Center for Conservation and Government Enforcement Initiative Presentation to USAID Jim Cannon and Anita Akella April 2 nd, 2003.

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Presentation transcript:

Center for Conservation and Government Enforcement Initiative Presentation to USAID Jim Cannon and Anita Akella April 2 nd, 2003

Goal and Objectives oGoal: Compliance with conservation and natural resource management laws improved oObjectives: 1.Enforcement strengthened 2.Incentives driving illegal logging reduced Opportunity cost of not logging illegally reduced Public perceptions changed 3.Effective and fair conservation and natural resource management laws promoted

Strengthening Enforcement: Approaches 1.Work with national enforcement agencies to implement adaptive management of enforcement, and undertake strategic strengthening activities at all levels of government 2.Work with national enforcement agencies, legislators, the judiciary, national NGOs to clarify jurisdictions, improve enforcement policies and procedures etc. 3.Work with CI field programs and local partner NGOs and train them to carry out enforcement analyses and strengthening programs at the site level

Enforcement Economics Model ED = P d * P a|d * P p|a * P c|p * Penalty * e -rt Where: ED Expected deterrent P d Probability of detection P a|d Probability of arrest given detection P p|a Probability of prosecution given arrest P c|p Probability of conviction given prosecution r discount rate t time from detection through collection of penalty

How the Model Works ED = P d * P a|d * P p|a * P c|p * Penalty * e -rt Calculates the expected deterrent (the expected value of the penalty or enforcement disincentive): the ‘cost’ the illegal actor will consider in his calculations Breaks enforcement system down into its component parts, each of which must happen for enforcement system to be effective By looking at each component piece individually, we develop a precise understanding of where weaknesses are, and therefore why overall enforcement is weak

Insights from the Model ED = P d * P a|d * P p|a * P c|p * Penalty * e -rt Enforcement is more than just detection: more agents and equipment alone will not fix enforcement If any element in the chain is equal to zero, the value of the entire enforcement disincentive falls to zero The time element is critical because of discounting –E.g., a discount rate of 20% and a lag of 5 years reduces the value of the penalty by over 60%

Project Sites and Focus Bahia, Brazil: Illegal logging, illegal deforestation Selva Maya, Mexico: Illegal wildlife trade Palawan, Philippines: Cyanide/Dynamite fishing Papua, Indonesia: Illegal logging, illegal wildlife trade

Atlantic Forest, Bahia, Brazil Original extent of the Atlantic Forest: 3500km along the coastline of Brazil Only 4-5% of original AF still standing Southern Bahia one of the most important “hotspots” for endemism and diversity in the Atlantic Forest Threats include: –Illegal logging –Illegal conversion for agriculture Enforcement Agency: IBAMA

Findings in Bahia Probability of detection is low –Lack of personnel/equipment –Jurisdictional confusion between agencies –Poor training of detection personnel –Low public will to report environmental crime Probability of citation is high, but –Citations often improperly filled out –No evidence or poor quality of evidence Probability of prosecution is low –Cases get ‘lost’ before making it to prosecution –Inaccurate citations/poor quality evidence impede prosecution –Statute of limitations often exceeded due to long processing times

Findings in Bahia (cont.) Probability of conviction low –Prosecutors have little knowledge of environmental law –Difficult to secure convictions if poor evidence/erroneous citations –Judges lack knowledge of environmental law Time is lengthy –Cases pass between locale of crime, Ilheus, and Salvador prior to prosecution –Processing time can take 3 years or longer –Discounting diminishes Enforcement Disincentive

Enforcement Strengthening Priorities in Bahia Task force comprised of IBAMA, CRA and MP set up to clarify jurisdictions for the new Pacto Federativo –Will improve P detection Workshops with IBAMA and MP to streamline case processing procedures –Will improve P prosecution –Will shorten processing times (, t) Develop training curricula and conduct training programs for enforcement agents/forest police, public prosecutors and judges –Will improve all aspects of the enforcement system

Progress to Date in Bahia Obtained World Bank (PPG7) and Ministry of the Environment (Projeto Corredores) support for recommendations Adjusted how existing enforcement strengthening money will be spent by the State Committee for the Atlantic Forest Biosphere Reserve Improved inter-agency collaboration by demonstrating the value of a holistic approach and greater cooperation to enforcement agencies active in Bahia. Two lawyers have been hired to: –Improve quality of prosecution by helping public prosecutors –Help push cases through the system –Refine our understanding of key bottlenecks –Partnership with local university (UESC)

Next Steps in Brazil In Bahia –Supplemental funding for PPG7 enforcement strengthening –Collaborate with civil society partners to implement recommendations –Shift in leadership of enforcement agencies provides excellent opportunity to influence priorities Nationally –Assist national enforcement agencies to report their performance according to international best-practices and implement adaptive management –Promote reforms to enforcement policies and procedures through an inter-agency task force

Papua Province, Indonesia 50% of Indonesia’s terrestrial biodiversity found in Papua 33 million ha of forest: 22 million ha zoned for forestry, 12 million ha currently in concessions Forest governance in flux due to decentralization 50% of illegal logging (by volume) in Indonesia takes place in Papua Enforcement Agencies: Ministry of Forestry, Dinas Forestry, BKSDA, PA management units, Police etc. Illegal logging threat to protected forests in Papua

Preliminary findings in Papua Illegal shipping of logs out of Sorong District These numbers are preliminary and are not to be quoted or cited. Average of 1500m 3 per case Estimated value ~ $100,000 to $300,000 Cumulative probability of being penalized = 0.7% (assumes P d = 0.1) Average penalty = ~ $1000 Average deterrent effect of penalty = $7 Average deterrent effect of confiscation = $700 to $2100 Theoretical maximum fine (Act 41/1999) ~ $1 million Still 50 times lower than required to equal economic incentive, but large fines socially and politically unacceptable Enforcement improvements critical

Enforcement Strengthening Priorities in Papua Challenge: increase enforcement performance by ~ 50 times Requires, e.g.: Improving P d 5x to 0.5 (greater intelligence gathering capacity, improved jurisdictional clarity, better inter- agency coordination, training etc.) Improving P p|a|d 4x to 1 (procedural reform to allow forest civil investigators to work directly with prosecutors etc.) Improving P f|c|p 2.5x to 0.85 (training for prosecutors and judges)

Progress to Date in Papua Results discussed with all enforcement agencies in Papua Early focus on wildlife trade resulted in improved searches Discussions and agreements underway include: Improved intelligence sharing between different agencies, and between NGOs and agencies Suer Surjadi of CI Indonesia discusses searches of naval vessels with Navy commander Mechanism for public complaints/information to be made without fear of intimidation (e.g., anonymous illegal logging tip “hotline”) Strengthening of inter-agency coordination throughout the enforcement system Training to improve detection capabilities, particularly raising quality of evidence and early phases of case development

Next Steps in Indonesia In Papua –Secure additional funding for enforcement strengthening –Collaborate with local NGOs and enforcement agencies to secure agreements and implement recommendations –Initiate training of BKSDA and Dinas Kehutanan directors in adaptive management best practices Nationally –Finalize agreement with Ministry of Forestry Forest Protection DG to: Improve information sharing and assist with coordination between central, provincial and district authorities Report enforcement performance according to international best-practices and implement adaptive management –Promote reforms to enforcement policies and procedures through an inter-agency task force –Explore options for civil society support of high-level illegal logging cases

Lessons Learned Low levels of funding for detection agencies and prosecutorial services –Low infrastructure capacity –Low technical capacity –Financial disincentives to efficient performance Greater collaboration among agencies would result in improved procedural efficiency and higher conviction rates. Biodiversity-rich municipalities are remote and therefore lack their own prosecutors and judges. Sometimes it is better to invest in a new system than to invest in fixing the current system

Lessons Learned (cont.) Multiple audiences in the enforcement chain require training to improve their performance. Laws governing use of natural resources can be conflicting, inadequate, or otherwise weak: –Low penalties for environmental crimes –No clear definition of what is an environmental crime –May not vest agencies at different levels with authority to detect and punish cases of environmental crime Enforcement agencies have no adaptive management systems and do not report annually on performance –Poor data management –Lack of inter-agency collaboration

Priority: Reform Enforcement Policy Provide clarity regarding jurisdiction Increase budget resources to enforcement agencies Create the legal framework for alternative enforcement systems to operate Make penalties and their application more appropriate Establish guidelines for inter-agency cooperation and reporting Create specific prosecutorial/judicial services for environmental crimes

Priority: Implement Adaptive Management Build enforcement agency capacity to monitor enforcement performance Ensure all agencies report enforcement data consistently (definitions, format, IT system etc.) Reach agreement on enforcement statistics to be produced annually Train key enforcement agency staff to analyze statistics using enforcement economics approach Train key enforcement agency staff to develop recommendations for strategic enforcement strengthening Require annual publication (public disclosure) of enforcement performance report