Transnational Approaches to Forestry Management and Forest Risk Strategies”

“Transnational approaches to forestry management and forest risk strategies”

State-of-the-art-report of the project-team M (Dr. Ir. Luc Boerboom, International Institute for Geo-Information Science and Earth Observation, The Netherlands)

02.09.2008 Koblenz, Germany, Rhein-Mosel-Halle 17:35 - 18:00

INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ITC International Institute for Geo-information Science and Earth Observation

Enschede The Netherlands www.itc.nl Mission

Provide international education through knowledge exchange Capacity building Institutional development For and in economically and technologically less developed countries & Research and advisory services ITC’s organisation chart

Supervisory 2010: Faculty in University Twente Board

Scientific Employees Directorate Council Council

Bureau Research Bureau Education Bureau Marketing and Coordination Affairs Project Services

Scientific departments Support departments Earth Observation Science (EOS) Communication

Geo-information Processing (GIP) Personnel Affairs and Organisation

Urban and Regional Planning Financial and Economic Affairs and Geo-Information Management (PGM)

Natural Resources (NRS) Information Technology

Water Resources (WRS) Facility Management

Earth Systems Analysis (ESA) Geochemical, Water and Soil Laboratory What’s ITC all about? 58 years of “Space here, space out there”

Staff staff core activities: 140 fte support staff core activities: 45 fte general support staff: 55 fte 28 nationalities Students 600 p/year PhD researchers 110 Alumni 16,000 mid-career professionals 160 countries Adaptation

Courtesy: Sibout Nooteboom Courtesy: Sibout Nooteboom Content

Forest Adaptation 2008 Leveling of basic concepts Decisions, decision making Examples of DSS Critical understanding for Forestclim to get a.o. through decision makers Follow the decision makers and differentiate contexts Integrate scales and levels Relate to variable potentials and constraints in the forestry sector (and others?) Integrate with regular forest management and mitigation Develop from existing models Integrated modeling through management models Resolve level dilemma of adaptive (co-?) management vs forest adaptation Address uncertainty from decision maker’s perspective: avoiding the wrong decision more than making the right decision? Use and develop latest technology to cross scales and levels Forest Adaptation 2008 conference Forest adaptation options Some technical options for adaptive management of forests Phase Measure Regeneration Adjust silvicultural system and/or regeneration technique Prefer mixed stands Match species and provenance to present and future site and climate Consider proven introduced species Adapt natural regeneration to changing reproduction and competition patterns Rehabilitate degraded and eliminate off-site stands Consider nurse trees Consider artificial shading in planting dry, exposed sites Adjust planting densities Monitor competing vegetation Add nutrients likely to become deficient Under-plant high risk stands Treat for wind resistance starting systematically from establishment Reduce excessive game, rodent populations Tending of Adjust intensity and frequency of pre-commercial thinnings and stocking control stands Adjust stand structure and composition Phase out off-site stands Enhance monitoring for pathogens and insects Schöne, D. (2008). Adapting forests and forestry to Climate Change: A challenge to change paradigm. A background paper for the international Conference on Adaptation of Forests and Forest Management to Changing Climate with Emphasis on Forest Health. Forest Adaptation 2008. Umea, Sweden: 1-12. Some technical options for adaptive management of forests Phase Measure Harvesting Avoid large clearcuts, edge effects fragmentation Adjust harvest method and equipment, reduce impact of skidding Consider converting to uneven-aged stands Protecting Intensify monitoring of risk and damage forests Eliminate added stresses (acid rain, game) Adjust fire management, develop fire-smart landscapes Protect rare habitats and species, genetic stocks Management, Raise awareness and information of top and field staff. owners planning and Educate extension foresters administration Rewrite silvicultural and management guidelines Intensify or update site classification and mapping Provide adequate human resources; management and labour intensity likely to increase Plan and train for calamities and timber salvage, sales pools ?? Integrate climate change into management plans ? Reconsider rotations and allowable cut OW Reconsider species choice and introduced species H Update yield tables Carry out professional national and local vulnerability analysis Prioritize no-regret options

Practice adaptive forest managementSchöne, D. (2008). Adapting forests and forestry to Climate Change: A Monitor for climate change impchallengeacts in protected to change areas paradigm. A background paper' for the international Conference on Adaptation of Forests and Forest Management to Changing Climate with Emphasis on Forest Health. Forest Adaptation 2008. Umea, Sweden: 1-12. Spatial and Temporal Change in Fire Risk III

Current Risk 2080s Risk 2 parameter risk model – model of survival probability

1,0

0,9

0,8 p(t) = survival prob. at age t 1− p p = survival prob. at age 100 0,7 100 b 100 tp 1)( −= b ⋅t b = form parameter 100 0,6 Spruce 0,5 Pine surviving probability surviving Parameter for Spruce: Beech 0,4 Oak p100 = 0,7 (70%); b = 2 0,3

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 1 1 1 1 1 1 1 1 1 2 age [years]

(based on data by Knoke et al., 2008)

Staupendahl and Benrhard, 2008 British Columbia: Coast Mountains

Elevation Shift of Subalpine Forests Climate Envelope

Mbogga M. and Hamann A. What Influences Results of Bioclimate Envelope Models? A sensitivity analysis for five sources of uncertainty. Presentation at For14est Adaptation 2008 conference, Umea, Sweden Observations Forest Adaptation conference Umea, Sweden, Aug. 25-28

Most interesting was a discussion in special session on "Scenarios and modeling for forest management planning“:

Vulnerability assessment and uncertainty receive special attention. Adaptation strategies less

From discussion: Most if not all systems detached from real planning and decision processes. Poor understanding of who are decision makers, what is a decision, a decision problem, policy making process, a decision process, and the implications for decision support. Need to be closer. No understanding about how decision makers see and consider uncertainty and how they communicate uncertainty, nor how uncertainty can be communicated with them.

Personal observation: Everything is decision support None look at conflicts, nor have good evaluation tools, more for plan development, but again not normatively. Preconceived notion that optimization methods can not handle stochasticity and dynamics, whereas they can. No consideration of uncertainty in the normative models decision makers carry around in their heads, but only on the biophysical uncertainties. Content

"What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it."

Herbert A. Simon, Designing Organizations for an Information-Rich World, in: Computers, Communications and the Public Interest, pages 40-41, Martin Greenberger, ed., The Johns Hopkins Press, 1971 The basis of evaluation: What is a “Decision Problem”? (Ackoff, 1981, The art and science of mess management, Interfaces 11(1) pp. 20-26)

Decision problem is defined as a situation where an individual or a group perceives a difference between a present state and a desired state and where: The individual or group has alternative course of actions available The choice of action can have a significant effect on this perceived difference The individual or group is uncertain a priori as to which alternative should be selected Semantic confusion about scenarios

Scenarios

Scenarios Alternatives Exogenous Endogenous variables variables

It is about control, which varies between decision makers Definitions of both sets can be found

SET 1 SET 2 Scenarios are archetypal Scenarios focus on the analysis descriptions of alternative of uncertainties, drivers of images of the future, created change and causal relationships from mental maps or models associated with a potential that reflect different decision. Wollenberg, E. et al., 2000. Using scenarios to perspectives on past, present make decisions about the future: anticipatory and future developments. learning for the adaptive co-management of Greeuw S.C.H. et al. 2000 Crystal clear balls: An community forests. Landscape and Urban assessment of recent European and global Planning 47 (2000) 65-77 scenario studies and models. European Environment Agency Scenarios are focused The robustness of the chosen descriptions of fundamentally policy measures can be tested different futures presented in by imposing effects on the coherent script-like or - system that in the real world are narrative fashion. beyond his control. These Schoemaker P.J.H., 1993. Multiple Scenario effects are called scenarios. Development: Its Conceptual and Behavioral Engelen, 2000. The wadbos policy support Foundation. Strategic Management Journal, Vol. system: information technology 14, No. 3. (Mar., 1993), pp. 193-213. to bridge knowledge and choice. Research Institute for Knowledge Systems bv. Policies operate under uncertain conditions

Engelen, 2000. The wadbos policy support system: information technology to bridge knowledge and choice. Research Institute for Knowledge Systems bv. Types of scenarios

Causality

Predictions Explorations

Projections Speculations

Ittersum van, M. K., R. Rabbinge, et al. (1998). "Exploratory Uncertainty land use studies and their role in strategic policy making." Agricultural Systems 58(3): 309-330. Decision Support Systems (DSS)

Class of computer systems that help manager/ Decision Maker in the process of decision making, where: decision/choice problem exists human judgment (value judgment) is an important contributor to the decision making process human information processing capacity limits the decision making process

(adapted from Rauscher et al., 1995) Team M: “Integrated assessment” relating policy to practice!

Sluijs, J. P. v. d. (2002). Integrated Assessment. Responding to global environmental change. M. K. Tolba. Chichester, John Wiley & Sons, Ltd. 4: 250–253. How we like to make decisions

Describe system

Understand system behavior Intelligence (Process model) Assess current situation

Formulate objectives

Design Planning & solutions Formulate model Decision-Making (planning

Process model) Generate alternatives Evidence

Assess impacts Decision/choice (evaluation Evaluate and decide model)

Explain & communicate results How should we see role of the information coming out of this project?

(Davoudi, 2006) How we make policy decisions

Kingdon (1984) Policy streams idea Advocacy coalition approach (Sabatier, 1991)

Hofferbert (1974) Funnel of causality

Ostrom (1986) Institutional rational Choice

Paul A. Sabatier, 1991. PS: Political Science and Politics, Vol. 24, No. 2. (Jun., 1991), pp. 147-156. Policy networks

Many actors involved in decision making Because of interest Because of resource needed Policy Network Theory (Kickert, W. J. M., E. Klijn, et al., Eds. (1997). Managing complex networks: Strategies for the public sector. London, Sage.) Sees policy as being formed in interactions between actors with their own perceptions and strategies Neither bureaucracy nor markets provide ultimate solutions for governance in modern societies

Edelenbos, J. and E. Klijn (2006). "Managing stakeholder involvement in decision making: A comparative analysis of six interactive processes in the Netherlands." Journal of Public Administration Research and Theory 16(3): 417-446 The Paradox of Policy Analysis

Invest tremendous resources (in USA – congress!) yet all signs: not used.

Policy analysis as a tool for the choosing Policy analysis as a tool for the democratic process.

It’s value lies in its contribution to the understandings that citizens have of issues and the political process ????

Shulock, Nancy, 1999, The Paradox of Policy Analysis: If It Is Not Used, Why Do We Produce So Much of It? Journal of Policy Analysis and Management, Vol. 18, No. 2. (Spring, 1999), pp. 226-244. Content

CONCEPTUAL RAIL ALIGNMENT OF BRANCHES N WITH RADIAL OPTION YEAR 2020

Ki lome ters Simpang S. Choh 20246 #Y

LEGEN D #Y Rawang

Branches with Radial Option Existing Railway Gombak Existing Road District Boundary #Y Town Kuang #Y Selayang Baharu #Y Gombak Sri Utara #Y #Y

S. Buloh #Y Kuala #Y #Y #Y Lumpur Wangsa Maju Bukit Subang Manjalara #Y Sri Hartamas Kg Datuk Keramat Kuala Lumpur #Y #Y Damansara #Y #Y Ampang Taman Maluri Mer u Petali ng #Y #Y Kapar #Y #Y Pandan Indah #Y Bandar #Y Bangsar Tun Razak

#Y Batu 14 #Y #Y Salak Petaling Jaya Selatan Hulu Langat Taman Segar #Y Bukit Indah #Y #Y #Y Batu Sembilan Kelang #Y Subang Jaya Shah Alam Bukit Jalil #Y Hulu Langat Klang #Y #Y Cheras Seri Kembangan #Y Puchong Batu #Y Dua Belas

Pelabuhan Klang #Y Kajang #Y

Semenyih CONCEPTUAL RAIL ALIGNMENT #Y N P U T R A J A Y A OF RADIAL OPTION YEAR 2020 #Y #Y Broga Bandar Baru Bangi Kilometers Simpang S. Choh 20246 #Y

LE GEN D #Y Rawang Radial Option Exist in g R ai lwa y Gombak Exist in g R oad District Boundary #Y Town Kuang #Y Selayang Baharu #Y Gombak Sri Utara #Y #Y

Manjalara S. Buloh Wangsa Maju #Y Kuala #Y #Y #Y Lumpur Bukit Subang

#Y Sri Hartamas Kg Datuk #Y Keramat Kuala Lumpur #Y Damansara #Y #Y Ampang Taman Maluri Mer u Petali ng #Y #Y Kapar #Y #Y Pandan Indah #Y Bandar #Y Bangsar Tun Razak

#Y Batu 14 #Y #Y Salak Hulu Langat Petaling Jaya Selatan Taman Segar #Y Bukit Indah #Y #Y #Y Batu Sembilan Kelang #Y Subang Jaya CONCEPTUAL RAIL ALIGNMENT Shah Alam Bukit Jalil #Y Hulu Langat N Klang OF LOOP OPTION YEAR 2020 #Y #Y Cheras Seri Ki lome ters Kembangan #Y Puchong Batu #Y Simpang Dua Belas 20246 S. Choh #Y Pelabuhan Klang #Y Kajang Rawang #Y LEGEN D #Y

Loop Option Gombak Existing Railway Existing Road Semenyih #Y District Boundary P U T R A J A Y A #Y Town Kuang Selayang #Y #Y Broga #Y Baharu Bandar Baru Bangi #Y #Y #Y Gom bak Sri Utara

S. Buloh #Y Kuala Wangsa Maju #Y #Y #Y Lumpur Buki t Subang Manjalar a #Y Sri Hartamas Kg Datuk Keramat Kuala Lumpur #Y #Y

Damansara Ampang #Y #Y Taman Maluri Meru Pet aling #Y Kapar #Y #Y #Y Pandan #Y #Y Indah Bangsar Bandar Tu n Raza k Batu 14 Hulu Langat #Y #Y #Y Salak Petaling Jaya Selatan

#Y Buki t Indah #Y Taman Segar Shah Alam #Y #Y Batu Sembilan Kelang #Y Subang Jaya Bukit Jalil Klang #Y Hulu Langat #Y #Y Cher as Seri Puchong Batu Kem bangan Dua Belas #Y #Y

Pel abuhan Kajang #Y Klang #Y

Semenyih #Y P U T R A J A Y A #Y #Y Broga Bandar Baru Bangi Value driven design and evaluation Value functions & maps (ILWIS-SMCE) Prioritization (ILWIS-SMCE) Branch option favored by stakeholders involved, but for different reasons Spatial multi-criteria evaluation

High Area suitable for demand transit zone area development

Accessibility of area

Environmen Final composite tal index map suitability

1.00

Cost 0.75

0.50 0.25 Area that can be 0.00 developed by transit zone Future Growth

Deprived Area What is the probability of making the wrong decision due to uncertainties in data and priority?

Probability of each alternative being in 1st, 2nd, or 3rd, rank Apply understanding of error and decision making

Uncertainty analysis

Descriptive Normative Error model model Impact on decision certainty

Sensitivity analysis Descriptive Normative Required model model Decision reversal error point Lots of judgments and hotspots Variation and grouping: Do people follow gut feeling or analysis? (Keeney,1990)

Eliciting Public Values for Complex Policy Decisions Ralph L. Keeney; Detlof von Winterfeldt; Thomas Eppel Management Science, Vol. 36, No. 9. (Sep., 1990), pp. 1011-1030. Recent developments in evaluation

Spatial application of multi-criteria evaluation (MCE) Addressing a wider range of problems with spatial multi-criteria evaluation (SMCE): Understanding of problems Designing solutions Choosing solutions Integration of non-spatial and spatial concerns Software for spatial multi-criteria evaluation: ILWIS-SMCE Application to improve group decision processes Focus on spatial sensitivity analysis to evaluate consequences of errors in data for certainty about choices Content

Pyke, C. R., B. G. Bierwagen, et al. (2007). "A decision inventory approach for improving decision support for climate change impact assessment and adaptation." Environmental Science & Policy 10(7-8): 610-621. Comparison of European, national and regional spatial planning systems

Nature Oriented Flood Damage Prevention

http://nofdp.bafg.de/servlet/is/13142/ Content

“Problem [in forest management for mitigation or adpataion] is that we have the difficulty of many jurisdictions.” “We have to consider to become more people based than government based.”

Pers. com. at plenary session Aug. 27 Forest Adaptation 2008, Umea, Sweden The common view

Scales

Levels

Cash, D. W., W. N. Adger, et al. (2006). "Scale and cross-scale dynamics: Governance and information in a multilevel world." Ecology and Society 11(2) Reality’s complexity

Cash, D. W., W. N. Adger, et al. (2006). "Scale and cross-scale dynamics: Governance and information in a multilevel world." Ecology and Society 11(2) Interactions between scales and levels

Cash, D. W., W. N. Adger, et al. (2006). "Scale and cross-scale dynamics: Governance and information in a multilevel world." Ecology and Society 11(2) Interactions may occur within or across scales, leading to substantial complexity in dynamics “scale challenge” = a situation in which the current combination of cross scale and cross- level interactions threatens to undermine the resilience of a human-environment system. “ignorance” “mismatch” “plurality” Example challenges

Challenges of mismatch: Inability to relate an understanding of larger-scale climate dynamics to the decision-making needs of actors at lower levels.

Challenges of ignorance: farmer who is making decisions without knowing that weather in the district is strongly influenced by El Niño and the Southern Oscillation

Challenges of plurality: district water-resource manager “What matters is that the monsoon rains fill the dam by the end of the wet season.” For the mayor of the city downstream, storms come when the rivers are already high and cause destructive floods. How should water levels in the Climate system dam be managed? Climate research Cash, D. W., W. N. Adger, et al. (2006). "Scale and cross-scale dynamics: Water management Governance and information in a multilevel world." Ecology and Society 11(2) Responses to scale challenges

Institutional interplay: UN-Habitat- Google.org program “Inform and Empower to Improve Public Services” http://www.google.org/inform.html

System through “adjustments” made by Co-management (i.e. a continuum of arrangements that rely on various degrees of power- and responsibility-sharing between governments and local communities) Two conclusions from empirical studies: Sub challenges: state nor civil society are homogeneous Successful co-management often arises from the adaptive, self-organizing processes of learning-by-doing rather than from an optimal power-sharing across levels

Boundary or bridging organization (as in our consortium!) Ecomuseum Kristianstads Vattenrike, which grew out of and continues to depend on issue networks to bring in and share information with stakeholders Characteristics: (1) accountability to both sides of the boundary; (2) the use of “boundary objects” such as maps, reports, and forecasts that are co-produced by actors on different sides of a boundary; (3) participation across the boundary; (4) convening; (5) translation; (6) coordination and complementary expertise; and (7) mediation

Cash, D. W., W. N. Adger, et al. (2006). "Scale and cross-scale dynamics: Governance and information in a multilevel world." Ecology and Society 11(2) Content

Context dependent

e.g. biofuels? van Latesteijn, H. C. (1999). Land use in Europe: A methodology for policy-oriented future studies. plantaardige productiesystemen. Wageningen, Wageningen University. PhD: 175. Content

IPCC (2007). Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. . Cambridge, Cambridge University Press. Possible combinations of adaptation and mitigation

Silva, Balance, ZEUS (http://www.wwk.forst.tu- muenchen.de/research/projects/zeus/ ) Heureka (http://heureka.resgeom.slu.se/wiki/index.php?title=Main_Page) Picus (http://www.wabo.boku.ac.at/picus.html?&L=1) Ecological Site Classification Decision Support System (ESC-DSS) (http://www.forestresearch.gov.uk/fr/infd-5v8jdg) Decision Support System Wald und Klimawandel - DSS-WuK (http://www.dss-wuk.de/) NED-2: a decision support system for integrated forest ecosystem management (http://nrs.fs.fed.us/tools/ned/products/ned2/) Content

Liu, Y., H. Gupta, et al. (2008). "Linking science with environmental decision making: Experiences from an integrated modeling approach to supporting sustainable water resources management." Environmental Modelling & Software 23(7): 846-858. Clear and limited! definition of problems

Argent, R. M. (2004). "An overview of model integration for environmental applications--components, frameworks and semantics." Environmental Modelling & Software 19(3): 219-234. Content

Collaborative management, or co-management, has been defined as ‘the sharing of power and responsibility between the government and local resource users’ (Berkes et al., 1991: 12). Singleton (1998: 7) defines co-management as ‘the term given to governance systems that combine state control with local, decentralized decision making and accountability and which, ideally, combine the strengths and mitigate the weaknesses of each. (Carlsson, 2005)

adaptive co-management “A long-term management structure that permits stakeholders to share resource management responsibility and to learn from their actions. It is a systematic approach to improving resource decision making that involves structuring planning and management as a collaborative learning process.” (Cash, D. W., W. N. Adger, et al. (2006). "Scale and cross-scale dynamics: Governance and information in a multilevel world." Ecology and Society 11(2) Content

Uncertainty analysis

Descriptive Normative Error model model Impact on decision certainty

Sensitivity analysis Descriptive Normative Required model model Decision reversal error point

Lohmander, p. (2007). Adaptive optimization of forest management in a stochastic world. Handbook of operations research in natural resources. A. Weintraub, C. Romero, T. Bjorndal and R. Epstein. New York, Springer: 525-543 Content

Presented by : Jaap de Kroes - Alterra

INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Spatial brainstorming/decision room Sketching and Developing Ideas Results of the Model Calculation Collaborative touch screens Spatial planning and decision support systems as web services

Other computer-based External data systems Other computer-based External data systems Data Model management management Data Model management management Knowledge management

Knowledge management Dialogue management

Dialogue management Decision maker/planner

Decision maker/planner Internet

Other computer-based External data systems

Data Model management management

Knowledge management

Dialogue management

Decision maker/planner Looking forward to be working with you!

Partner no. 1 3 4 5 6 9 11 12 13 14 WP1 Keyword 1.1 Climate data preparation 1.2 Climate data center 1.3 Data exchange 1 1 1 1.4 CC scenario downscaling 1 1.5 Plant -atmosphere model coupling 1 1 1 1 1 WP2 2.1 Harmonize site survey methods 1 1 1 1 1 2.2 Inventory prediction monitoring shifts 1 1 1 2.3 Risk assessment 1 1 1 1 1 2.4 Water regime 1 1 1 1 2.5 Ecological goods 1 1 2.6 Economics 1 1 WP3 3.1 MCA 1 1 1 1 3.2 Develop management strategies 1 1 1 1 3.3 Protection strategies 1 1 1 1 1 1 1 1 3.4 Booklet 1 WP4 4.1 Implentation 1 1 1 1 4.2 Advisory board. 1 1 1 1 1 1 1 1 Total 1325 123423510

Institution (Official name) Institution (Official name) 1 Landesforsten Rheinland-Pfalz 9 University of Newcastle upon Tyne 3 KontextU Umweltberatung & Kommunikation 11 Vereniging Nederlands Cultuurlandschap 4 Lehrstuhl für Waldwachstumskunde, Technische 12 International Institute for Geo-information Universität München Science and Earth Observation 5 Office National des Forêts - Direction Territoriale Alsace 13 The Mersey Forest 6 Université Louis Pasteur - SERTIT 14 Forestry Commission