Salience, credibility and legitimacy in land use change modeling : model validation as product or process?

Sustainable resource management requires balancing trade-offs between land productivity and environmental integrity while maintaining equality in resource access. Scenario analysis based on a credible simulation model can help to efficiently assess the dynamic and complex interactions in between components and their trade-offs. However, despite the potential of simulation models as decision support tools, acceptance and use by decision makers and natural resource managers are still major challenges, particularly in developing countries. This study was carried out to address issues related to validation of simulation models that includes users perspectives on validity of simulation models, scenario-based trade-offs analysis and uncertainty assessment for designing management intervention. Firstly, the current study analyzed users perspectives on validity of a simulation model for natural resource management based on two activities. The first activity is based on surveys in four countries (Indonesia, Kenya, Philippines and Vietnam). It explored the perceptions and expectations of potential model users (researchers, lecturers, natural resource managers, policy makers, communicators) on a hypothetical model. The second activity was a participatory model evaluation in Aceh, Indonesia involving use of the spatially explicit FALLOW model and evaluation of its outputs. When assessing a hypothetical model, potential model users considered salience (relevance) as the most important attribute in a simulation model followed by credibility. Once a model was used, the ability of the model results to depict reality on the ground (credibility) became a critical and most important aspect for users. Nevertheless, even in cases where model performance was poor, users considered the scenario approach in evaluating their landscape a novelty. Potential model users profession, prior exposure to a simulation model and interest in using models did not significantly influence respondents ranking of model attributes (salience, credibility, legitimacy). In the second study, to improve salience of a FALLOW model application, a livestock module was developed and tested for a peri-urban situation in the Upper Konto catchment, East Java, Indonesia. This study aimed to explore the impact of land use zoning strategies on farmers welfare, fodder availability and landscape carbon stocks. Scenario analysis revealed that the current land zoning policy of establishing protected areas and allowing farmers access to fodder extraction in part of the protected areas is the most promising strategy in balancing the trade-offs of production (farmers welfare) and environment (represented by above-ground carbon sequestration). Compared to the scenario reflecting current policy, the open-access scenario that allows opening land in protected areas, was simulated to increase farmers welfare by 13% at the expense of losing 23% of landscape carbon. The extended FALLOW model with its livestock module proved an effective tool to examine the interactions between livestock, cropping systems, household decision and natural resources in data poor environments. The FALLOW model was able to simulate the land cover spatial pattern in the catchment (2002-2005) with a goodness of fit of 81% while the ability of predicting land change was 34.5% at a pixel resolution of 1 ha. In the third study, to understand the effect of uncertainty in input parameters influencing model outcome, an uncertainty analysis of landscape C stock and emissions was carried out using several approaches that can cater for different situations of data availability (plot level carbon stocks and land cover maps). The analysis used data collected during a study assessing opportunities for REDD+ (Reducing Emission from Deforestation and Degradation) in a forest frontier region in Jambi, Indonesia, during 2000-2009. In a minimum data set situation (only single plot carbon estimates and a single land cover map available) the average landscape C stock estimates were 114.5 Mg.ha-1 and 81.0 Mg.ha-1 for 2000 and 2009, respectively. Based on an expected-carbon-deviance curve, the confidence levels that the landscape C estimates were correct were 70% and 63% for 2000 and 2009, respectively. For other cases of enhanced data availability, Monte Carlo simulations were carried out to evaluate the propagation of land use classification errors and plot-level carbon stocks variation, jointly influencing landscape C stock and emission estimates. Results showed that excluding errors in land use classification resulted in biased estimates of landscape C stock and emissions. However, the bias over the whole area was estimated to be less than 7.5% (or 2.8 Mg.ha-1) with a coefficient variation of less than 0.2%. In the last study, we combined spatial aggregation analysis on the error-perturbed C emission maps (resulting from Monte Carlo analysis in the third study) with local stakeholders perspectives to develop an effective REDD+ scheme at the district level. The uncertainty analysis formed the basis for determining an appropriate scale for monitoring carbon emission estimates as performance measures of a REDD+ scheme. Changes in spatial resolution of C emission maps influenced the magnitude of potential area eligible for carbon payment and the uncertainty in carbon emission estimates. At 100 m resolution, 34.8% of the area would be eligible for REDD+ with an uncertainty of 82%while at 5000 m resolution only 6.5% of the area would be eligible with a 1% error. At 1 km2 pixel size (1000 m resolution), the errors dropped below 5%, retaining most of the coarser spatial variation in the district. Hence, feasible measures for emission reduction in the district, derived from a participatory planning process, are compatible with the 1000 m spatial resolution of the C emission map. Overall, the research elucidates the importance of involving model users in evaluating a simulation model, including scenario development and subsequent results analysis and interpretation. The study also indicates the importance of making efforts to improve model output accuracy to gain users acceptance as users consider spatial accuracy is an important aspect of landscape-based models. In data-scarce situations, model users considered model robustness in responding to new situations to be more important than precision. Scenario analysis proved to be an effective tool to examine interactions in a complex landscape, including their consequences for trade-offs (e.g. farmers welfare versus landscape carbon stocks) and synergies (e.g. fodder availability and farmers welfare). Analysis of uncertainty of landscape C emission during land use changes can provide guidance in developing appropriate natural resource management interventions. Although model users may perceive model validation as a product, it is in fact a process.Nachhaltiges Ressourcenmanagement erfordert eine Balance der Austauschbeziehungen (trade-offs) zwischen Landproduktivität und ökologischer Integrität, sowie der Aufrechterhaltung eines gleichberechtigten Ressourcenzugangs. Szenarienanalyse basierend auf glaubwürdigen Modelsimulationen kann dabei die dynamischen und komplexen Interaktionen zwischen beteiligten Komponenten und deren Austauschbeziehungen unterstützen. Ungeachtet des Potentials von Simulationsmodellen als unterstützendes Mittel im Entscheidungsprozess des Landmanagements, stellen Akzeptanz und Verwendung von Entscheidungsträgern und Naturschutzmanagern eine noch immer große Herausforderung, vorallem im Kontext der Entwicklungsländer, dar. Diese Studie wurde erstellt, um relevante Aspekte im Bezug der Validierug von Simulationsmodellen aus Sichtweise der Nutzer-Perspektive sowie der Anwendung von Simulationsmodellen zur Bewertung von Austauschbeziehungen und deren Unsicherheitsabschätzungen zur Erstellung von Managementinterventionen zu ergründen. Zunächst wurde in der vorliegenden Studie die Validität von Simulationsmodellen aus Sichtweise der Modelnutzer basiered auf zwei unterschiedlichen Aktivitäten des Naturschutzmanagements untersucht. In der ersten Aktivität wurde dabei die Wahrnehmung und Erwartungshaltung von potentiellen Modelnutzern (Wissenschaftlern, Dozenten, Naturschutzmanagern, Entscheidungsträgern und Kommunikatoren) aus Indonesien, Kenia, Philippinen und Vietnam mit Hilfe von Fragebögen betrachtet. Die zweite Aktivität beinhaltete eine partizipative Validierung von Modelergebnissen generiert mit dem räumlich-expliziten FALLOW Model in Aceh, Indonesien. Die Ergebnisse ergaben, das potentielle Modelnutzer Relevanz als das wichtigste Attribut vor Glaubwürdigkeit als Grundlage zur Bewertung eines hypothetischen Models verwendeten. Nachdem ein Model bereits eingesetzt wurde, waren Glaubwürdigkeit der Modelergebnisse im Vergleich der Realtität vor-Ort als ein kritisches und zugleich als das wichtigste Nutzerkriterium angesehen. Auch in Fällen schlechter Simulatiosnergebnisse wurde von den Modelnutzern der Szenarienansatz zur Bewertung Ihrer Landschaft als Novum angesehen. Der potentielle Modeliererhintergrund, eine vorherige Erfahrung mit Simulatiosnmodellen und das Interesse zur Verwendung von Simulationsmodellen beeinflußten die genannte Rangfolge der Modelattibute (Relevanz, Glaubwürdigkeit, Legitimiät) der befragten Personen dabei nicht signifikant. In der zweiten Studie wurde zur Verbesserung der Relevanz einer FALLOW Modelanwendung ein Modul zur Viehbestandsbewertung entwickelt und anhand eines peri-urbanen Fallbeispiels im Upper Konto Wassereinzugsgebiet, Ost-Java, Indonesien getestet. Die Studie untersuchte dabei den Einfluss von Landnutzungszonenstrategien auf die Wohlstandssituation von Bauern, Futtermittelverfügbarkeit, und der Kohlenstoffbestände auf Landschaftsebene. Eine Szenarienanalyse machte deutlich, das die gegenwärtigen Richlinien zur Landzonierung zur Etablierung von Schutzgebieten und die erlaubte Nutzung von Futtermittelextraktion aus Teilen der Schutzgebiete die bestgeeigneteste Strategie ist, um ein ausgeglichene Bilanz der Austauschbeziehungen von Produktion (Wohlstand der Bauern) und Umwelt (Kohlenstoffsequestrierung) zu erreichen. Im Vergleich zur bestehenden Richtlinie hatte das Open-access Szenario, das eine vollständige Nutzung der Schutzgebiete erlauben würde, eine simulierte Wohlstandsteigerung der Bauern von 13% zur Folge, im Gegenzug dazu müße mit einem Verlust von 23% der Kohlenstoffbestände auf Landschaftsebene gerechnet werden. Das erweiterte FALLOW Model mit dem Tierbestandmodul bewies das es als effektives Werkzeug, zur Bewertung der Interaktionen zwischen Viehbestand, Anbausystemen, Haushaltsentscheidungen und Naturschutzmanagement, in einer datenarmen Umgebung einsetzbar ist. Das FALLOW Model war in der Lage, die räumlichen Landbedeckungsgrade im Wassereinzugsgebiet mit einer Genauigkeit (Goodness-of-fit) von 81% und einer Ladnutzungsänderung von 34,5% auf der Pixelebene von 1 ha im Zeitraum von 2002-2005 vorherzusagen. In der dritten Studie wurden die Effekte untersucht, die durch die Unsicherheit von Eingabeparamtern auf Seiten der Modelergebnisse entstehen können. Unter Zuhilfenahme einer Unsicherheitsanalyse von Kohlenstoffbeständen und Emissionen auf Landschaftsebene wurden dabei verschiedene Situationen der Datenverfügbarkeit (Schlagspezifische Kohlenstoffbestände, Landbedeckungskarten) untersucht. Die Analyse verwendete Daten die während einer Studie zur Abschätzung der REDD+ (Reducing Emission from Deforestation and Degradation) Verwendungsmöglichkeiten in einer Waldgrenzregion in Jambi, Indonesien während der Jahre 2000 bis 2009 erhoben wurden. In einer Minimumdatensatzsituation (nur schlagspezifische Datensätze, und einzelne Landbedeckungskarte verfügbar) wurde der Durchschnittskohlenstoffbestand auf Landschaftsebene auf 114,5 Mg ha-1 in 2000 und 81,0 Mg ha-1 für 2009 geschätzt. Basierend einer zu erwartenden Kohlenstoff-Abweichungs Kurve, wurde der Vertrauensgrad der Kohlenstoffschätzung auf Landschaftsebene im Jahr 2000 mit 70% und in 2009 auf 63% beziffert. Für Fälle mit erweiterterter Datenverfügbarkeit wurde ein Monte-Carlo Simulation ausgeführt, um die Fehlerfortpflanzung bedingt durch Landnutzungsklassifizierung und Variation der schlagspezifischen Kohlenstoffbestände auf den Einfluss der Kohlenstoffbestände auf Landschaftsebene und deren Emission gemeinsam zu untersuchen. Die Ergebnisse zeigten, das ein Fehlerauschluss innerhalb der Landnutzungsklassifizierungen, sowie die Variationen der schlagspezifischen Kohlenstoffbestände einen systematischen Fehler in den Abschätzungen des Kohlenstoffbestandes und der Emission auf Landschaftsebene erzeugten. Allerdings betrug der Fehler im Landschaftskontext weniger als 7,5% (oder 2,8 Mg ha-1) mit einem Varianzskoeffiezient von weniger als 0,2%. In der letzten Studie wurde eine räumliche Aggregierungsanalyse der fehlerbehafteten Kohlenstoddemissionskarten (basierend auf den Monte-Carlo Simulationen) dazu verwendet, eine räumlich-skalierte Abhängigkei, der Durschnitts- und Varianzabschätzungen der Kohlenstoffemissionen auf Schlagebene aufzeigen. Die Skalenabhängigkeit beinflusste das Ausmaß des potentiellen Gebietes für Kohlenstoffausgleichzahlungen und daher die Gerechtigkeit im Kontext des Ausgleichszahlungplans. Auf Schlagebenengröße von 1 ha (Einheitsgröße Kohlenstoffzahlungen), wären 34,8 % des Untersuchungsgebietes für einen REDD+ Plan geeignet, während bei einer 2500 ha großen Schlaggröße nur 6,5 % geeignet wären. Das Entwurf eines leistungsbasierten Zahlungsschemas sollte diese Skalenabhängigkeit berücksichtigen. Im Gesamtüberblick konnte die vorgelegte Dissertation die Bedeutung der mit einzubeziehenden Modelnutzer zur Evaluierung eines Simulationsmodels, der Ergebnis- und Szenarienanalyse aufzeigen. Die Studie konnte ebenso deutlich machen, das die Steigerung der Genauigkeit von Modelergebnissen im Bezug von Landschaftsmodelle vorallem der räumlichen Genauigkeit, zu einer höheren Modelnutzerakzeptanz führt. In datenarmen Situationen zeigte sich, das Modelnutzern die Robustheit eines Models sich an eine neue Situation anzupasen wichtiger erscheint als Genauigkeit. Szenarienanalyse erwiess sich als ein effektives Werkzeug, um Interaktionen in einer komplexen Landschaft, inklusive deren Konsequenzen (z.B. Wohlstand der Bauern im Vergleich von Kohlenstoffbeständen auf Landschaftsebene) und deren Synergien (z.B. Futtermittelverfügbarkeit im Vergleich zum Wohlstand der Bauern) untersuchen zu können. Die Analyse von Unsicherheiten von Kohlenstoffemission auf Landschaftsebene im Verlauf eines Landnutzungswandels bietet eine Orientierung zur Entwicklung von angemessenen Interventionen im Naturschutzmanagement. Auch wenn Anwender Modelvalidität als ein Produkt wahrnehmen ist es in Wirklichkeit ein Prozess

SANDALWOOD AS A COMPONENT OF AGROFORESTRY: EXPLORATION OF PARASITISM AND COMPETITION WITH THE WANULCAS MODEL

Sandalwood is an important component of agroforestry systems in the drier Eastern parts of Indonesia, although its value to farmers is still limited by existing policies and regulation of marketing. As a relatively slow growing root parasite, sandalwood will interact with other components in a complex pattern of competition and host-parasite relationships, depending on root distribution and rooting depth of potential hosts. We describe a number of modifications to the generic tree-soil-crop simulation model WaNuLCAS, that allow exploration of the transition between parasitism and competition. The key variable in this transition is the effectiveness of formation of the parasitic link for all situations where roots of the host and parasite occur in the same volume of soil. At low values of this effectiveness competition dominates, at higher values sandalwood will weaken the host, until it effectively kills it, leading to an optimum response of sandalwood to the effectiveness parameter. Unresolved questions in the formulation of the model are the lifespan of parasitized roots and the question whether or not sandalwood will allocate energy resources for maintenance respiration of host roots after the formation of haustoria. The'desk study' reported here was intended to focus subsequent field studies on these unresolved issues

Sandalwood as a Component of Agroforestry: Exploration of Parasitism and Competition with the Wanulcas Model

Sandalwood is an important component of agroforestry systems in the drier Eastern parts of Indonesia, although its value to farmers is still limited by existing policies and regulation of marketing. As a relatively slow growing root parasite, sandalwood will interact with other components in a complex pattern of competition and host-parasite relationships, depending on root distribution and rooting depth of potential hosts. We describe a number of modifications to the generic tree-soil-crop simulation model WaNuLCAS, that allow exploration of the transition between parasitism and competition. The key variable in this transition is the effectiveness of formation of the parasitic link for all situations where roots of the host and parasite occur in the same volume of soil. At low values of this effectiveness competition dominates, at higher values sandalwood will weaken the host, until it effectively kills it, leading to an optimum response of sandalwood to the effectiveness parameter. Unresolved questions in the formulation of the model are the lifespan of parasitized roots and the question whether or not sandalwood will allocate energy resources for maintenance respiration of host roots after the formation of haustoria. The'desk study' reported here was intended to focus subsequent field studies on these unresolved issues

Designing a procurement auction for reducing sedimentation: a field experiment in Indonesia

The setting is a watershed area in Lampung, Indonesia where soil erosion has broad implications for environmental damage. The strategy to engage farmers in an environmental protection initiative is through the Payment for Environmental Services (PES) scheme. In situations where most of the procurement auction participants have low education, low asset endowment, small plot size and little market-based competitiveness, findings show the process outlined in this study is able to include farmers in the conservation programme. Introducing the “procurement auction” as a market-based approach to rural communities does not appear to hamper social relationships and is applicable in a rural setting

From recreational to income-generating opportunities: assessment of public preferences for non-wood forest products in the Czech Republic

With the alarming increase in dying trees and massive logging in the Czech forests due to bark beetle infestation, the collection of non-wood forest products, a beneficial recreational activity in the Czech Republic, is now being promoted as an alternative to wood provisioning services. This paper aims to present findings on the non-wood forest product preferences in the country as part of a baseline assessment for promoting the usage. This study relied on the 2019 national survey data of public preferences in collecting forest berries, mushrooms, honey, and medicinal herbs. K-means cluster analysis was employed to classify the respondents. A binary logistic regression with a conditional forward approach was employed to identify the potential predictors of the high preference for each non-wood forest product. Data from 1,050 online respondents were included, and two groups of respondents were clustered based on their preferences for the entire non-wood forest, i.e., higher and lower utilization. The regression analysis revealed that frequent forest visitors were the primary predictor of high utilization of all non-wood forest products (between 1.437 to 4.579 odd ratios), in addition to age, gender, and location of the forest property. By clustering the respondents based on the high and low preferences in utilizing non-wood forest products, the promotion of this service, from recreational to potential livelihood activities and economic benefits, can be better targeted, e.g., target customer, infrastructure development in the location with high preferences, scenarios based on the type of owners (municipal or private forest owners), which in accordance to the national forest policy and laws, and, at the same time, maintain the ecological stability

Hi-sAFe: a 3D agroforestry model for integrating dynamic tree–crop interactions

Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree–crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree–tree and tree–crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model’s 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice

Flood risk reduction and flow buffering as ecosystem services - Part 2 : Land use and rainfall intensity effects in Southeast Asia

Watersheds buffer the temporal pattern of river flow relative to the temporal pattern of rainfall. This "ecosystem service" is inherent to geology and climate, but buffering also responds to human use and misuse of the landscape. Buffering can be part of management feedback loops if salient, credible and legitimate indicators are used. The flow persistence parameter Fp in a parsimonious recursive model of river flow (Part 1, van Noordwijk et al., 2017) couples the transmission of extreme rainfall events (1-Fp), to the annual base-flow fraction of a watershed (Fp). Here we compare Fp estimates from four meso-scale watersheds in Indonesia (Cidanau, Way Besai and Bialo) and Thailand (Mae Chaem), with varying climate, geology and land cover history, at a decadal timescale. The likely response in each of these four to variation in rainfall properties (including the maximum hourly rainfall intensity) and land cover (comparing scenarios with either more or less forest and tree cover than the current situation) was explored through a basic daily water-balance model, GenRiver. This model was calibrated for each site on existing data, before being used for alternative land cover and rainfall parameter settings. In both data and model runs, the wet-season (3-monthly) Fp values were consistently lower than dry-season values for all four sites. Across the four catchments Fp values decreased with increasing annual rainfall, but specific aspects of watersheds, such as the riparian swamp (peat soils) in Cidanau reduced effects of land use change in the upper watershed. Increasing the mean rainfall intensity (at constant monthly totals for rainfall) around the values considered typical for each landscape was predicted to cause a decrease in Fp values by between 0.047 (Bialo) and 0.261 (Mae Chaem). Sensitivity of Fp to changes in land use change plus changes in rainfall intensity depends on other characteristics of the watersheds, and generalisations made on the basis of one or two case studies may not hold, even within the same climatic zone. A wet-season Fp value above 0.7 was achievable in forest-agroforestry mosaic case studies. Inter-annual variability in Fp is large relative to effects of land cover change. Multiple (5-10) years of paired-plot data would generally be needed to reject nochange null hypotheses on the effects of land use change (degradation and restoration). Fp trends over time serve as a holistic scale-dependent performance indicator of degrading/ recovering watershed health and can be tested for acceptability and acceptance in a wider social-ecological context

Wanulcas 2.0 : Background on a model of water, nutrient ang light capture in agroforestry system/ Noordwijk

vi, 186 hal: ill, tab ; 21 cm

Wanulcas 2.0 : Background on a model of water, nutrient ang light capture in agroforestry system/ Noordwijk

vi, p. 186: ill.; 21 c

Flood risk reduction and flow buffering as ecosystem services - Part 1 : Theory on flow persistence, flashiness and base flow

Flood damage reflects insufficient adaptation of human presence and activity to location and variability of river flow in a given climate. Flood risk increases when landscapes degrade, counteracted or aggravated by engineering solutions. Efforts to maintain and restore buffering as an ecosystem function may help adaptation to climate change, but this require quantification of effectiveness in their specific social-ecological context. However, the specific role of forests, trees, soil and drainage pathways in flow buffering, given geology, land form and climate, remains controversial. When complementing the scarce heavily instrumented catchments with reliable long-term data, especially in the tropics, there is a need for metrics for data-sparse conditions. We present and discuss a flow persistence metric that relates transmission to river flow of peak rainfall events to the base-flow component of the water balance. The dimensionless flow persistence parameter Fp is defined in a recursive flow model and can be estimated from limited time series of observed daily flow, without requiring knowledge of spatially distributed rainfall upstream. The Fp metric (or its change over time from what appears to be the local norm) matches local knowledge concepts. Inter-annual variation in the Fp metric in sample watersheds correlates with variation in the "flashiness index" used in existing watershed health monitoring programmes, but the relationship between these metrics varies with context. Inter-annual variation in Fp also correlates with common base-flow indicators, but again in a way that varies between watersheds. Further exploration of the responsiveness of Fp in watersheds with different characteristics to the interaction of land cover and the specific realisation of space-time patterns of rainfall in a limited observation period is needed to evaluate interpretation of Fp as an indicator of anthropogenic changes in watershed conditions