriented agriculture. Because agricultural production is the main livelihood activity in both CSAs, we develop a BN that calculates the probability distribution of net household agricultural production income. BN structure and parameterization are based on data collected in 110 household surveys across both CSAs, as well as interviews with villagers, government officials, and private sector actors. We analyze the effect of crop price and yield variability, land-use portfolio, and land holdings, on the probability of having a negative net agricultural income, which reflects a household’s ability to meet its food consumption needs through cash crop sales. Results show that agricultural income is highly sensitive to rubber plantation area, rubber yield, and rubber price given the very large income potential of the crop. Households with larger agricultural areas have a lower probability of falling under an agricultural income threshold regardless of their diversification choices. Households that own more high-value cash crops are more buffered against rice yield shocks despite having higher agricultural income variability. However, low-income households are better off if they maintain a minimum level of rice sufficiency in combination with high-value cash crop production. Diversifying upland cash crops by increasing the share of cardamom (a lowvalue but low-volatility crop) at the expense of rubber (a highly lucrative crop with high price volatility) does not have a sizable beneficial impact, because returns from cardamom are significantly lower than for rubber. We show that BNs can be useful tools for the design and evaluation of rural development policies.ISSN:1708-308

Structural change in agriculture and farmers' social contacts: Insights from a Swiss mountain region

CONTEXT: Farm numbers are steadily declining in Europe and globally while farms become larger and more intensive. Driven in part by worsening macroeconomic conditions, these structural changes and the associated rationalization of agricultural supply chains have affected social relations in rural areas. In turn, farmers' social contacts influence farming decisions. Social and structural changes are thus interconnected, and they affect the resilience of rural areas through their influence on environmental, social, and economic capital. OBJECTIVE: We examine the connection between farm structures and farmers' social contacts in the UNESCO Biosphere Reserve Entlebuch (UBE), a mountain region in central Switzerland with a strong presence of family farms, and explore the implications of social and structural change for rural resilience. METHODS: We conduct a survey of N =102 farming households and combine it with farm-level agricultural census data and interviews with key stakeholders (N =13) to analyze farmers' current social contacts and their changes since the year 2000. We use regression and cluster analyses to examine the relationship between (changes in) social contacts and farm-level characteristics. RESULTS AND CONCLUSIONS: Farmers in the UBE have a high, but decreasing frequency of contacts with family, friends, and colleagues and lower, but increasing frequency of commercial and administrative contacts. Work-loads have increased by 6% in five years, driven by farm-level expansion of agricultural area (+5%)—including expanding ecological compensation areas—and intensification in managed areas (+3%), leading to parallel processes of intensification and extensification. Since most of these family farms do not hire workers, growing workloads directly impinge on farmers' free time, affecting informal contacts most. Farm managers in larger and more intensive farms have more frequent and more diverse, but also more rapidly declining, social contacts. Our results point to a net loss in social capital as social contacts become less frequent and shift from local and informal to regional and national professional contacts. SIGNIFICANCE: A 17% decline in farm numbers in 15 years reflects the vulnerability of farms in this region. Growing financial strain, workloads, time pressure and the associated erosion of informal contacts contribute to this vulnerability. Policymakers from local to national should recognize the contribution of farmers' diverse social networks towards rural resilience and seek options to maintain and enhance such networks. Beyond direct interventions that foster social capital, policymakers should more rigorously consider the short- and long-term interconnections and tradeoffs between different forms of capital.ISSN:0308-521

From global drivers to local land-use change: understanding the northern Laos rubber boom

Crop booms in forest frontiers are a major contributor to land conversion and deforestation. In this study, we investigate the smallholder-driven northern Laos rubber boom in two case study areas (CSAs) with different speed and intensity of rubber expansion. We assess the relative importance of market, contextual, and behavioral factors in fostering or hindering the conversion of forest to rubber plantations. We develop a Bayesian network (BN) model of land-use change based on household surveys, expert interviews, market price data, and land use maps covering the period 2000–2017. We use regression analysis to inform the structure of the BN, compare model results, and analyze time-varying effects. The BN and regression models incorporate perceived price signals as a combination of market price and local price knowledge, and local self-reinforcing imitation dynamics as a combination of aggregate rubber conversion and imitation behavior elicited in the survey. Results show that deforestation was lower in strictly protected areas but not in forests with lesser protection status. Imitation had a large effect on rubber uptake in both areas. In the CSA that experienced the most intensive spread of rubber, price signals transmitted through social networks had a significant impact, especially throughout the stage of rapid expansion. Rubber expansion continued in both areas during periods of descending prices mainly because of increased cash availability and access to inputs. Our research sheds light on the underlying dynamics of crop booms and contributes to the understanding of agricultural expansion processes.ISSN:1462-9011ISSN:1873-641

Biofuel greenhouse gas calculations under the European Renewable Energy Directive - A comparison of the BioGrace tool vs. the tool of the Roundtable on Sustainable Biofuels

The European Renewable Energy Directive (EU RED) requires biofuels to reduce greenhouse gas emissions (GHG) by 35% compared to fossil fuels in order to count towards mandatory biofuel quota or to be eligible for financial support schemes. This reduction target will rise to 50% in 2017. For biofuel producers this implies that they want or need to calculate their emissions. The purpose of this paper is to compare two calculation tools for economic operators that are on their way to the market: the "BioGrace tool" and the "Roundtable on Sustainable Biofuels (RSB) GHG tool" for GHG calculations under the Renewable Energy Directive (both of which are freely available). Greenhouse gas emissions from four production pathways were calculated: ethanol from wheat, ethanol from sugarcane, biodiesel from rapeseed and biodiesel from palm oil. In addition, three land use change (LUC) scenarios were calculated: for expansion of the biofuel cultivation area to grassland and to forest (10-30% canopy cover) and for improvement of agricultural practices. Both tools follow the methodology of the European Renewable Energy Directive and exactly the same input data along the production chain was used. Despite this, the results were significantly different. GHG emissions of the pathway ethanol from wheat were 21% lower when calculated with the BioGrace tool than with the RSB GHG tool. Differences were most pronounced in the cultivation phase with 20% deviation between the tools for biodiesel from palm oil and 35% deviation for ethanol from wheat and sugarcane. In practice this means that an economic operator can enhance the GHG performance of his biofuel by 20-35% by using a different calculation tool without improving the production process. We identified the use of different standard values in the two tools, in particular for the production of N-fertilisers, for chemicals and electricity and one methodological choice regarding the calculation of field N2O emissions as source of these differences. This methodological point is not specified in the Renewable Energy Directive, giving economic operators and tool developers free choice. GHG emissions from land use changes varied by -14% to 49% due to differences in carbon stock data, methodological differences in allocation and a lack of precise land use type definitions. We conclude from the results that there is a need for a deep harmonisation in the calculation process that goes beyond the methodological framework set up in current legislation. These findings are relevant because they show a policy gap, a regulatory gap that needs to be addressed by policy makers in order to guarantee a level playing field on the market and to create an incentive to improve the GHG performance of biofuel production. (C) 2012 Elsevier Ltd. All rights reserved

Beyond the boom-bust cycle: an interdisciplinary framework for analysing crop booms

International audienceThe expansion of commercial agriculture is one of the primary drivers of livelihood and land-use changes in the world. Globalisation and other factors have intensified this expansion to the point where booms in single cash crops overtake entire regions before going bust, a pattern that is particularly pervasive in resource frontiers. Using case studies across the Mekong Region, a place which serves as a harbinger for crop booms globally, we propose a new analytical framework for understanding and governing crop booms. We combine multiple theoretical approaches to study crop booms and draw on insights from case study work conducted across temporal and spatial scales. The framework consists of three components: 1) the nested nature of crop boom-bust trajectories, 2) the cyclical spatial and temporal patterns of crop booms, and 3) the variegated pathways and impacts of agrarian change. The framework presents new insights into the processes of agricultural intensification in frontier spaces. As such, it facilitates a better understanding of the drivers, characteristics and impacts of crop booms for researchers and decision-makers alike with the intention of supporting efforts to develop more sustainable pathways in the region and beyond

Transformar la realidad : revista de investigación y experiencias educativas

Presenta una unidad didáctica de Educación Física para el segundo ciclo de educación primaria. La unidad es el resultado del grupo de trabajo creado en el Seminario de Educación Física llevado a cabo por el CPR de Leganés. El tema elegido es 'El Equilibrio', y la unidad didáctica se desarrolla a través de 6 sesiones dentro del Currículo oficial de Imagen y percepción y salud corporal. Pretende que el alumno sepa andar, correr, mantener posturas para distintas situaciones, etc. y todo ello requiere un aprendizaje, a través de prácticas que mejoren las habilidades del tono corporal.MadridES