Making REDD Work For communities& Forests

Linkages between Agriculture and Deforestation: Shadrack Yoash Nyugwa(Agric Offcer)

Introduction

MJUMITA and TFCG are piloting REDD in two sites – Lindi Rural district and in the Rubeho and Ukaguru mountains spanning parts of Kilosa and Mpwapwa districts.

One of the major goals of the pilot project is to help participating communities Improve their livelihood and sell their emissions reductions(Carbon Credits) in the voluntary carbon market.

Year: 2000

Year: 2010

200 hectares cleared: Average 20 ha/yr (3500 tons CO2 per year)

Potential value of REDD: $17,500 per year

Year: 2010

Village decides to start REDD project, but only protects some forests

Year: 2020

200 hectares cleared: Average 20 ha/yr (3500 tons CO2 per year)

REDD payments generated: $0.00

What happened? Deforestation shifted (Leakage)

Year: 2020

Solution? Put all forest into reserves.

Year: 2010

Year: 2020

0 hectares cleared: REDD payments Generated: $17,500

Explaning Lindi Deforestation

● 95% of deforestation in Lindi is caused by agriculture

● Charcoal contributes to deforestation near Lindi town and the highway

● Annual deforestation rates from 2001 to 2012 varied from 2.86% to 1.44%.

● Why are year to year rates of deforestation different?

● What will the future rates of deforestation be?

Lindi Deforestation Model

● All cultivation causes deforestation, but changes in maize cultivation drive changes in deforestation rates

● VNRC members found maize cultivation in 48 of 52 farms cleared from forests between 2010 and 2012

● In surveys, farmers report that mature forest is the prefered location to grow maize due to soil fertility demands

What drives Maize production

● Rainfall (but farmers can't predict the weather) ● Farmers report drought conditions discouraging

maize cultivation in subsequent years and deforestation analysis is in two year periods

● Drought lowers need for new clearings because most nutrients are still in soil, while pests and weeds are fewer

● Labor competition with other crops ● When farmers devote more labor to cash crops

(cashews in paticular) they grow less maize.

Farmer choices

● Farmers choose cash crops or maize depending on economic and environmental conditions

● Periods with the highest deforestation rates, 2001 to 2002 and 2010 to 2012, the only two periods when maize export bans were lifted

● Even switching from maize to sesame could lower deforestation slightly if sesame is more labor intensive than maize on a per area basis.

Measuring Carbon

● To know how much carbon is saved by avoiding deforesation, trees must be measured.

● For the case of our project, VNRC in all villages were trained on carbon assessment methodologies including the use of GPs units which are important tools in carbon assessment

● Randomly placed plots stratified by forest type were used.

How many plots per village?

Approximately 50 plots were placed per village and plan to use a representative subset of the data that accounts for village forest size to calculate project level stocks.

For instance, in Lindi project area, VNRC members worked with the project carbon monitoring officer to measure 12,000 trees in 490 plot accross the project area.

Carbon plots

What methodology was used?

The NAFORMA plot methodology was used, the plots used were 30m diameter plots with smaller concentric plots for measuring different tree DBH classes to reduce the effort required to measure smaller trees.

The Naforma Concentric plot

Data Analysis

Allometric equations used

● The project used equations developed by researchers at Sokoine University to use the tree measurements to determine how much carbon was in the forest

Results, the Lindi scenario

● While there are many forest types in Lindi, in terms of carbon, forests can be broken into low and high carbon forests.

● The results show that, saving

● 1 ha of high carbon forest saves 173.20 tonnes of CO2 equivalent

● 1 ha of low carbon forest saves 115.65 tonnes of CO2 equivalent

Monitoring deforestation?

Deforestation is monitored by the help of satellite images

This is done on a yearly basis

Locations of Spotted deforestation patches whether in the Village Forest Reserve or outside the VFR are uploaded in the GPS units for VNRC to cross check and impose fines

What is recorded by Vnrc?

When VNRC reach at the deforested patch, they record the following information in special forms;

Name of the cleared area, year when it was cleared, reason for clearing the area (farm, settlement, charcoal), size of the cleared plot, what crops were planted, residence of the person who cleared the area, how much he/she harvested, sex and age of people who cleared that area and if there any signs of new clearances

Deforestation maps

At last, deforestation maps showing areas that were cleared in that respective year are produced

These maps together with the amount of forest each village has cleared are presented at the general assembly for all villagers to understand what is happening n their village

Deforestation map

Trial Payment and Performance Based Payment

• Initially, Redd trial payment was done to test the redd payment mechanism model

• The payment was done to all villages participating in Redd

• In this year, villages have been paid after ding some work of reducing deforestation

• This is called Performance based Payment.

• In Lindi, out of 10 villages, 8 villages have qualified and have reduced deforestation for the period of April 2012to April 2013

Performance based payment

• Only two villages (Nandambi and Kinyope) didn’t reduce deforestation, rather they exceeded their baselines and hence they were not paid for this period.

• Another assessment period is from April 2013 to 2014 and villages that will reduce deforestation will be eligible to receive redd payment including those that could not make it during this period

In general....

• Mjumita Tfcg MRV work is done in a participatory way where communities are trained on how to measure carbon and even monitor deforestation happening in their forests by using modern remote sensing technology

• Mjumita assists communities on technical part of MRV (image processing and interpretation) but even communities have important role to play such as ground truthing work

Example from Nandambi Village -Lindi • The village total population is 731

• The trial payment was TZS 49,642,000/=

• The per capita dividend was TZS 67,909/= (their by-laws entitled equal dividends to all including children)

• Decisions of the village assembly were each individual entitled:- – Contribute TZS 25,000/= to the

construction of the village dispensary (Based on the budget presented)

– Contribute TZS 2,909 to facilitate the special committee and VNRC activities (based on their work plan)

– The remaining TZS 40,000/= was distributed to each individual (Women collected dividend for their children and disabled)

Challenges on CSA

adoption(project experience)

• Reliance on rainfall(not reliable) it scare farmers to change to new techniques.

• Availlability of required improved seeds in the villages(fake seeds in local shops)

• high costs of improved seeds Vs small scale farmers incomes.

• districts focusing on irrigation to one crop(only in low lands).

• improper drunkardness(early morning to late night).

• Lack of CSA bylaws to respective villages and sub villages.

Challenge...

• Uncontrolled Livestock keeping (wamasai cattles eating resdues)

• iliteracy.

• Uncontrolled forest fires.

• Lack of village blaws (on markets, fires...).

• Lack of village extension officers.

• Crop middlemens(brokers)

• No use of beam ballances(litters).

• Ability/little participation of veo/Vc in supervision of initiated small

• Politics inteferences in personal/project initiatives.

• Lack of commercial crops(REDD project villages)

• Promise politics(VC,Councilors/MP/presdent), wht will farmers do for themselves?.

Changamoto zaidi.

• Road inaccessibility to villages with forests (Lunenzi, manyomvi, mlenga, mfuluni & idete )

• Lack of enough manures( fear of Masai attack).

• Negative perseption on fertilizer use(soil depletion).

• distortion of techniques or not adopting.

• Input delays to farmers from gvt schemes.

• Lack of Capitals to farmers.

• No taking over budget from District when projects phases out.

• Crop taxes to bicycle carriers.

Recommendations

• Change from rain-fed agriculture reliance.

• Scale up irrigation even to up-hill villages.

• Improve the post harvest practices to small scale farmers.

• Reliable markets/selling centres to ward levels.

• crop-loss insurance

• Proper management of village natural resources.

• Right policy for agriculture and farmers.

• Improve the weather forecasting information and connect it to small scale farmers

recommendations

• Improve and link research to farmers needs(start from farmers)

• Priotise extension services(1/village).

1.Agriculture.

Land rights, 3.Livestocks

The weakness in one aspect affects the success of the rest in the triangle.

CONCLUSION

• Do we know the hub of the problems facing communities that we want to adopt CSA?.

• Are they ready/willing to change?

• To achieve Victory we must Mass

our efforts at the HUB of all Farmers

techincal(science&economical) and

Social(cultural/tradions,taboo

beliefs) problems. The poverty

centre of Gravity.

Agricultural problems never stand alone

• Poverty • iliteracy • selfishness • Negrigence • Self awareness(village leaders+ villagers ) • Bad policy and political will • Corruptions • Laziness and waiting for promisses from leaders(c, mp,

presdents) • Diseases and plaques. • Big gape btn leaders and villagers during implementation of

activities.

REQUIRED KNOWLEDGE IN RURAL AREAS.

• Increase and improve self understanding so that farmers do not get satisfied with poor life standards.

• improved agriculture(CSA) and vocational trainings

• To better understand their social sorrounding environments and their responsibilty to thier nation.

• To forsake/remove (gossips, lies, hate, laziness (work & thinking)