Appendix 2.5.3 Community Participatory Action Research (CPAR) - - PDF document

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Appendix 2.5.3

Community Participatory Action Research (CPAR) Approach of Enrichment Planting with Daemonorops jenkinsiana, Pinus merkusii and Dalbergia cochinchinensis in CF Sites

Guide on Field Data Collection, Data Entry, Analysis and Interpretation and Presentation to the community

1.0 Background As part of the compliance to the TOR, the research proposal will be presented to the FA Staff involved in the study. The presentation will include the concept of the Research, the analysis of the data, and the approach of the research. As part of building the capacity and in preparation for data analysis, spreadsheets are prepared that can be used by the Staff. This guide provides steps on how to complete the forms, encode the data and make the statistical analysis using Multiple Regression and Logit Models. These statistical tools are deemed appropriate in analyzing the factors that influences the growth of the plants. 2.0 Scope of this Guide Scope of this guide:

 Introduce the Field Data Gathering Forms and how to fill up  Orient how to store the information in the prepared spreadsheet  Present the methodology of analyzing factor analysis using multiple regression and Logit

Model analysis using MS Excel and NCSS-PASS softwares.

 Analysis and interpretation of the results (i.e. which factors have significant influence to

the growth and survival of the plants) and deriving conclusion

 Guide on presenting the results to the community

Included in this guide are the dummy Excel files for field data entry and the dummy file for NCSS-PASS for seedling survival analysis. 3.0 Data Collection 3.1 Field Data Collection Using Form 1: Data of Upperstory Plants The study will collect the information of the upperstory plants the main factor being studied that may influence the growth and survival of the planted seedlings. The information of the upperstory plants will be recorded in Form 1. Form 1 will be completed during the layout of the planting spot. The coordinates of each planting spot will be taken and the species name and girth of the 7 upperstory plants that are nearest to the planted seedlings (Figure 1). There will be separate forms for rattan in Ou Saom CF and Tbeng Lech CF, separate form for Pines and separate for Dalbergia. The geographic location per seedlings will be determined using geographic coordinates using WGS 84 datum. Each species will be assigned a code. The girth (or circumference) of the upperstory plants will be taken approximately 1.5 M from the ground. The attached Form shows the hypothetical data of the upperstorey plants. After completing the form, the information will be stored in the prepared worksheet (The entry of the information will be discussed in Section 4).

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1 4 3 6 5 2 7

Planted Seedling Overstory Plants

1 4 3 6 5 2 7

10 x 10 Meter Planting Distance

Figure 1. The 7 upperstory plants that will be measured in each planting spot 3.2 Field Data Collection Using Form 2: Data on Survival and Growth Status of Planted Seedlings

 Form 2 will be completed at the end of the growing period (after 12 months).  At the end of the observation period, the research plot will be visited to:

• Check whether the planted seedlings have survived.
• To measure the height (in cms.) if they survived. If dead, a default value of 0 will be

given.

• check if there are naturally growing rattan (in the rattan lot), Pines (in the Pine plot), or

Dalbergia in the (Dalbergia plots)

 Form 2 shows how the data will be entered.

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Form 1. Data Gathering Form for the Upperstory Plants with Hypothetical Data

Seedling No. Geog. Coordinates (Lat/Long) Trees Nearest to the Planted Seeding

1 2 3 4 5 6 7

1

13 33 10 104 1 12

Species Name

Trameing Trameing Trameing Kreuneung Chromash Kreuneung Kohkoh

• Dist. from

the Plant (M)

1 2.3 4 4.5 4.6 5 6

Girth (cms.)

52 56 120

58

90 67 78

2

13 33 11 104 1 11.8

Species Name

Kohkoh Trameing Kreu Cheutiel Kohkoh Cheutiel Pdeak

• Dist. from

the Plant (M)

2 2.3 3 4.5 5 5.1 5.6

Girth (cms.)

57 120

58

90 67 78 99

3

13 33 11.2 104 1 15

Species Name

Tbeng Kohkoh Kokei Trameing Poupeil Tbeng Kreu

• Dist. from

the Plant (M)

1.5 2.3 3 4.5 5 5.1 7

Girth (cms.)

88 78 52 56 120

58

77

4

13 33 15 104 1 17

Species Name

Trach Poupeil Pdeak Pdeak Kreuneung Trameing Kreu

• Dist. from

the Plant (M)

2.3 3 4.5 5 5.1 6 6.5

Girth (cms.)

78 52 120

58

90 67 120

5

13 33 18 104 1 21

Species Name

Trap Thom Chromash Sra Tbeng Chromash Cheutiel Cheutiel

• Dist. from

the Plant (M)

2 3 3.5 4 4.5 5 6.5

Girth (cms.)

57 89 67 58 55 60 91

6

13 33 20 104 1 22

Species Name

Kokei Ta Trou Pdeak Kohkoh Kokei Kreu Cheutiel

• Dist. from

the Plant (M)

2.3 3 4.5 4.8 5 6.5 7

Girth (cms.)

89 67 58 89 89 67 58

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Form 2. Data Gathering Form for the condition of planted seedlings and with Hypothetical Data

Seedling No. Status:

• 0 = Dead
• Height (cms.) if

Live

• No. of Natural

Seedlings Growing in the Plating Spot Seedling No. Status:

• 0 = Dead
• Height (cms.) if Live
• No. of

Natural Seedlings Growing in the Plating Spot

1 13 16 12 2 12 17 10 3 17 18 11 4 4 15 19 12 5 12 20 15 6 0 (dead) 21 12 1 7 15 22 10 8 12 23 19 2 9 10 24 12 10 19 2 25 20 11 12 26 18 12 27 0 (dead) 13 12 28 11 14 13 29 9 15 0 (dead) 30 16

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4.0 Using Spreadsheets to Process the Collected Data After the forms are filled up, these will be stored in the prepared MS Excel worksheets. The steps of encoding the Worksheet are shown below.

• 1. Open the MS Excel File named: [Research – Data Processing]
• 2. Open the [Species Code] worksheet and Check if all the upperstory species listed in the

forms are found in this file. If not add the other species and assign a code.

• 3. As soon as all the species were coded, open the [Data Entry] Worksheet
• 4. Fill up the columns G, I and J. Note that filling up column H is optional.

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• 5. Open the [Table] Worksheet and store the geographic coordinates of each planted
• seedling. Note that the geographic coordinates are in Lat/Long WGS 84 datum
• 6. Save the file. These will be kept and will be updated when the data on the survival is

available at the end of the growing period.

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• 7. When the data on the status of the planted seedlings are available, open the previously

saved MS Excel File named: [Research – Data Processing]

• 8. Fill up Column B, C, D and E based on the result of the result of the assessment of the

survival, seedling height growth and naturally growing plants. Take note that in these columns, fill up only the WHITE cells. By filling up these cells, all the associated Worksheets (Table, Survival and Height Worksheets) are also completed. These data are now ready for statistical analysis. 5.0 Conducting Statistical Analysis Two statistical software will be used in analyzing the results. MS Excel will be used in conducting multiple regression analysis for height versus the variables Basal Area and

• Density. A special software for statics will be used in analyzing the survival. In this case, we

will use NCSS-PASS (although SPSS can also be used). 5.1 Performing Multiple Regression Analysis Using MS Excel The Multiple Regression analysis will be used to determine the factors that influence the height of the planted seedlings. Be sure the “Data Analysis” Function is installed in the MS Excel File. In some MS Excel version these option needs to be activated. To avoid Multi- colinearity problem, a separate runs will be made on the effects of Basal Areas and Density

• f Upperstory plants on the height of the planted seedlings
• 1. Open the [Height-BA] Worksheet to analyze the effect of Basal Area on the eight of the

seedlings

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• 2. Sort the Height in Descending Order. The purpose is to exclude in the analysis the

“Dead” Seedlings.

• 3. Click “Data” in the Main Menu, Click “Data Analysis” in the Data Submenu and Choose

regression

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• 4. For the “Input Y” button, highlight all the cells in the Height column, and for the “Input X”

button, highlight all the cells of the Column BATot to the last column. Tick the “Label” button. The Cells that contains “0” height should be excluded.

• 5. Tick the Output Button and click at the bottom of the Worksheet to place the result of the

statistical analysis. The Result will be displayed showing the statistical analysis of the regression parameters. Those factors whose coefficients p < 0.05 are considered to be have significant effect on the height of planted seedlings. If the coefficient is ( + ) it means that these factors have a positive relationship with the height and otherwise if ( - ).

• 6. The same process will be done for the [Height-Density] Worksheet.

5.2 Performing the Logit Analysis Using NCSS-PASS The Logit Analysis is appropriate for the Binary Dependent Variable (i.e. Dead or Alive) and to determine the factors that influences its outcome. In this exercise, we will use NCSS although SPSS also have similar function. In preparation to the analysis, install NCSS-PASS software (or SPSS)

• 1. Run NCSS and open the prepared file named [Survival-BA.sav] and [Survival-

Density.sav].

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• 2. Open the MS Excel file containing the [Survival-BA] Worksheet and highlight all the

variables to be analyzed excluding the labels. Note that in the survival column, there are two (binary) data, 1 (alive) and 0 (Dead). Logit will similarly work with regression analysis only that it will have different statistical parameters. This time Wald probability level will be used.

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• 3. After highlighting the variables Copy these and paste to the prepared NCSS file.
• 4. Click Analysis, Regression and Logistic Regression
• 5. In the Variable - Analysis Menu, define the dependent variable (Status) and the

Independent Variables (Basal Area).

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• 6. Run the analysis. The result indicates that among the variables tested, the BA of Species

1 and Species 4 influence the survival of the planted seedlings. The positive sign of the coefficients indicate that the BA favors the survival of the seedlings.

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6.0 Presentation of the Results to the Community, Validation of Research Questions and Formulation of Restoration Plan Following the CPAR approach (Figure 2), the result of the statistical analysis will be validated with the community and to make actions (either to plan for the enrichment planting

• r to conduct another test) from the findings. The session may follow the session guide

below. Figure 2. The Community Participatory Action Research (CPAR) Approach of conducting the study Session Guide Step 1. Explain to the participants the objective of the meeting. Step 2. Present to the communities the objective of the research and the research questions that the study aims to answer. Step 3. Present to the community the following results:

 The effect of the total basal area and density of upperstory plants on the survival and

height of the planted seedlings based on the result of the statistical analysis.

 The influence (presence or absence) of a particular upperstory plants on the survival

and height growth of the planted seedlings based on the result of the statistical analysis.

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Step 4. Validate the result of the data analysis against the local knowledge and observation

• f their communities on the relationship between the seedlings growths/relationships with the

upperstory plants. Step 5. Draw initial conclusion with the community (if the community agrees with the

• bservation) or make a plan to make new hypothesis if the community disagree with the
• results. The conclusion should answer the following questions:

 What would be the stocking (basal area or density) of the upperstory if we will plant

Dalbergia, Pinus and Rattan will be planted underneath its canopy? What would be the extent of thinning to be conducted if we are going to plant the three species?

 What species has to be avoided in enrichment planting Dalbergia, Pinus and Rattan?

Specifically, which areas in the CF will these species will be planted? Step 6. Make a plan. Either the community will conduct further test to verify the result or decide to proceed in planting the species in the CFs.