APPENDIX B
INTEGRATION: REGIONAL HABITAT UNITS CHARACTERIZED BY BIOLOGICAL VALUE AND CONSERVATION STATUS

Type 1 - Tropical Lowland Forests

Major Habitat Type 2 - Tropical Montane Forests

Major Habitat Type 6 - Herbaceous Montane Grasslands

Major Habitat Type 7- Temperate Forests

APPENDIX C
SUMMARY OF FOUR INTEGRATION MODELS

Integration Group #1 (Buenos Aires Room)
Barry Chernoff - moderator
Meg Symington - rapporteur
Rhema Kerr, Dan Nepstad, Adriana Moreira, Mary Kalin Arroyo, David Neill, Bruce Potter, Tobey Pierce, Bruce Wilcox, Carlos Peres

This group reached consensus that a three level hierarchical model that first looked at the intersection of biological value and conservation status, next at utility and finally at PI data was appropriate. Other criteria, including geographic distribution, degree of neglect and amount of previous investment were also considered appropriate to modify the results of the first hierarchical level of analysis.

The thickly outlined squares in the table below were rated of urgent investment priority, the shaded squares of high investment priority, and the unshaded squares of moderate investment priority.

The group agreed that in differentiating Regional Habitat Units that fell within the same cell, utility and PI consideration could be used, but since only 14 units were classified as of urgent priority using this model, the need to differentiate between RHUs on this basis was not applied in practice. As applied by the group, this model did not rank order the RHUs within each major habitat, but merely classified them as urgent, high or moderate investment priority. In theory, utility and PI screens could differentiate between RHUs found within the same cell and result in a rank ordering of RHUs within Major Habitat Types.

Integration Group #2 (Brasilia Room)
Doug Stotz - moderator
Gustavo Fonseca - rapporteur
Jorge Soberón, Frances Seymour, Otto Huber, Miguel Cifuentes, Raul Gauto, Pablo Marquet, George Burgess, Kent Redford, Alejandro Grajal, Silvio Olivieri

Guiding Principle: Regionally Outstanding Biological Value Units Receive First Priority.

Within the regionally outstanding biological value group, conservation/threat placed in following order: critical > endangered > intact > stable > vulnerable.

Then treat regionally significant biological value, critical conservation status units.

For those units, evaluate whether the PI measure of short-term capacity in countries of relevance is sufficient to make it likely that investment would greatly and positively impact the aggregate unit. If PI rating suggests that investment is likely to make a positive impact (not low-low, see Cell D in Table 4), then investment would be appropriate. Otherwise, investment would not be appropriate.

Next treated are units of locally important biological value and critical conservation status. We ask at this point whether the unit is adequately represented in protected areas (the Olivieri test). If it is, then no investment is warranted. If it is not, then we treat it as we previously treated units of regionally significant biological value and critical conservation status.

A. We then go to units of regionally significant biological value that are considered intact. We first ask whether there exists an "intact" unit of regionally outstanding biological value in the same Major Habitat Type. If so, we postpone a decision on the unit and consider units of regionally significant biological value that are considered endangered.

B. If we consider the endangered units at this point, we recommend investment.

C. If an intact unit of regionally outstanding biological value is found within the same Major Habitat Type, then we ask a question regarding the effectiveness of investment in maintaining the intact units of regionally significant biological value (whose treatment was begun in A) as an extensive "functional" ecosystem. If investment of a long-term nature in increasing capacity is expected to have a significant positive influence on the maintenance of the unit in the long-term, then investment is appropriate (low existing capacity; high commitment/trend). If it is judged that investment would have little effect on long-term maintenance of the ecosystem, we postpone action on the unit and consider units of regionally significant biological value that are considered endangered.

D. Endangered units of regionally significant biological value should receive investment after intact units, if investment is appropriate in intact units (as described in C above), or before those units, if investment was deemed not appropriate. If endangered units of regionally significant biological value have been dealt with and intact regions of regionally significant biological value remain in which investment has not been placed, due to the decision rules at A and C, investment to ensure long-term protection of those units is considered the next priority.

E. At this point we consider those units considered of regionally significant biological value and relatively stable conservation status. We now ask a question similar to point C for intact regions. Will investment of a long-term nature in increasing capacity of the appropriate institutions have a significant positive influence on the maintenance of a major area of the unit with substantial integrity as a "functional" system (e.g., PI commitment high, capacity low)? If so, then investment is appropriate. If not, then return to units of regionally significant biological value and vulnerable conservation status, and ask question above for these units. Again, if the answer is yes, then investment would be appropriate. If not, then return to the units of regionally significant biological value and relatively stable conservation status. Any of these not deemed appropriate for investment by the question above, are now appropriate for investment. Any remaining units of regionally significant biological value and vulnerable conservation status without investment, would at this point, following investment in relatively stable units, be appropriate for investment.

Notes:

1. This provides a set of decision rules by which to rank units for investment priority within a single Major Habitat Type.

2. Utility was not included in this ranking scheme. A plan whereby a utility ranking of "high" for a unit which scored as locally important in biological value would cause that unit to be treated in the previous scheme just as if it had been ranked as being regionally significant was proposed, discussed and generally considered a good idea. When the model presented here was completely elaborated, this idea was not revisited however, so the group did not formally incorporate this into the model. It is presented here as an idea on how utility information might be integrated into this approach.

3. Because this model places emphasis on intact units for their potential to protect "ecosystem-level" values, for the purpose of evaluating which units are "intact," the snapshot conservation status ranking should be used rather than the conservation status modified by dynamic threat. This provides a measure of the current conditions within the unit which is appropriate to the analysis.

Integration Group #3 (Kingston Room)
Mario Baudoin - moderator J
uan Pablo Ruiz - rapporteur
Salvador Contreras, Phil DeVries, José Ottenwalder, Andrew Henderson, Jorge Hernandez Camacho, Roberto Cavalcanti, Shirley Keel, Agustin Iriarte, Michael Yates, Eric Dinerstein, John Robinson

The group took as its starting point the seven squares of the matrix that were highlighted in the illustrative model presented in the plenary as of highest priority.

These cells were selected as a priority based on the need to keep RHUs from falling into the critical category, as well as the need to diversify the donor's investment over the full spectrum of conservation threat. Since investment in critical areas is much more costly per unit of biodiversity conserved than investment in intact areas, donors should diversify their portfolio in relation to conservation threat.

If the RHU in these squares fell entirely within one country, then investment should be in that country, regardless of PI.

If the RHUs in these cells crossed national boundaries, then another iteration of the biological value/conservation status model should be carried out to determine which country within the RHU should receive investment. The country whose portion of the RHU is regionally outstanding in terms of biological value and most intact (upper right corner of the matrix) should receive investment. If the portions of the RHU in different countries are equal in terms of biological value and conservation status, then the PI value should be used to determine where and what.

Integration Group #4 (Nassau Room)
Jim Barborak - moderator
Keith Brown - rapporteur
Pablo Canevari, Richard Howard, Gerardo Lamas, Márcio Ayres, Bill Duellman, Francisco Erize, Ernesto Barriga, David Heesen, Frank Zadroga, Russ Mittermeier, Kathy Saterson, Doug Graham, Roberto de la Maza

1. Group members present gave a summary of their ideas on how to integrate, weight, use or work with the data at hand: biological value (R,S,L); conservation status/threat (C,E,V,S,I); aquatic systems (fish group); ecosystem utility; and policy/institutional summary ratings (capacity/commitment, H,M,L). These included some important points:

a) some felt that biological values should receive higher weight than landscape.

b) many felt that data were not satisfactory even in these two levels of analysis, and that great biases were present related to taxon, size of RHU, country, and threat. Others pointed out that these will never be ideally perfect.

c) aquatic systems: group consensus that these were best used for a posterior adjustment, (i.e., adding bonus points to those high priority RHUs which were also important for fish).

d) major habitats: in smaller or narrow countries, several major habitats can be included in a single conservation study, process or unit. This is not possible in larger countries. (Editor's note: even in larger countries project/conservation units can span major habitats, e.g. in Manu National Park, montane grassland, montane forest, and lowland forest are all found).

e) threat levels almost all guesses, many inflated, subjective.

f) PI data, applied just on upper left six squares of biological value/conservation status matrix, gives a very broad geographic and unit coverage (20/21) if only four high capacity countries (Brazil, Argentina, Colombia, Barbados) plus Mexico and three more medium capacity countries receive extra funds for biodiversity investments. This sliding data set may prove useful for priority determination.

g) PI data are insufficient and should be mostly used to determine how to distribute aid among countries within a unit.

h) might be good to distribute to lots of countries and units as "bet-hedging."

2. It was noted that PI ranking of high capacity and high commitment could favor investment in short-term critical situations whereas low PI rank could identify those countries to be selected for long-term capacity-building investments.

3. MODEL for Integration proposed: A 1:1 non-biased square accepted, and the RHUs occupying the cells up to Rank #10 were identified from the previous days' work. In the matrix below, the point value and rank (in parentheses) of the cells are given.

The three top left squares (ranked 1-3) include 7 units. The six upper left squares (ranked 1-6) include 18 units.

Some RHUs moved between cells on the basis of fish analysis and utility for tropical moist forest (low, montane). This "upgraded" Upper Amazon, Llanos and Chocó-Darién.

PI would be used only for noting differences in various countries within each unit. This data will also be useful in determining the type of investment (the "what" as opposed to the "where").

Combination of units that can be treated together in local or country-level work permits reduction of RHUs to only 17, drawing in two more units. These are recommended with top seven of required attention (RHUs in darkly outlined cells below) and next 10 of urgent priority (RHUs in shaded cells below).

APPENDIX D
SAMPLE DATA FORMS USED BY WORKSHOP PARTICIPANTS TO ASSESS BIOLOGICAL VALUE, CONSERVATION STATUS AND POLICY/INSITUTIONAL FEASIBILITY

APPENDIX E1
ANALYSIS OF DATA INDICATOR USEFULNESS AND DATA NEEDS FOR POLICY AND INSITUTIONAL (PI) COMPONENT

Latin American experts assessed the usefulness of data indicators presented at the Miami BSP Biodiversity Priority-Setting Workshop in terms of their usefulness for evaluating national-level institutional capacity, commitment and other factors affecting the effectiveness of external assistance. Experts were also asked to define what other data (both existing and uncaptured) would be useful in such an exercise. The results of this assessment, gathered through a questionnaire survey and a workshop session, are presented below.

A. Indicator data made available for PI component, considered useful by Latin American experts.

Each of the 18 data indicators presented at the Miami Workshop were considered to be at least somewhat useful by at least one of the questionnaire respondents, with one exception-paved road density-which has been deleted from the list below.

** ranked as a "5" on a 1-5 ranking scale (5 = very useful) by at least one respondent.

* ranked as a "4" on a 1-5 ranking scale (5 = very useful) by at least one respondent.

* National level biodiversity reporting and planning: Tropical Forestry Action Plan (TFAP); UNCED National Report; UNEP Country Study; and Biodiversity Strategy or Action Plan

** Ratification of regional treaties: 1940 Convention on Nature Protection and Wildlife Preservation in the Western Hemisphere, Conservation of Biological Diversity, Regional Seas

* Participation in major global conventions: Ramsar, World Heritage, CITES, Migratory Species (1979) and Biodiversity Convention

* CITES reporting requirement met

Per capita GNP

** Overseas Development Assistance (ODA) as a percent of GNP

Debt service as a percent of export revenue

* Percent of R&D scientists in the natural resource sector * Scientists and technicians per 1,000 population

* Average number of zoos

* Average number of vertebrate species per zoo

* Average number of botanical gardens

** Protected areas staffing and funding

** UNDP Human Development Index (Index is based on 3 equally weighted indicators: longevity as measured by life expectancy; knowledge as measured by adult literacy and mean years of schooling; and income as measured by per capita purchasing power parity)

** "Human Freedom" Index (Index is based on sum of two scores: "civil liberties" and "political rights")

* U.S. funding for biodiversity conservation

** Donor funding for biodiversity conservation from European Union and U.S. bilateral and multilateral organizations

B. Existing data that experts felt should be included in future PI assessments:

- number of NGOs per country (based on UNCED data)
- disbursements of externally-provided funds (as indicators of absorptive capacity)
- number of gene banks in a country
- distribution of landholdings (average size of holding, % of farmers per holding class size)
- actual land use vs. potential land use
- literacy rate (male, female)
- % of men and women voting
- media (number of newspapers, radios, per 1,000 people)
- access to family planning - income distribution
- existence of national environmental funds (IUCN)

C. Data indicators we wish we had (data may exist, but have not been captured) for use in a PI assessment:

- % gov't. budget allocated to conservation (include trend data)
- external funds going to national spending on biodiversity conservation (trend data)
- money spent to implement treaties (by source)
- donor funding for all forms of development (trend data, disaggregated by source)
- government funding spent on conservation legislation enforcement -
(complete) data on protected area staffing and funding
- number of visitors (national, international) to protected areas
- revenues from park fees (and other measures of revenues from biodiversity conservation)
- numbers of guards in protected areas
- ratio of protected area personnel in field vs. central office
- protected areas: actual boundaries
- disaggregated data on number of employed scientists in natural resource sector (i.e. those directly involved in conservation)
- disaggregated data on number of research and development scientists in natural resource sector (i.e. those directly involved in conservation)
- proxies for indigenous ownership/control (of biodiverse lands), e.g., existence of supportive laws, number of indigenous groups
- number of environmental impact assessments completed per country
- budgets allocated to gene banks
- percent of newspaper coverage (in column inches) devoted to conservation issues

APPENDIX E2
CONSENSUS STATEMENT POLICY /INSITUTIONAL WORKING GROUP

IMPORTANCE OF POLICY/ INSTITUTIONAL INFORMATION

Working group members agree that policy/institutional factors should be taken into account in the setting of geographical priorities for the allocation of limited biodiversity conservation investment resources. Policy/institutional data and analysis can be used as a discriminator ("tie-breaker") when choosing among similar alternatives generated by biological value and threat/opportunity assessments. It can also be used to inform decision-making related to the types of activities to be supported.

ADEQUACY OF CHECKLIST ASSESSMENT INSTRUMENT

Working group members agree that while imperfect, the checklist assessment instrument refined during the workshop effectively identifies the key features of the country-level policy/institutional landscape relevant to strategic, course-scale, region-wide decision-making regarding the allocation of conservation investment resources. In order to inform decision-making at the country level, the instrument would have to be reapplied at a smaller scale. In addition, comparisons among parts of countries such as Brazil, where sub-national level policy/institutional landscapes may be very different from national or country-wide landscapes, would require repeating the analysis at the sub-national level.

THE INDIVISIBILITY OF "WHERE" FROM "WHAT" AND "HOW"

Working group members agree that in the case of policy/institutional factors, it is not possible to separate the analysis of where investments should be directed from the question of what conservation interventions are proposed and how they will be implemented, including their time horizon.

Working group members recommend that policy/institutional analysis should be used to develop a diversified portfolio of investments to achieve conservation goals that balances risk and benefit over any given time horizons. For example, where important biological units are highly threatened in the short-term, on-the-ground investments in countries with existing institutional capacity and other factors affecting the effectiveness of external assistance should be given priority. Conversely, where important biological units are not immediately threatened, capacity-building investments in countries with low institutional capacity and other factors but high political commitment and a positive trend should be given priority.

SAMPLE SIZE AND COUNTRY EXPERTISE LIMITATION

Working group members agree that due to the limited number and country expertise of workshop participants, there is an insufficient basis of expert opinion to inform the policy/institutional characterization of certain countries.

STANDARDIZATION AND SCALE ISSUES AMONG COUNTRIES AND SUB-REGIONS

Working group members agree that standardization presents an important methodological problem constraining the comparability of expert opinion data due to the insufficiently detailed scoring instructions, the lack of overlap among participants' country expertise, and insufficient time to standardize scoring through group discussion at the workshop. Further specification of the meaning of intermediate scores in the checklist assessment instrument would improve the standardization of the methodology.

Working group members agree that the methodology is most useful for comparisons across countries that are similar in scale. For example, standardization problems would be lessened if comparisons were limited to within three groups: South America and Mexico, Central America and the Greater Antilles, and the Lesser Antilles.

POST-WORKSHOP USE OF DATA AND ANALYSIS

Working group members agree that a wealth of useful data and analysis has been captured through the checklist assessment and PI working group discussions. However, there are important limitations on how that data and analysis, and any analysis conducted subsequent to the workshop, should be used.

Reporting of workshop data and analysis of policy/institutional factors should be accompanied by explanatory text asserting the preliminary and experimental nature of the workshop exercise. Such text should include detailed statements of the limitations of the data and analysis, including, among others, the issues of sample size, standardization, and scale mentioned above.

In addition, reporting of workshop data and analysis of policy/institutional factors should be accompanied by explanatory text that could function as a "users' guide." Such text should include, for example, an explanation of how the data and analysis should be used to provide different answers to different questions, such as priorities for short-term, on-the-ground conservation interventions vs. long-term institutional strengthening strategies.

Working group members agree that it may be preferable to present data and analysis in qualitative rather than quantitative terms (i.e. high/medium/low as opposed to 1-5) to avoid creating an illusion of false precision, and to prevent users from focusing on numbers at the expense of the valuable qualitative information captured through the assessment process.

Working group members agree that policy/institutional data and analysis have a short half-life, and should be updated to coincide with the time-frame of decision-making processes.

POST-WORKSHOP REFINEMENT OF ANALYSIS

Working group members recommend that the analysis be improved by expanding the number of experts providing opinions. Accordingly, a broader, representative group (which could include USAID mission staff as well as additional in-country expertise) should be surveyed through the checklist instrument for each country being assessed.

Working group members recommend that for large countries in particular, supplementary expert opinion data should be collected for the sub-national level. This implies the development of two separate checklist assessment instruments, national and sub-national, in order to be able to disaggregate sub-national conditions and trends by province or state for countries such as Mexico and Brazil.

OTHER RECOMMENDATIONS

Working group members recommend that the checklist assessment instrument be provided to individual USAID missions and other organizations; these organizations should make an effort to collect some of the existing but "uncaptured" policy/institutional data identified by workshop participants as being useful for decision-making to inform future priority-setting exercises.

Working group members recommend that the names of individual experts should not be associated with specific policy/institutional scores in public reports.

APPENDIX E3
USING POLICY AND INSTITUTIONAL DATA-EXAMPLES

Following up on a recommendation from the Policy and Institutional (PI) working group at the Miami workshop, a mail survey was conducted subsequent to the workshop to obtain additional expert opinion data. The survey was sent to individuals suggested by members of the PI working group as having expertise on the political and institutional climates of a subset of seven Latin American countries selected for further PI analysis. A copy of the survey instrument is included in Appendix D.

The individuals surveyed represented a variety of institutional affiliations-including NGO representatives, academics, and government officials-and it was hoped that the sample would capture a range of perspectives. The purpose of the survey was to:

Slightly more than one-quarter of the 22 individuals contacted responded to the survey. Based on this experience, it would appear that a mail survey is an efficient method for collecting preliminary PI data, as a 25 percent response rate is considered average for mail surveys of this type. None of the respondees indicated that they had difficulty understanding and completing the questionnaire they received. The individuals surveyed were given only two weeks to respond. Through a combination of a longer grace period and follow-up phone calls to non-respondents, one might expect a higher response rate in future surveys.

Table 1 presents the results of the mail survey, augmented by expert opinion data collected from experts at the Miami workshop. For the seven countries depicted, the table shows average scores (on a five-point scale) questionnaire respondents gave when rating each country on the following four characteristics:

(i) political commitment;
(ii) institutional capacity;
(iii) additional factors affecting the effectiveness of external assistance; and
(iv) overall trend (for the previous three criteria).

Table 1. Example of Policy/Institutional Country Rankings

Data presented here are for illustrative purposes only. Because of the lack of standardization and small sample size (an average of only four responses per country), results should not be used for priority-setting.

To avoid the appearance of false precision in reporting inherently qualitative data, the PI working group recommended that PI results be reported as qualitative descriptions rather than as quantitative, raw scores (e.g., "low," "medium," and "high," rather than numerical scores on a 1-5 scale). As is evident from Table 1, PI scoring tended to cluster around the middle of the 1-5 range, perhaps due to reluctance on the part of experts to score countries as either an abysmal 1 or a perfect 5 (particularly in the absence of clear guidance on how to standardize the scoring). However, as differences between countries are indistinguishable when raw scores are lumped into three qualitative categories, for the limited purpose of this illustrative example the survey results are reported here as raw scores (which could easily be translated into five rather than three qualitative descriptors: very low, low, medium, high, and very high.)

Two examples illustrate how PI data might be used in a priority-setting framework. In these examples, only "institutional capacity" and "political commitment" scores are counted (i.e., scores for "additional factors" and "overall trends" do not weigh into the process). Figure 1 is a matrix showing the relative institutional capacity and political commitment scores of the seven countries included in this sample. Countries falling closest to the top left-hand axis represent countries with the highest capacity and commitment (corresponding to "cell A" in Table 4).

For the purposes of these examples, it is assumed that policy-makers are building a portfolio of biodiversity conservation investments, some with short-term, low-risk returns, and others with longer-term, higher-risk returns. It is further assumed that where priority RHUs are highly threatened (i.e., toward the critical end of the critical-intact spectrum in the conservation status analysis), policy-makers would favor investment where high institutional capacity exists, so that immediate, on-the-ground conservation activities would have a high probability of success. Conversely, it is assumed that where priority RHUs are toward the other end of the landscape integrity scale (i.e., representing more conservation potential than threat), policy-makers would be interested in investment in long-term capacity-building activities, and would weigh existing political commitment more heavily than existing institutional capacity.

Example 1: PI Data Used to Prioritize Among Countries that Share a Priority RHU

Many RHUs in the Latin America and Caribbean region straddle national boundaries, and policy-makers will be faced with the decision of which national portion to prioritize for investment. (Clearly, RHUs are not internally homogeneous in biological importance, conservation threat and opportunity, and utility either; for the purposes of this example, PI data will be assumed to be the most important discriminating variable.)

The tropical Andes, a priority RHU generated by the "hybrid" integration model, has significant portions of its area in four countries: Colombia, Peru, Ecuador, and Venezuela. For the purposes of illustration only, the PI expert opinion data set generated by Miami workshop participants and the mail survey is used to rank order the four countries for the two different investment objectives described above. As the tropical Andes RHU was rated as "endangered" on the landscape integrity scale, it is likely that policy-makers would favor investment in countries with high institutional capacity, where immediate conservation interventions could be expected to be effective in the short term (with political commitment also preferred but given less weight). Priorities in this example would be, in descending order: Colombia, Peru, Venezuela, and Ecuador (see Figure 1).

If, in contrast, the Tropical Andes RHU had been rated as "stable" or "intact," policy-makers would be expected to favor opportunities to invest in building institutional capacity where political commitment is high to assure conservation of these areas in the long term. Priorities in this example would be, in descending order: Colombia, Venezuela, Peru, and Ecuador (see Figure 1).

Example 2: PI Data Used as a Tie-breaker Between Equivalent RHUs

In a few cases in the Latin American and Caribbean region, more than one RHU from a single major habitat type are given the same ratings for biological value and conservation status (i.e., the RHUs end up in the same box in the matrix included in Appendix B). In that case, integration models require a decision-rule for discriminating between the two otherwise equivalent RHUs, and using PI data to break the tie is one option. (Other options considered at the Miami workshop included utility data and aquatic biodiversity data.)

The NGO Working Group integration model ranks two herbaceous montane RHUs, Paramo and Puna, as having "high" biological value and "vulnerable" conservation status. For the purposes of illustration only, the PI expert opinion data set generated by Miami workshop participants and the mail survey is used to rank order the two RHUs for the two different investment objectives described above. In order to generate numerical PI scores for each RHU, the PI scores for each of the countries that harbors at least 10 percent of the Paramo (Colombia and Ecuador) and the Puna (Peru, Bolivia, Argentina, Chile) RHUs are combined. (In this example, the scores were given equal weight; alternatively, country scores could be weighted for percent area.) Ideally, sub-national level data for the PI characteristics of the relevant portion of each country would be available, facilitating comparison of all otherwise-equivalent RHU segments.

Table 2. Using PI Data as a Tie-Breaker

In this illustrative example, whether policy-makers wanted to make a short-term investment in on-the-ground conservation activities or a long-term investment in capacity-building, the Puna would be somewhat favored over the Paramo due to its higher composite scores for both institutional capacity and political commitment, although the difference in raw scores is small (see Table 2).

APPENDIX F
ALPHABETICAL LIST OF WORKSHOP PARTICIPANTS

WORKSHOP ON GEOGRAPHIC BIODIVERSITY CONSERVATION INVESTMENT PRIORITIES IN LATIN AMERICA AND THE CARIBBEAN MIAMI, FLORIDA, SEPTEMBER 27 - OCTOBER 1, 1994

APPENDIX G
WORKSHOP AGENDA: GEOGRAPHIC BIODIVERSITY CONSERVATION
INVESTMENT PRIORITIES IN LATIN AMERICA AND THE CARIBBEAN

SHERATON BISCAYNE BAY, MIAMI, FLORIDA September 27 - October 1, 1994

MONDAY, SEPTEMBER 26

NGO Working Group members arrive
GIS/Administrative staff arrive

TUESDAY, SEPTEMBER 27

All other participants arrive

2 pm - 6 pm Workshop Registration. Look for table near the Hotel Lobby Registration Desk.

6 pm - 8 pm OPENING PLENARY Session: Introduction of priority setting project, project objectives, expected results, introduction of participants

8 pm - 10 pm Reception - Bayside Terrace

WEDNESDAY, SEPTEMBER 28

Biological (Taxonomic) Maps and Policy/Institutional Methods

7:00 - 8:00 Continental Breakfast

8:00 - 9:30 PLENARY Session: Review of agenda; review of process and products; assignment of tasks and working groups; introduce habitats and aggregated ecoregions

9:30 - 10:30 Seven Simultaneous Working Group Sessions

Six taxonomic working groups (see List A for proposed members) convene to review data collected for birds, mammals, herps, butterflies, plants and freshwater fish, revise and add data as necessary.

Policy/institutional (PI) working group (see List B for proposed members) convenes for introduction and overview of the institutional component-purpose, data, methodology. Review additions and revisions to data indicators, revise where necessary.

10:30 - 10:45 Morning Coffee Break

10:45 - 12:30 Continue with Working Group Sessions

12:30 - 1:30 Lunch Buffet

1:30 - 4:15 Simultaneous Taxonomic and PI working groups reconvene. By the end of the day biological priority maps are produced for 6 taxonomic groups: birds, mammals, freshwater fish, insects (butterflies), herps and plants. These taxonomic priority maps integrate considerations of alpha diversity, beta diversity, higher taxonomic diversity, endemism and presence of threatened and endangered species for each taxonomic group. Methods for weighting these indicators and proxy indicators for habitat diversity discussed.

PI working group reviews checklist indicators and revises where necessary. Trial application of country-level assessment. Assess and refine overall methodology. Discuss weighting schemes. Bruce Wilcox will confer with individuals from biological priorities group to complete assessment of species-level utility data. Outputs: By end of day, will have a revised institutional assessment methodology, and proposals for how to weight component categories.

4:15 - 4:30 Afternoon Coffee Break

4:30 - 7:30 Continue with Working Group Sessions

7:30 Adjourn for the Day

THURSDAY, SEPTEMBER 29

Overall Biological Priority Maps and Policy/Institutional Feasibility

7:00 - 8:00 Continental Breakfast

8:00 - 10:30 Simultaneous Subregional Biological Working Groups (see List C attached) convene to prepare one integrated biological priority map (integrating six separate taxonomic priority maps).

PI Working Group: regional subgroups apply revised methodology to assess all LAC countries. Review data and possible weighting schemes.

10:30 - 10:45 Morning Coffee Break

10:45 - 12:30 Continue Subregional Biological and PI working groups.

PI working group: presentation of utility component. Data assessment.

12:30 - 1:30 Lunch Buffet

1:30 - 4:15 Continue Subregional Biological and PI working groups.

PI Working Group: Complete utility data assessment, discuss ranking scheme. Outputs: By end of day will have completed national-level institutional assessment, collected and revised all data for utility overlay.

4:15 - 4:30 Afternoon Coffee Break

4:30 - 5:30 Continue Subregional Biological and PI working groups.

5:30 - 7:30 PLENARY Session for presentation of subregional integrated biological priority maps and discussion

7:30 Adjourn for the Day

FRIDAY, SEPTEMBER 30

Conservation Threat & Opportunity and Policy/Institutional at Sub-National Level

7:00 - 8:00 Continental Breakfast

8:00 - 9:30 PLENARY Session to explain data needs from experts concerning conservation threat and opportunity. PI Working Group will explain sub-national institutional assessment methodology.

9:30 - 10:30 Subregional Conservation Threat & Opportunity Working Groups (see List D attached) will convene to identify and delineate relatively intact blocks of original habitat, identify and delineate important landscape features such as corridors, areas containing critical habitat for various components of biodiversity and areas important for critical ecosystem functions (e.g., watershed protection). Discussion of methods for assessing the relative degree of degradation of habitat types.

PI Working Group's core institutional members (several individuals not involved in threat assessment) will review and revise national-level assessment, propose methods for integrating with utility sub-component.

10:30 - 10:45 Morning Coffee Break

10:45 - 12:30 Continue Subregional Conservation Threat & Opportunity and PI working groups.

12:30 - 1:30 Lunch Buffet

1:30 - 4:15 Subregional Conservation Threat & Opportunity Working Groups continue to meet.

PI Working Group: regional subgroups will complete sub-national assessment for select areas (AUs that look like they will emerge as investment priorities biologically). Outputs: By the end of the day, will have completed both the utility and sub-national institutional overlay.

4:15 - 4:30 Afternoon Coffee Break

4:30 - 7:30 Continue subregional conservation threat & opportunity and PI working groups. Produce conservation threat & opportunity maps by subregion. Produce national and sub-national policy/institutional feasibility priorities.

7:30 Adjourn for the Day

SATURDAY, OCTOBER 1

Integration and Recommendation of Investment Priorities

7:00 - 8:00 Continental Breakfast

8:00 - 9:30 PLENARY Session to present conservation threat and opportunity priority maps by subregions.

9:30 - 10:45 PLENARY Presentation of policy/institutional feasibility, and human utility priorities.

10:45 - 11:00 Morning Coffee Break

11:00 - 12:30 PLENARY to explain and begin integration.

12:30 - 1:30 Lunch buffet

1:30 - 4:15 Smaller working groups meet to produce integration of three levels of analysis (Biological, Threat/Opportunity, Policy/Institutional). Preliminary integration scenarios attempted for the aggregated ecoregions within one Major Habitat Type.

4:15 - 4:30 Afternoon Coffee Break

4:30 - 5:00 Smaller integration groups continue to meet.

5:00 - 6:30 PLENARY to present integration results. Closing.

7:30 - 10:30 Closing dinner (Cash bar opens at 7:30, dinner at 8:30)

SUNDAY, OCTOBER 2

Regional Experts and observers depart.

8:00 - 11:00 Core NGO/USAID Working Group meeting to discuss workshop results and discuss schedule and activities for integration and development of products for USAID.

LIST A

BIOLOGICAL (TAXONOMIC) WORKING GROUPS

LIST B

POLICY/INSTITUTIONAL FEASIBILITY WORKING GROUP

LIST C

SUBREGIONAL BIOLOGICAL WORKING GROUPS

LIST D

CONSERVATION THREAT/OPPORTUNITY WORKING GROUPS

Appendix H:

Literature Cited and Bibliography of Other Selected Biodiversity Priority Setting References:

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