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Performance Indicator Reference Sheet - 1

Name of Develop Objective:  To promote low emissions development in Ghana’s Western Region by strengthening community-based natural resource management and monitoring.

Name of Related Output: Improved environment and natural resource management

Name of Indicator-1: 4.8-7 Quantity of greenhouse gas (GHG) emissions, measured in metric tons of CO2e, reduced or sequestered as a result of USG assistance

Is this a USAID Annual Report indicator?  Yes, for all reporting years.

DESCRIPTION

Precise Definition(s):  This indicator reports the quantity of greenhouse has (GHG) emissions, estimated in metric tons of CO2-equivalent, reduced, sequestered, and/or avoided, as a result of USG activities, as compared to a baseline level of GHG emissions.  Relevant greenhouse gases (GHGs) are CO2, methane and nitrous oxide. However, measuring CO2 equivalent is the surest way of converting quantities of the other GHGs into a common, globally comparable metric which has a well-defined potential effect of climate change. CSLP’s interventions will reduce GHS emissions through sustainable natural resource management practices, biodiversity conservation, forest protection and afforestation.

The baseline for this indicator is the ‘business as usual’ reference for GHG emissions that would have occurred during the reporting period if there had been no USG intervention.

This indicator is a calculated estimate and not a result of direct emissions measurements. CSLP utilizes look-up tables based on evidence based data from Ghana’s FORIG and a study commissioned by Ghana’s Forestry Commission. This is locally accepted method of calculating / estimating CO2 equivalent reduced or sequestered. The indicator therefore measures the direct contribution of USG assistance through CSLP.

 

Note: for the detailed calculation of GHG by the CSLP, refer to the following CSLP guidelines/documents

  • Guidelines for Estimating Greenhouse Gas (GHG) Equivalents in the Coastal Forest Landscapes of the Six Districts of Ghana’s Western Region
  • Land Use Land Cover (LULC) classes used by the CSLP

 

Higher=Better.

Indicator Type:          Outcome

Unit of Measure:  Metric Tons of Co2 equivalent

Disaggregated by: N/A

Justification & Management Utility: The Development Objective (The Overall Goal) of the project is aimed at reducing emission of greenhouse gases.  It is therefore required to have an indicator that can help to estimate carbon sequestration using a transparent and globally acceptable procedure. This indicator will enable the project to know whether emission is stabilized, reducing or increasing as a result of USG assistance in the region. The indicator estimates CO2 equivalent because it is now the global standard measure of carbon emissions reductions or sequestration.

PLAN FOR DATA ACQUISITION BY CSLP

Data collection method:  The measurement will be done through land use/vegetation/biodiversity sampling sites’ measurement of parameters and using standard formulas to estimate carbon stocks. Based on the field data collected, The AFOLU carbon calculator will be employed to calculate the carbon stocks using USAID standard formulas.

Data Source:  The source of data will be field measurements taken by the CSLP and partner staff as well as community volunteers whose capacity will be built to monitor carbon stocks regularly.

Method of data acquisition by CSLP:  The identified sites will be monitored at set periodic times and the set parameters will be measured. Carbon stocks will be calculated and compared with previous years.

Frequency and timing of data acquisition: Data will be received monthly by the CSLP Specialists from the field for analysis and processing.

Estimated cost of data acquisition:  Estimated cost (in dollars and/or level of effort) of collecting, analyzing and providing the data to USAID is TBD.

Individual(s) responsible at CSLP:  The Environmental Planning and Spatial Planning Specialist, Assistant Director and M&E Specialist.

Individual(s) responsible for providing data at CSLP:  The CSLP Director and the Assistant Director  

Location of Data Storage:  The data will be stored electronically within the CSLP office in Takoradi.

DATA QUALITY ISSUES

Data Quality Assessment:  To be done on periodic basis

Known Data Limitations and Significance (if any):   (The current method only estimates above ground carbon stocks. However, in many project landscapes such as the operational areas of CSLP, carbon stocks are likely to be contained below ground (in dead wood, soil organic carbon etc.) and could be as higher as that above ground. Therefore, carbon stocks are most likely to be underestimated significantly within the operational areas across the 6 coastal districts.

Actions Taken or Planned to Address Data Limitations:  The data collection process to be used in measuring carbon stocks above ground will be quite intensive and rigorous, in order to obtain a good estimate of carbon stocks.

PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING

Data Analysis:   Data will be analyzed through spot checks by the Environmental Services Specialist, Assistant Director and USFS experts on a semiannual basis to ensure data quality.

Presentation of Data:    Data will be presented through graphics (charts and tables) as much as possible to allow for easier interpretation by all stakeholders including community-level partners.  Additionally, reporting will include narrative descriptions.

Review of Data:   Data will be reviewed semiannually in order to ensure data quality and to provide updated information for quarterly reporting to USAID.

Reporting of Data:  Annual reports will feature data tables along with narrative information.  Budget requests will similarly leverage data analysis, where possible and practical, in order to request additional funding.  Reports to the US Ambassador and other interested USG and Government of Ghana counterparts will also include data whenever and wherever practical.

OTHER NOTES

Notes on Baselines/Targets:  Targets for FY2016-FY2018 were set based on experiences and lessons learned in FY2014 and FY2015 and in consultation with USFS

THIS SHEET LAST UPDATED ON:  05/10/17

 

 

 

Performance Indicator Reference Sheet - 2

Name of Develop Objective:  To promote low emissions development in Ghana’s Western Region by strengthening community-based natural resource management and monitoring.

Name of Related Output: 1: Increased incomes from livelihood diversification 2: Improved environment and natural resource management

Name of Indicator-2:  4.8.1-26 Number of ha of biological significance and/or natural resources under improved NRM as a result of USG assistance

Is this a USAID Annual Report indicator?  Yes, for all reporting years.

DESCRIPTION

Precise Definition(s):  “Improved natural resource management” includes activities that promote enhanced management of natural resources for one or more objectives, such as conserving biodiversity, sustaining soil or water resources, mitigating climate change, and/or promoting sustainable agriculture.

Management will be guided by a stakeholder-endorsed process following principles of sustainable NRM and conservation, improved human and institutional capacity for sustainable NRM and conservation, access to better information for decision-making, and/or adoption of sustainable NRM and conservation practices.

An area is considered under “improved management” when any one of the following occurs: management actions are implemented; adaptive management is demonstrated; or on-the-ground management impacts are demonstrated.

Reported as total number of hectares improved during the fiscal year in question, which can include maintained improvement in previously reported hectares and/or new, additional hectares.

A subset of this indicator may also be reported as “Number of hectares of natural resources showing improved biophysical conditions as a result of USG assistance” if the latter indicator is used; double counting IS allowed.

Higher=better.

Reported as total number of hectares improved during the fiscal year in question, which can include maintained improvement in previously reported hectares and/or new, additional hectares.  Improved management should be reported for activities where the CSLP project is plausibly linked to the improvements observed.

Indicator Type:          Outcome

Unit of Measure:  Hectares.

Disaggregated by: Biologically significant areas=areas identified as important for biodiversity through national, regional, or global priority-setting processes.  Biodiversity-funded (components of) activities should report on this category regardless of overlap with other categories.

All other areas=areas with natural resources which are outside of biologically significant areas and targeted for management interventions with non-biodiversity funds.  These may include areas characterized by forest production, watersheds, sustainable agriculture areas, areas with tree crop or agroforestry systems.

Justification & Management Utility:  Due to inequity in benefit sharing, ownership and management roles of natural resources, people are not interested in establishing private and/or collective forestry/agroforestry resources. An improved policy and enabling environment is the only sure means to encourage more private resources creation. An increase in the number of hectares of private and/or collective forestry/agroforestry estates indicates attractive enabling environment/policy.

PLAN FOR DATA ACQUISITION BY CSLP

Data collection method: Land area under improved management will be estimated using GPS and estimated in hectares. The CSLP staff and partners will collect this information from any piece of land that is identified for development including all other biological information relevant for LED/REDD+. This data will be stored in hard copies and/or soft copies in CSLP office in Takoradi

Data Source: This data will be gathered by the field staffs of CSLP and partners in the field in collaboration with site owners and community stakeholders. It will involve the use of GPS units, GIS software in spatial planning analysis.

Method of data acquisition by CSLP:  The data will be collected as and when sites are identified and prepared for development. Therefore, every week or day that a site is earmarked following targeted interventions, the data will be taken.

Frequency and timing of data acquisition: The data will be received weekly by CSLP from partner staffs and/or CSLP staff through the specialists.

Estimated cost of data acquisition:  Staff time will be used to collect and analyze data.  Minimal training costs may be incurred to train community members on data collection methods as necessary.

Individual(s) responsible at CSLP:  The Environmental and Spatial Planning Specialist, Assistant Director and M&E Specialist.

Individual(s) responsible for providing data to CSLP:  The Director and the Assistant Director.

Location of Data Storage:  The data will be stored electronically in the CSLP office in Takoradi.

DATA QUALITY ISSUES

Data Quality Assessment:  To be done on periodic basis

Known Data Limitations and Significance (if any):  A potential data quality limitation could be the precision level of the GPS for collecting the data.

Actions Taken or Planned to Address Data Limitations:  Good precision GPS units will be used for the data collection. Staff will be trained in the use of the GPS and in planning to collect data on more favorable cloud free times in the day. 

Procedures for Future Data Quality Assessments:  Data checks will be conducted by sampling sites which are distributed among partners’ sites and areas of jurisdiction. Sample sites will be categorized into small, medium and large sizes and samples will be taken from all 3 categories. 

PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING

Data Analysis:  The raw data will be entered into GIS/Spatial Planning software for analysis. This will be done by CSLP and partners and will be done as and when the data arrives.

Presentation of Data:  The data will be processed into GIS/Spatial Planning maps. This will be done internally by the CSLP and partners.

Review of Data:  The data will be reviewed and analyzed during monthly internal or activity-level reviews with implementing partners.

Reporting of Data:  The data will feature in quarterly and annual reports

OTHER NOTES

Notes on Baselines/Targets: Baseline is zero.

Other Notes:

THIS SHEET LAST UPDATED ON:  05/10/17

 

 

Performance Indicator Reference Sheet - 3

Name of Develop Objective:  To promote low emissions development in Ghana’s Western Region by strengthening community-based natural resource management and monitoring.

Name of Related Output: 1: Increased incomes from livelihood diversification, 2: Improved environment and natural resource management.

Name of Indicator-3:  4.8.1-29  Number of person hours of training in natural resources management and/or biodiversity conservation supported by USG assistance

Is this a USAID Annual Report indicator?  Yes, for all reporting years.

DESCRIPTION

Precise Definition(s):  This indicator uses the following equation to express the number of USG-supported training hours that were completed by training participants: (Hours of USG supported training course X Number of people completing that course).

Support from the USG: This indicator counts training hours that were delivered in full or in part as a result of USG assistance.  This could include provision of funds to pay teachers, providing hosting facilities, or other key contributions necessary to ensure training was delivered.  This indicator does not automatically count any course for which the USG helped develop the curriculum, but rather focuses on delivery of courses that was made possible through full or partial funding from the USG.

People: only people who complete the entire training course are counted for this indicator.

Training: Training is defined as sessions in which participants are educated according to a defined curriculum and set learning objectives.  Sessions that could be informative or educational, such as meetings, but do not have a defined curriculum or learning objectives are not counted as training.  Natural resources and biodiversity is defined as conserving biodiversity and management natural resources in ways that maintain their long-term viability and preserve their potential to meet the needs of present and future generations.

 

Note: Refer to the CSLP guideline on standard curriculum

Indicator Type:          Output

Unit of Measure:  Number of person hours.

Disaggregated by: The data will be disaggregated according to sex (male/female), youth/adult, and district. Involving the youth and women will ensure that natural resources management decisions are embedded amongst the community members so as to incorporate the concerns of all stakeholders.

 Justification & Management Utility:  The development objective seeks to improve capacity of stakeholders in the six districts in low emissions development and these calls for training of individuals and stakeholders in that direction. The more stakeholders and individuals that are trained, the higher the likelihood that low emission development capacity will be sustained in the districts.

PLAN FOR DATA ACQUISITION BY CSLP

Data collection method:  The data will be gathered from participants’ lists in all capacity building/training events within the six districts and even outside the districts at regional and national levels. The data will be collected by the CSLP staff and partners.

Data Source: The data will be from CSLP direct field activities as well as partner field activities that comprise capacity building, training and skill development.

Method of data acquisition by CSLP:  CSLP and partners will plan trainings and other skill development events. Participant lists will be gathered from these events to provide the data for CSLP.   The CSLP team will receive these data through weekly reporting by field staff and monthly reporting by partners.

Frequency and timing of data acquisition: The data will be generated weekly as and when the events occur in the work plans of field staff of CSLP and partners.

Estimated cost of data acquisition:  Staff time will be used to collect and analyze data therefore no additional cost for collection is foreseen. 

Individual(s) responsible at CSLP:  All CSLP staff conducting training.

Individual(s) responsible for providing data to CSLP:  M&E Specialist and Assistant Director.  

Location of Data Storage:  The data will be stored electronically in the CSLP office in Takoradi.

DATA QUALITY ISSUES

Data Quality Assessment:  To be done on periodic basis

Known Data Limitations and Significance (if any):  There could be multiple counting of the same individual(s) for same training.  This could inflate the numbers and create the picture as if more individuals have received training by the project. 

Actions Taken or Planned to Address Data Limitations:  In order to try and mitigate double counting, as much as possible, everyone participating in training will be given a unique identification number.  Participants will be documented with their birth date, household information, family name, etc.  At subsequent trainings, participants with ID numbers will be required to use them as their unique identifier in order to more accurately count the number of people trained.

Procedures for Future Data Quality Assessments:  There will be planned periodic/quarterly visits to communities to identify individuals and interact with them to confirm that they are not being recorded more than once.

PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING

Data Analysis:  The data will be analyzed according to sex (male/female), youth/adult, and district.

Presentation of Data:  The data will be analyzed and presented in table format for reporting purposes and aggregated in narrative reporting. 

Review of Data:  CSLP and partner team will review and analyze the data during internal or activity-level reviews.

Reporting of Data:  The data will be reported in quarterly and annual reporting

OTHER NOTES

Notes on Baselines/Targets: 

Other Notes:

THIS SHEET LAST UPDATED ON:  05/10/17

 

 

 

Performance Indicator Reference Sheet - 4

Name of Develop Objective:  To promote low emissions development in Ghana’s Western Region by strengthening community-based natural resource management and monitoring.

Name of Related Output: 1: Increased incomes from livelihood diversification, 2: Improved environment and natural resource management

Name of Indicator-4:   4.8.1-6 Number of people with increased economic benefits derived from sustainable natural resource management and conservation as a result of USG assistance

Is this a USAID Annual Report indicator?  Yes, for all reporting years.

DESCRIPTION

Precise Definition(s):  Number of people may be a direct count, or it may be determined by multiplying number of households with increased economic benefits by the number of people per household.  Increased economic benefits are increases in economic earnings or consumption due to sustainable management or conservation of natural resources, which can include wages, communal revenues, non-cash benefits, and economic benefits from ecosystem services.

Higher=Better.

Number is specific to each year, not cumulative.

Indicator Type:          Outcome

Unit of Measure:  Number of people.

Disaggregated by: The data will be disaggregated by sex (male/female), age (youth/adult), and district. This is to ensure that all ages are involved but especially that activities implicate women and youth to encourage equity in decision making and benefit sharing.

Justification & Management Utility:  The IR seeks to adopt practices that increase economic benefits to the people of the six coastal districts of the Western Region. This indicator will thus enable the CSLP to track and segregate the number of people by sex, age and district location who are associated with the first two indicators being tracked as a part of CSLP—as an objective means of associating economic benefits with improved management and sequestration or reduction of GHG emissions.   A high number of people benefiting from natural resources management related livelihoods will likely result in sustainable management of the resources and also being climate change conscious.

PLAN FOR DATA ACQUISITION BY CSLP

Data collection method:  There would be data collected on the number of people that adopt and implement any of the livelihood ventures including their direct dependents. They will be segregated into sex and age class and also into district of origin. Structured interviews will be used to determine their direct dependents. The data will be collected by staff of CSLP and partners.  The data will be stored electronically in the CSLP office in Takoradi.

Data Source: The data will be gathered from the field of people implementing livelihood activities through CSLP.

Method of data acquisition by CSLP:  CSLP staff will submit data weekly from the field, while partners will submit data monthly. 

Frequency and timing of data acquisition: The data will be received weekly by the CSLP staff and monthly by partners.

Estimated cost of data acquisition:  Staff time will be used to collect data therefore no additional expenses are anticipated. 

Individual(s) responsible at CSLP:  The M&E Specialist, Assistant Director and the field staff of CSLP will be responsible for collection and receipt of data.

Individual(s) responsible for providing data to CSLP:  The M&E Specialist and Assistant Director

Location of Data Storage:  Data will be stored electronically in the CSLP office in Takoradi.

DATA QUALITY ISSUES

Data Quality Assessment:  To be done on periodic basis

Known Data Limitations and Significance (if any):  A likely limitation could be multiple counting of individuals. If same household is counted more than once, it will result in inflation of the figures and make the data less reliable. As such, beneficiaries will be issued a Unique Identification number in order to avoid double-counting.

Actions Taken or Planned to Address Data Limitations:  The data collection instrument should take more information such as age, location, full names etc. so that likely multiple counting will be identified and rectified.

Procedures for Future Data Quality Assessments:  The data will be assessed through visits to the communities, identifying the people and conducting short interview/discussions with them.

PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING

Data Analysis:  The data will be analyzed and categorized into numbers of people, sex, location (town and/or district), and age. 

Presentation of Data:  The data will be presented in table format and aggregated to be presented in narrative format.

Review of Data:  The CSLP team and partners will review and analyze the data during monthly internal review with implementing partners.

Reporting of Data:  The data will feature in quarterly and annual reports

OTHER NOTES

Notes on Baselines/Targets:  The targets were based on the fact that at least 70 people will be targeted in each of the project intervention communities per year. 

THIS SHEET LAST UPDATED ON:  05/10/17

To avoid version control problems, type the date of most recent revision or update to this reference sheet. 

 

 

 

Performance Indicator Reference Sheet - 5

Name of Develop Objective:  To promote low emissions development in Ghana’s Western Region by strengthening community-based natural resource management and monitoring.

Name of Related Output: 2: Improved environment and natural resource management

Name of Indicator-5:  4.8.2-14 Number of institutions with improved capacity to address climate change issues as a result of USG assistance

Is this a USAID Annual Report indicator?  Yes, for all reporting years.

DESCRIPTION

Precise Definition(s):  Institutions with improved capacity will be better able to govern, coordinate, analyze, advise, or make decisions related to mitigation, adaptation, and improved natural resources management. “Improvement” can be ascertained by evaluating capacity gained as a result of training and other interventions as a result of the CSLP project.  Relevant institutions may include Government of Ghana agencies, private sector entities, communities and community groups (CREMAS, NGOs, farmers’ or fishing associations), and others.

In order to assess capacity, some possible measures of institutional improvement may include:

-Providing input to relevant assessment or planning exercises,

-Increasing the number of certified or technically trained staff,

-Engaging with stakeholders to ensure that policies, plans, budgets and investments reflect local realities and ensure that local communities benefit from climate change efforts and investments,

-Having access to equipment or other inputs necessary for planning, assessment and management of climate change topics, or

-Collaborating with scientists and policymakers, or hosting workshops involving relevant sectors or themes (e.g. agriculture, environment, forestry, energy, and water) to engage with climate change assessments, plans, or activities.

The narrative accompanying this indicator should describe the nature and extent of capacity built, and the institution(s) involved. If a project builds capacity of the same two institutions from one year to the next, the same number should be reported each year

Indicator Type:          Outcome

Unit of Measure:  Number of institutions.

Disaggregated by: N/A

Justification & Management Utility:  Climate Change is a problem of all and requires addressing the root causes. It therefore requires a sustained and long term initiative that cannot be achieved by a short term project such as CSLP. Sustainability can be assured if local institutions, both governmental and non-governmental within the CSLP coverage area, are engaged to participate in the process. The higher the number of local institutions that are brought on board, the higher the chances of sustaining the ideals of the project. It will also ensure a good number of stakeholders speaking to the same voice on climate change impact reduction.

PLAN FOR DATA ACQUISITION BY CSLP

Data collection method:  Planned programs will involve institutions within the catchment area. Participants list will identify the source of participants. Data will be collected by CSLP and partner teams and will include stakeholder interviews to identify how and if institutional capacity has been enhanced.

Data Source: The source of the data will be participants’ lists from project events and events reports in addition to surveys of stakeholders within identified institutions.

Method of data acquisition by CSLP:  The CSLP will receive data from CSLP staff and partners on a monthly basis. 

Frequency and timing of data acquisition: Data will be received monthly from the CSLP and partner field staff.

Estimated cost of data acquisition:  Staff time will be used to collect and analyze data therefore no additional expenses are anticipated. 

Individual(s) responsible at CSLP:  All CSLP staff.

Individual(s) responsible for providing data to CSLP:  M&E Specialist and Assistant Director  

Location of Data Storage:  The data will be stored electronically in the CSLP office in Takoradi.

DATA QUALITY ISSUES

Data Quality Assessment:  To be done on periodic basis

Known Data Limitations and Significance (if any):  N/A

Actions Taken or Planned to Address Data Limitations:  N/A

PLAN FOR DATA ANALYSIS, REVIEW, & REPORTING

Data Analysis:  The data will be analyzed and categorized into number of institutions per district. This analysis will be done by the Assistant Director every month during team monitoring meetings.

Presentation of Data:  The data will be analyzed in tables and categorized into numbers of institutions per district assembly.

Review of Data:  CSLP and the implementing partners will review and analyze the data at monthly internal review meetings.

Reporting of Data:  The data will be presented in quarterly and annual reports

OTHER NOTES

Notes on Baselines/Targets:  The targets were set based on the known existing institutions which are critical to the implementation of CSLP activities such as District Assemblies (6), Traditional Councils (6), Traditional/Town Palaces (at least 30), CREMAs (9), farmer based organizations (at least 9), Western Region EPA, District and Region Forest Services Division (3), Wildlife Division, Western Region Ministry of Food and Agriculture

Other Notes:

THIS SHEET LAST UPDATED ON:  05/10/17