Learning from non-linear ecosystem dynamics is vital for achieving land degradation neutrality

Land Degradation Neutrality is one of the Sustainable Development Goal targets, requiring on-going degradation to be balanced by restoration and sustainable land management. However, restoration and efforts to prevent degradation have often failed to deliver expected benefits, despite enormous investments. Better acknowledging the close relationships between climate, land management and non-linear ecosystem dynamics can help restoration activities to meet their intended goals, while supporting climate change adaptation and mitigation. This paper is the first to link ecological theory of non-linear ecosystem dynamics to Land Degradation Neutrality offering essential insights into appropriate timings, climate-induced windows of opportunities and risks, and the financial viability of investments. These novel insights are pre-requisites for meaningful operationalisation and monitoring of progress towards Land Degradation Neutrality

The PESERA-DESMICE Modeling Framework for Spatial Assessment of the Physical Impact and Economic Viability of Land Degradation Mitigation Technologies

This paper presents the PESERA-DESMICE integrated model developed in the EU FP6 DESIRE project. PESERA-DESMICE combines a process-based erosion prediction model extended with process descriptions to evaluate the effects of measures to mitigate land degradation, and a spatially-explicit economic evaluation model to evaluate the financial viability of these measures. The model operates on a grid-basis and is capable of addressing degradation problems due to wind and water erosion, grazing, and fire. It can evaluate the effects of improved management strategies such as maintaining soil cover, retention of crop residues, irrigation, water harvesting, terracing, and strip cropping. These management strategies introduce controls to various parameters slowing down degradation processes. The paper first describes how the physical impact of the various management strategies is assessed. It then continues to evaluate the applicability limitations of the various mitigation options, and to inventory the spatial variation in the investment and maintenance costs involved for each of a series of technologies that are deemed relevant in a given study area. The physical effects of the implementation of the management strategies relative to the situation without mitigation are subsequently valuated in monetary terms. The model pays particular attention to the spatial variation in the costs and benefits involved as a function of environmental conditions and distance to markets. All costs and benefits are added to a cash flow and a discount rate is applied. This allows a cost-benefit analysis(CBA) to be performed over a comparative planning period based on the economic lifetime of the technologies being evaluated. It is assumed that land users will only potentially implement technologies if they are financially viable. After this framework has been set-up, various analyses can be made, including the effect of policy options on the potential uptake of mitigation measures and an analysis of where cost-effectiveness is highest. Apart from model description, we present case studies of the use of the framework to illustrate its functioning and relevance for policy-making

Agent-based modelling of agricultural water abstraction in response to climate change and policies: In East Anglia, UK

Freshwater is a vital natural resource for multiple sectors. However, freshwater available for abstraction in the UK and in particular agricultural irrigation in East Anglia is becoming increasingly variable and uncertain due to climate and policy changes, and increase in demand. We present an Agent-Based Model (ABM) that has the capability to capture the complexity of this system as individual abstractors interact, learn and adapt to internal and external changes. The purpose of this model is to understand under which policy and climate change scenarios sustainable water resource management emerges from decisions and interactions of water abstraction licence holders. This poster will present the conceptual model and preliminary results

Applying Bayesian belief networks (BBNs) with stakeholders to explore and codesign options for water resource interventions

Bayesian Belief networks (BBNs) are a useful tool to account for uncertainty and can be used to incorporate stakeholder understandings of how a system works. In this study, BBNs were applied to elicit and discuss local stakeholders’ concerns in conflicts over water resource planning in two cases in southern Thailand. One concerned the construction of a dam proposed by a top-down project. The other concerned a bottom-up participatory process at the catchment scale to assess the need for water resources interventions and explore perceptions on alternative design options. In the top-down project, the responses of participants during the elaboration of the BBN showed that potentially affected stakeholders were particularly concerned about limited consultation and lack of shared benefits, which led them to oppose the dam project. In the bottom-up project, local stakeholders expected and agreed with the benefits of a dam, proposing to locate the dam upstream of community land. The BBN method did not facilitate dialogue in the top-down dam-building project because no alternative design options could be discussed and potentially affected stakeholders did not want to discuss compensation because of mistrust and differences in valuation of effects. In the bottom-up project, the BBN method did facilitate dialogue on alternative intervention options and their effects. The replicable BBN framework can support policy-makers to better understand water conflict situations in different stages of planning. Its application supports exploring a wider repertoire of options, enlarging the scope for more inclusive and sustainable solutions to water resource conflicts

A new dryland development paradigm grounded in empirical analysis of dryland systems science

Global drylands face a host of urgent human and environmental challenges with far-reaching impacts. Improving smallholder agriculture remains a key development pathway to tackle these challenges. The Dryland Development Paradigm (DDP), introduced in 2007, presented a highly influential framework for dryland development based on systems research. This paper empirically derives a new, updated DDP. It assesses recent, cutting-edge dryland science, combining literature review with qualitative and quantitative analysis of research published by the world's largest dryland science and development research initiative. The new DDP comprises eight characteristics that are distilled into three integrative principles: Unpack, Traverse and Share. The new DDP is applied and tested to identify key dryland knowledge and development gaps. A future research agenda is then elucidated, grounded in a research in development approach, in which research anchored in the three integrative principles is embedded within the context it seeks to improve. Supported by greater transdisciplinarity and knowledge co-production, operationalization of the new DDP can deliver both novel scientific insights and development impact in line with the aspirations of the 2030 Sustainable Development Goals

Allying knowledge integration and co-production for knowledge legitimacy and usability: The Amazonian SISA policy and the Kaxinawá Indigenous people case.

Environmental policies that aim to enhance nature conservation, biodiversity, and well-being of Indigenous Peoples and Local Communities (IPLC) rely on knowledge integration and co-production processes that include both science and Indigenous and local knowledge (ILK) systems. While these processes are expected to safeguard the diversity of knowledge systems, uneven power relations among participants often prevent them from achieving this which can affect the legitimacy and usability of the outcomes of these processes. Using a case study in the Acre state (Brazil), where policy practitioners implemented the REDD+policy System of Incentives for Ecosystem Services in the Brazilian Kaxinawá Nova Olinda Indigenous Land, we investigate how participants manage challenges to safeguard knowledge diversity and usability during policy assessment and planning. Our findings show how, despite the use of participatory approaches, knowledge diversity ended up being compromised because policy practitioners were insufficiently attentive to power asymmetries and their implications. This, however, did not negatively affect the usability of the knowledge outcomes. Rather than focusing on the perfection of participatory methods, we call for a practical ethics that relies on culturally and ethically sensitive dialogues and that include continuous reflection. Such reflection will enable adaptation and improvisation to be able to respond to emerging power dynamics in an adequate and timely manner, thereby ensuring both the legitimacy and the usability of the outcomes of knowledge integration and co-production

Making land management more sustainable: experiences implementing a new methodological framework in Botswana

It is increasingly recognised that tackling land degradation through more sustainable land management depends on incorporating multiple perspectives by using a variety of methods at multiple scales, including the perspectives of those who manage and/or use the land. This paper reports experience implementing a previously proposed methodological framework that is designed to facilitate knowledge sharing between researchers and stakeholders about land degradation severity and extent, and sustainable land management options. Empirical findings are presented from the Botswana site of the EU-funded Desertification Mitigation and Remediation of Land project. The paper reflects upon the challenges and benefits of the proposed framework and identifies a number of benefits, notably related to insights arising from the integration of local and scientific knowledge, and the ownership of the sustainable land management strategies that emerged from the process. However, implementing the framework was not without challenges, and levels of poverty and formal education may limit the implementation of the framework in some developing world contexts

Soil Quality - a critical review

Sampling and analysis or visual examination of soil to assess its status and use potential is widely practiced from plot to national scales. However, the choice of relevant soil attributes and interpretation of measurements are not straightforward, because of the complexity and site-specificity of soils, legacy effects of previous land use, and trade-offs between ecosystem services. Here we review soil quality and related concepts, in terms of definition, assessment approaches, and indicator selection and interpretation. We identify the most frequently used soil quality indicators under agricultural land use. We find that explicit evaluation of soil quality with respect to specific soil threats, soil functions and ecosystem services has rarely been implemented, and few approaches provide clear interpretation schemes of measured indicator values. This limits their adoption by land managers as well as policy. We also consider novel indicators that address currently neglected though important soil properties and processes, and we list the crucial steps in the development of a soil quality assessment procedure that is scientifically sound and supports management and policy decisions that account for the multi-functionality of soil. This requires the involvement of the pertinent actors, stakeholders and end-users to a much larger degree than practiced to date

An exploration of scenarios to support sustainable land management using integrated environmental socio-economic models

Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the PESERA–DESMICE modeling framework with various scenarios for 13 global land degradation hotspots. Starting with an initial assessment representing land degradation and productivity under current conditions, options to combat instances of land degradation are explored by determining: (1) Which technologies are most biophysically appropriate and most financially viable in which locations; we term these the “technology scenarios”; (2) how policy instruments such as subsidies influence upfront investment requirements and financial viability and how they lead to reduced levels of land degradation; we term these the “policy scenarios”; and (3) how technology adoption affects development issues such as food production and livelihoods; we term these the “global scenarios”. Technology scenarios help choose the best technology for a given area in biophysical and financial terms, thereby outlining where policy support may be needed to promote adoption; policy scenarios assess whether a policy alternative leads to a greater extent of technology adoption; while global scenarios demonstrate how implementing technologies may serve wider sustainable development goals. Scenarios are applied to assess spatial variation within study sites as well as to compare across different sites. Our results show significant scope to combat land degradation and raise agricultural productivity at moderate cost. We conclude that scenario assessment can provide informative input to multi-level land management decision-making processes