Livestock Research for Rural Development 29 (10) 2017 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Leguminous fodder trees as protein source and carbon sink in smallholder dairy production systems in Muheza District, Tanga Region, Tanzania

W E Mangesho, L R Kurwijila1 and D D Shirima2

Tanzania Livestock Research Institute (TALIRI) -Tanga, Box 5016, Tanga, Tanzania
wmangesho81@gmail.com
1 Sokoine University of Agriculture, Department of Animal, Aquaculture and Range Sciences, Box 3004, Morogoro Tanzania.
2 Sokoine University of Agriculture, Department of Ecosystem and Conservation, Box 3010, Morogoro Tanzania.

Abstract

This study was carried out to investigate the potential and role of leguminous fodder trees Leucaena leucocephala (LL) and Gliricidia sepium (GS) under small scale dairy production system and their carbon storage potentials. Structured questionnaires were used in data collection and a total of 120 farmers in 3 zones of Muheza district were included in the study. Above ground biomass was calculated from different tree components (stem and branches) in t ha -1, 29% of stem biomass was taken as biomass of branches. Carbon storage was calculated as 49% of the total tree species biomass. Data from the survey and biological data were analyzed using SPSS and SAS statistical software, respectively.

Only 46.7% respondents do allocate land for fodder trees equivalent to 0.05 – 3.4% of their farm land. About 32.5% of them cultivated LL alone and 7% cultivated GS while 11% cultivated both species. Size of the farm land influenced (P>0.05) area allocated for fodder production. Generally, (81.7%) of the farmers were using leaf meal (LM) to feed their dairy cows. About 71% and 5% of the respondents used Leucaena leaf meal (LLM) and Gliricidia leaf meal (GLM), respectively, while 3.3% used both LLM and GLM. The use of LM differed between the target zones and the protein supply potential from LLM was 250g CP/kg DM. Carbon density (CD) of LL was estimated to be 5.06 t onnes C ha-1 at 16169 trees per ha, whereas GS had 10.24 tonnes C ha-1 at 1334 tree density per ha which is equivalent to emissions from 3 and 5 cattle, respectively. Hence one cow requires 0.3 and 0.2 ha or 5390 and 269 trees of LL and GS to be carbon emission neutral. The CD for both species differed between zones. Carbon stock above the ground in the two species were sufficient and therefore planting at 6000 and 1000 trees of LL and GS respectively per cow can save as a mitigation option for offsetting CO2 emissions to the atmosphere.

Key words: carbon density, emission, fodder production, leaf meals


Introduction

Dairy development in the tropics is generally directed towards the smallholder sector (Walshe 1993), with major constraints being the scarcity and poor quality of on-farm feed resources and the uncertain supply of purchased concentrates (Lanyasunya et al 2001, Mapiye et al 2006, Urassa 1999, Teendwa 2005, Kivaria et al 2006). In Tanga region, dairy production is one of the major economic activities (MDC, 2008), but is constrained by lack of quality and quantity supply of forages especially during dry season (Kavana et al 2005). Underfeeding in basal diet and supplementary feeds has created protein deficit leading to reduction in milk production, also inconsistent feeding plans contributes to low milk productivity (Urassa 1999). Protein supplements have been indicated as one of the most limiting nutrients for dairy cattle during the dry season (Kavana et al 2005). This is due to the inherent low crude protein content of tropical grasses that are used as the basal diet. Multipurpose trees and shrubs (MPTS) constitutes a rich and critical source of supplementary fodder and protein in the diet of ruminants especially during the dry season (Phiri et al 2000). Therefore, leguminous fodder trees such as Leucaena leucocephala, Gliricidia sepium or other herbaceous legumes are known to be crucial supplement for dry season feeding (Kavana et al 2005). These legumes, apart from being a good protein source, they also act as a carbon sinks hence reducing CO2 emitted in the atmosphere through carbon sequestration (CS). One of the major challenges of the 21st century is the mitigation and adaptation to climate change (FAO 2004). The concern about climate change is that it is caused by anthropogenic emission (FAO 2004, Kirby and Potvin 2007) but at the same time, it will have significant negative impacts on livestock production systems (Thornton et al 2009). However, livestock including dairy cattle contributes largely to climate change problem (IPCC 2007), they contribute an estimates of 18% of global anthropogenic GHG emissions (Steinfeld 2006). The main sources and types of GHGs from livestock systems are CO2 from land use and its changes (feed production, deforestation), which accounts for 32% of emissions from livestock; nitrous oxide (N2O) from manure and slurry management, which accounts for 31%; and methane (CH4) production from ruminants, which accounts for 25% of emissions (Steinfeld 2006). Mitigation efforts for reducing concentration of CO2 emissions in the atmosphere include embanking on tree afforestation/reforestation programs as trees have proven to have high carbon sequester potentials (Vesterdal et al 2002; FAO 2004). Dairy farmers can contribute to mitigation of the potential negative impact of dairy animals on GHGs emissions through planting of fodder trees. Leguminous fodder trees such as L. leucocephala and G. sepium have been planted by farmers in Tanga region in their Agroforestry systems and used as animal supplement especially during the dry seasons (Urassa 1999). They are known to be high biomass producers, however, in spite of their high rated growth, less is known on their potential mitigation to climate through carbon emissions.

Over 200 000 smallholder farmers plant fodder trees in East Africa mainly to supplement the protein requirements of dairy cows, Franzel et al (2014). The average protein requirement of a crossbred cow with 400 kg live weight is said to be 640 g/day depending on production level, Van Tol (2004). By knowing the CP in basal diet, the CP present in leaves to be supplemented and the daily CP requirement by a particular cow, the amount of fodder to be supplemented can easily be calculated. In addition, when the expected leaves production per tree per annum is known, the number of fodder trees to be planted in a farm can also be calculated. Assuming a crossbred cow weighing 400 kg live weight required to be supplemented with 4kg concentrate with 16 % CP = 640 g CP daily. The amount of fresh L. leucocephala leaves 25%DM (50 g CP /kg) to be fed per day instead of buying dairy meal is therefore 12.8 kg. It is however, important to be cautious on the inclusion level in the diet i.e. for L. leucocephala it should not be beyond 30% of the ration. From the example above, the number of L. leucocephala trees to be planted per year can be calculated. Assuming an annual fresh leaf yield of 4.5 kg per tree, the amount of fresh leaves which is required during a whole year is the product of the amount needed for one day and the total number of days (365). The product is then divided by annual fresh leaf production per tree to get the number of trees to be planted at the farm to feed that particular cow in a year. In this case, the total number of trees is 1039. Since there is limited acreage of most farms in the study area, it is best to integrate fodder trees into the existing cropping system, rather than planting them in pure-stand (mono-culture) fodder banks. Van Tol (2004) recommended a spacing of a double zigzag line of 30x30 cm in planting L. leucocephala. Such spacing can accommodate about 111 111 trees/ha with no other crops or trees. Conversely, non-specific spacing of L. leucocephala was observed in the study area with the average number of 16169 trees /ha. Densities of 75 000 – 140 000 trees/ha was reported by NAS (1984) with a recommended row spacing of 75 cm. Closer spacing maximizes fodder production, but may make access for harvest or grazing difficult. Spacing of 1x1 meter is common for many species (Devendra 1990).

This study aimed at evaluating the potential synergistic role of leguminous fodder trees as carbon sink and feed for dairy cattle in mixed crop-livestock systems. The specific objectives were to: (i) assess the extent of current use and potential of leguminous fodder trees ( L. leucocephala and G. sepium) as protein supplement to cows in Muheza district, (ii) assess the potential GHGs mitigation effect of leguminous trees in mixed crop livestock systems, and (iii) determine the potential of leguminous trees in carbon storage in mixed crop livestock system in Muheza district.


Methodology

Study area

The study was carried out in Muheza district, which is located Southwest to Tanga City, in Tanga region, Tanzania.

Data collection

Assessing the current use and potential of leguminous fodder trees as protein supplement to cows

Stratified random sampling was done in 3 zones based on altitude. The highland, midland and coastal zone elevated at 500-1200, 200-500 and < 200 m.a.s.l., respectively. Structured questionnaires were used to interview 120 households who were randomly selected from 12 villages in 6 wards.

Determination of the carbon storage potential of leguminous trees

Size of the farms with either or both of the two species was recorded and sample plots of circular radius 11.3m were selected on each farm. Diameter at breast height (DBH) and height of trees were measured using tape measure and Sunto-Hypsometer respectively (Matthews and Mackie 2006). Measurements were taken to 192 trees of L.leucocephala 162 trees of G. sepium from each zone. Information like rainfall pattern and temperature, soil type, were obtained from the secondary sources in district profile and Mlingano meteorological station.

Measurements of tree parameters
Tree Basal Area (BA)

BA (m2/ha) = (π (dbh2)/4)/10,000. Where π = 3.14; dbh = diameter at breast height (cm). Volume (V) was obtained by using the following formula: Vi = 0.5g hi. Where Vi = the volume of the ith tree (m3); hi = the total height of the i th tree (m); g = the tree basal area (m2); 0.5 = tree form factor as indicated in the formula (Haule and Munyuku, 1994).

Biomass production, Expansion Factors and Wood Density

Biomass production was calculated as: Biomass density (t/ha) = VOB x WD x BEF. Where: VOB = Volume Over Bark; WD = Wood Density; BEF = Biomass Expansion Factor

A biomass Expansion Factors (BEF) of 0.49 was used (Löwe et al 2000). The wood densities were taken as 820 and 750kg/m3 for L. leucocephala and G. sepium, respectively at 12% moisture content (Ngulube 1994) and multiplied by a factor of 0.872 to get wood specific gravity (Chave et al 2005). Therefore, wood specific gravity of 715 and 654 was used to convert the tree volume into biomass estimate (Aboal et al 2005).

The total above ground biomass was calculated from different tree components (stem and branches), 29% of stem biomass was taken as biomass of branches (Montes et al 2000, Ketterings et al 2001).

Carbon storage and Protein content

Carbon storage was taken as 49% of the total tree species biomass (Kirby and Potvin 2007, Laclau 2003), and the protein content per unit biomass of the two species was obtained from different literatures (Doto et al 2004a). The abbreviation "t C" = "tonnes carbon".

Data analysis

Data for assessing current use, extent and potential of leguminous fodder trees as protein supplement to cows were analyzed by using statistical package for social science (SPSS 2007) 16.2 version. The frequencies, percentages and Analysis of variance (ANOVA) were determined on; social and demographic characteristics of the households, farm size and allocation pattern, and yield and utilization pattern. The extent of use of fodder trees was compared between zones. Biomass data were analyzed using Statistical Analytical System - (SAS 2004). ANOVA was also performed on the effect of specie and zone and on biomass and carbon density. The abbreviation "t C" = "tonnes carbon".


Results and discussion

Socio-economic and demographic characteristics of head of household

The main socio-economic and demographic characteristics indicated that, 73.3% of the households were male headed and only 26.7% were female headed (Table 1). The results are more or less the same as those by Ngaga et al (2007) and (NBS 2002). Most of these head of households (52.5%) were between 41 - 60 years old (Table 1). The results suggest potential availability of labour in the area for activities such as fodder harvesting. Age also influences experiences, wealth and decision making powers, all of which have effect on the working capability of an individual and therefore individual productivity. According to Nkurlu (2002), the age of a person is usually a factor explaining the level of production and efficiency.

Table 1. General characteristics of the interviewed households

Characteristic of the respondent

Percentage (%)

Frequency

Gender

Male

88

73.3

Female

32

26.7

Age (years)

20 – 40

44

35.8

41 – 60

63

52.5

>60

4

11.7

Education level

Primary

107

89.2

Secondary

9

7.5

Diploma

4

3.3

Farm size and land allocation pattern

Most of the households (89.1%) own 0.1 – 2 ha of land farm and majority of them (53.3%) does not allocate their farms to fodder trees production (Table 2). This is due to land scarcity and the fact that L. leucocephala can be widely found in the communal land. Similar results were reported by Lukuyu (2016) i.e. majority of small-scale dairy producers allocate less than five acres of land for fodder production.

Table 2. Farm size and farmers allocation of land to fodder production

Zone

Farm size (ha)

Land allocation for
fodder production

0.1 – 2

2.1 – 4

> 4

Highland (n=40)

36 (90)

3 (7.5)

1 (2.5)

15 (37.5)

Midland (n=40)

36 (90)

3 (7.5)

1 (2.5)

29 (72.5)

Coastal (n=40)

35 (87.5)

5(12.5)

0 (0)

13 (32.7)

Overall (n=120)

107 (89.2)

11 (9.2)

2 (1.7)

57 (47.5)

NB: Figures in bracket indicate percentage

Frequency of farmers who have cultivated L. leucocephala alone was higher (32.5%) than 5.8% who cultivated G. Sepium alone (Figure 1) and there were no significant effect (P>0.05) on farmer’s level of education to the area under fodder production. High significant effect was observed (P<0.05) on size of the farm to the area of fodder cultivation. Study by Franzel et al (2014) indicates that fodder trees production requires little land, labor or capital but are knowledge-intensive. Moreover, women involvement in fodder tree production in East Africa was said to be about 40–50%.

Figure 1. Type of fodder tree cultivated by farmers in the different zones
Yield and utilization pattern

Leucaena leaf meal (LLM) was highly used by respondents (71.1%) while 5% used Gliricidia leaf meal (GLM) and only 3.3% used both LLM and GLM. Generally, majority of respondents (81.7%) use leaf meal to feed their dairy cows. In the coastal zone 95% use leaf meal compared to 85% and 65% in Midland and highland zones respectively. The results are higher than that by Franzel et al (2007) who reported 61% of farmers in Tanga to use leaf meal. This could be due to the difference in total coverage of the area of study. On the other hand, there might be an increase in adoption rate of farmers on the use of leaf meals although some farmers (65.8%) complained on lack of enough knowledge on the importance of the fodder trees to dairy cows. Example, most farmers especially in the highland zone cultivated G. sepium as a supportive tree for black pepper (Piper nigrum)and not as fodder to cows.

About 36% of the respondents use LLM at an average amount between 0.25-0.5kg per lactating cow per day. This amount is somehow the same as that of 0.52 and 0.58kg per lactating cow per day as reported by Franzel et al (2007). Forty four percent of farmer uses the ratio of maize bran and LLM at 2:1 while 16.2% uses 3:1 ratio (Figure 6). The recommended ratio by (MoA 2003) is 3:1, however, Livestock Extenstionists in Muheza recommends farmers to use the ratio of 3:2 due to high availability and lower price of the product in the area. An increase of milk production of 1-2 litres per day was experienced by 74.2 % of the respondents when continuously using the leaf meal. The same increase was reported in the study results by Franzel et al (2007). The two fodder trees will at least in the near future continue to be cheaper sources of supplementary protein to dairy cows and much more benefits on their uses will depend on how best the farmers are aware on their management and use.

Figure 2. Mixing ratios of MB and LLM in the study area
Species leaf biomass production

The estimated average production of fresh leaf per tree per annum was 6.5±1.4 kg and 7.3±1.3 kg for L. leucocephala and G. sepium, respectively. Unlikely, Van Tol (2004) estimated an annual fresh yield ranging from 1.8-4.8 kg and 1.5-2.5 kg per tree for L. leucocephala and G. sepium, respectively. The difference could be due to the effect of age and height at which the estimates were done. The average age and height in this study were 3.5 years and 7m, respectively, contrary to tree age of 1year and height of 0.5m used in the study by Van Tol (2004).

Diameter distribution and basal area

The mean diameter of L. leucocephala and G. sepium was 7.27 ± 2.56 and 11.4 ± 1.79 cm, respectively and the mean basal area of the two species was 2.04 ± 1.69 m2 ha-1 for L. leucocephala and 4.20 ± 1.30 m2 ha-1 for G. sepium (Table 3).

Table 3. Means of various tree parameters in the study area

L. leucocephala

G. sepium

Parameter

Highland

Midland

Coastal

Overall

Highland

Midland

Coastal

Overall

DBH (cm)

6.0(2.2)

7.5(3.1)

8.3(1.8)

7.7(2.6)

11.0(1.8)

11.9(1.6)

11.3(1.9)

11.4 (1.8)

Age (yrs)

4.1(1.2)

4.2(1.4)

5.0(1.2)

4.4(1.3)

4.9(1.0)

5.9(1.0)

4.1(1.5)

5.0 (1.4)

BA (m2ha-1)

1.3(0.9)

2.2(1.7)

2.6(2.0)

2.0(1.7)

3.9(1.2)

4.5(1.3)

4.2(1.4)

4.2 (1.3)

Vol. (m3)

6.2(5.2)

12.0(11.3)

15.4(13.8)

11.2(11.3)

22.8(8.3)

7.3(8.8)

24.3(9.0)

24.8 (8.8)

BD (t ha-1)

5.7(4.8)

11.1(10.4)

14.2(12.7)

10.3(10.5)

19.2(7.0)

23.0(7.5)

20.5(7.6)

20.9 (7.5)

CD (t C ha-1)

2.8(2.4)

5.4(5.1)

7.0(6.2)

5.1(5.1)

9.4(3.4)

11.3(3.7)

10.0(3.7)

10.2(3.7)

NB: Figures in brackets indicate standard deviation; DBH= diameter at breast height, BA= basal area, Vol. = volume, BD= biomass density and CD= carbon density.

Comparison between diameter size class and basal area show that there was high basal area per hectare in higher diameter size class (> 12 cm) and low basal area per hectare in the lower diameter size class for both species (Table 4). The basal area is a good predictor for biomass and carbon since it integrates the effect of both the number and size of trees. A correlation between these variables is to be expected since the basal area and biomass are both related to the trunk diameter (Simons and Stewart 1994).

Carbon stocks by DBH size classes

The carbon density  for both species was found to be greater in the high diameter size class, whereas it was lower in the least diameter size class for L. leucocephala. There were no observations in class range 0-4cm in G. sepium, and the lowest carbon density was found in the diameter size class of 4.1-8cm (Table 4). 

Table 4. Means of observed parameters under DBH classes for L. leucocephala and G. Sepium

DBH Class

DBH
(cm)

Age
(yrs)

BA
(m2ha-1)

Vol.
(m3)

BD
(t ha-1)

CD
(t C ha-1)

L. leucocephala

0-4

3.4(0.4)

2.7(0.6)

0.4(0.1)

1.3(0.4)

1.5(0.4)

0.6(0.2)

4.1-8

6.4(1.2)

4.5(1.2)

1.9(1.8)

10.0(11.3)

10.0(11.3)

10.0(11.3)

8.1-12

9.7(1.0)

4.0(1.1)

2.8(1.2)

16.1(9.9)

4.9(9.1)

7.3(4.5)

>12

12.8(0.6)

6.7(0.5)

4.1(2.1)

24.6(14.5)

22.7(13.3)

11.1(6.5)

G. sepium

0-4

0.0

0.0

0.0

0.0

0.0

0.0

4.1-8

7.7(0.4)

3.6(0.1)

1.9(0.2)

9.5(0.7)

8.0(0.6)

3.9(0.3)

8.1-12

10.4(0.97)

4.8(1.4)

3.5(0.6)

19.9(4.5)

16.8(3.8)

8.2(1.9)

>12

13.4(0.8)

5.3(1.4)

5.6(0.7)

34.2(5.7)

28.8(4.8)

14.1(2.4)

NB: Figures in brackets indicate standard deviation; DBH= diameter at breast height, BA= basal area, Vol. = volume, BD= biomass density and CD= carbon density

The basal area for different zones for L. leucocephala was comparable to a study by Colòn and Lugo (2006) who reported the basal area for this species in farmland to be 1.84m2 ha-1. On the other hand, the basal area of G. sepium was higher compared to that of L. leucocephala studied in the same zones. This may be attributed to disturbance to L. Leucocephala due to selective harvesting as L. leucocephala is harvested more than G. sepium. It may also due to the differences of DBH measurements of the two species.

Age versus carbon density

From the study results shown in Table 5, G. sepium had higher carbon density at above five years compared to L. leucocephala at the same age. Those results may be due to higher tree volumes in G. sepium which had 27.43±9.74 m3ha-1, contrary to L. leucocephala with 17.46±14.62 m3 ha -1 at corresponding ages. The variation of carbon density values with age is comparable with the study by Renezita et al (2004) who found the carbon density values of various trees to vary with age, type of species, site conditions and silvicultural treatments applied in the stand. 

Biomass and Carbon density

The overall mean BD was 10.33 ± 10.45 and 20.89±7.46 for L. leucocephala and G. sepium, respectively (Table 3). Also, results shows that at above five years old L. leucocephala had mean volume of 17.46± 14.62 m3 ha -1 and mean biomass of 16.11± 13.48 t ha-1. On the other hand, G. sepium at above six years old had a mean volume of 27.4± 9.74 m3 ha-1 and mean aboveground biomass of 23.14± 8.22 t ha-1(Table 5).

Table 5. Means (±) of observed parameters under age classes for L. leucocephala and G. Sepium

L. leucocephala

G. sepium

Age Classes(yrs)

0-2.5

2.6-5

>5

0-3

3.1-6

>6

Parameters

DBH (cm)

3.5(0.4)

7.2(2.4)

8.5(2.0)

10.7(1.9)

11.5(1.7)

12.1(1.9)

BA (m2ha-1)

0.4(0.1)

1.8(1.3)

3.0(2.1)

3.7(1.3)

4.2(1.2)

4.7(1.5)

Vol. (m3)

1.4(0.4)

9.4(8.1)

17.5(14.6)

21.7(8.9)

24.9(8.3)

27.4(9.7)

BD (t ha-1)

1.3(0.4)

8.7(7.5)

16.1(13.5)

18.3(7.5)

21.1(7.0)

23.1(8.2)

CD (t C ha-1)

0.6(0.2)

4.2(3.7)

7.8(6.6)

9.0(3.7)

10.3(3.4)

11.3(4.0)

NB: Figures in brackets indicate standard deviation; DBH= diameter at breast height, BA= basal area, Vol. = volume, BD= biomass density and CD= carbon density.

Higher results of aboveground biomass were observed the study of the use of these two species in alley cropping systems to improve Brazilian coastal tableland soils i.e. 4.87 and 5.80 ton ha-1 year -1 for L. leucocephala and G. sepium, respectively (Barreto and Fernandes 2001).

The mean CD value was 5.06 ± 5.12 and 10.24 ± 3.66) tonnes C ha-1 for L. leucocephala and G. sepium, respectively (Table 3). Analysis revealed high significant levels (P<0.05) in CD in all zones for both species (Table 6). Generally, the biomass obtained in the study was within the biomass production figures of 2 to 20 t ha-1 for L. leucocephala and 2–10 t ha-1 for G. sepium (NAS 1984). This observation suggests that the two species have high carbon sink potential to mitigate carbon emissions. The different mean values obtained in different zones from both species may be caused by zone variations in climatic factors, edaphic factors and management regimes. It has been argued that carbon stock in trees is influenced by climate, especially precipitation and temperature, also by soil and physiographic factors (Williams et al 2009). Moreover, carbon storage was dependent on the amount of biomass of trees, specifically, on the variables trunk diameter and total height (Table 3). This conforms to the findings by Terakunpisut et al (2007) who mentioned the carbon storage potential in the different trees tends to be correlated to DBH and tree height. If one cow produces 100kg of methane or the equivalent of 2,300kg CO2 per year [http://timeforchange.org/are-cows-cause-of-global-warming-meat-methane-CO2], with 506 cattle in the study area, the emission is about 1164 tonnes of CO2-equivalents per year. Therefore, in relating the carbon stock results with the emissions from cattle, it was found that the mean carbon stocks of 5.06 t C ha-1 from L. leucocephala is equivalent to emission from 3 cattle and that of 10.2 t C ha-1 from G. sepium is equivalent to emission from 5 cattle. The zero carbon footprint threshold for both species per cow is suggested to be 0.3 and 0.2 ha or 5390 and 269 trees of L. leucocephala and G. sepium, respectively.

Table 6. Effect of elevation (zones) on biomass density and carbon density of L. leucocephala and G. sepium

Specie

L. leucocephala

G. sepium

Parameter

BD (t ha-1)

CD (t C ha-1)

BD (t ha-1)

CD (t C ha-1)

Zone

Highland

12.47 ± 0.34c

6.11 ± 0.16c

20.82 ± 0.41c

10.20 ± 0.20c

Midland

12.58 ± 0.26b

6.16 ± 0.13b

21.32 ± 0.40a

10.45 ± 0.20a

Coastal

13.04 ± 0.32a

6.39 ± 0.16a

20.17 ± 0.50b

9.88 ± 0.24b

P-value

<0.001

<0.001

<0.001

<0.001

abcMeans with the different superscript in a column are different at (P<0.05)
BD= biomass density and CD= carbon density


Conclusions


Acknowledgements

The authors acknowledge Sokoine University of Agriculture (SUA) diligent supervision of this work. We thank farmers who spared their valuable time and participate fully in data collection without which this work would not have been possible. The assistance by Extension Offices in farmers selection and data collection is highly is appreciated. Sincere thanks are also due to the Government of Tanzania, Ministry of Livestock and Fisheries Development through ASDP for financing this work.


References

Aboal J R, Arevalo J R and Fernandez A 2005 Allometric relationships of different tree species and stand above ground biomass in the Gomera laurel forest Canary Islands. Flora-Morphology, Distribution, Functional Ecology of Plants Journal 200(3): 264 – 274.

Barreto A C and Fernandes M F 2001 Use of Gliricidia sepium and Leucaena leucocephala in alley cropping systems to improve Brazilian coastal tableland soils. Pesq. agropec. bras.Journal 36(10): 1287-1293. http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2001001000011

Chave J, Andalo C, Brown S, Cairns M A, Chambers J Q, Eamus D and Fölster H 2005 Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145: 87 – 99.

Colòn S M and Lugo A E 2006 Recovery of a Subtropical Dry Forest After Abandonment of Different Land  Uses. Biotropica Journal 38(3): 354–364.

Devendra C 1990 Shrubs and Tree Fodders for Farm Animals. International Development Research Centre. Ottawa, Ontario, Canada. 349pp.

Doto S P, Kimambo A E, Mgheni D M, Mtenga L A, Laswai G H, Kurwijila L R, Pereka A E and Kombe R A 2004a Tanzania Feedstuff Table for Ruminants. ENRECA (SUA-MU/RVAU-DIAS) and ASLIP project. Morogoro, Tanzania. 71pp.

Doto S P, Weisbjerg M R, Hvelplund T, Kimambo A E, Mgheni D M, Mtenga L A, Laswai G H, Madsen J and Petersen P H 2004b The Tanzania feedstuff table for ruminants. Proceedings of the 31st Scientific Conference of Tanzanian Society of Animal Production 31: 46 – 50.

FAO 2004 Low Greenhouse Gas Agriculture: Mitigation and Adaptation Potential of Sustainable Farming Systems. [www.fao.org/organicag] site visited on 14/6/2011.

Franzel S, Carsan S, Lukuyu B, Sinja J and Wambungu C 2014 Fodder trees for improving livestock productivity and smallholder livelihoods in Africa. Elsevier Journal 6: 98–103.

Franzel S, Wambungu C, Nanok T, Kavana P, Njau T, Aithal A, Muriuki J and Kitalyi A 2007 The production and marketing of leaf meal from fodder shrub in Tanga, Tanzania: A pro-poor enterprise for improving livestock productivity. ICRAF Working paper No. 50. World Agroforestry Centre, Nairobi. 24pp.

Haule E F and Mnyuku F C 1994 National Forest Inventory in Tanzania. In: Proceedings of the workshop on Information Acquisition for Sustainable Natural Forest Resource of Eastern, Central and Southern Africa. (Edited by Malimbwi R. E. and Luoga E. J.), Faculty of Forestry, SUA, Morogoro, Tanzania. pp. 99 -113.

IPCC 2007 Intergovernmental Panel on Climate Change Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Edited by Solomon, S. et al.), Cambridge University Press, Cambridge, and New York. 996pp.

Kavana P Y, Mtunda K, Abass A and Rweyendera V 2005 Promotion of cassava leaves silage utilization for smallholder dairy production in Eastern coast of Tanzania. Livestock Research for Rural Development Journal 17(4): 1- 9.

Ketterings Q M, Coe R, Noordwijk van M, Ambagau Y and Palm C A 2001 Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. Journal of Forest Ecology and Management 146: 199 – 209.

Kirby K R and Potvin C 2007 Variation in carbon storage among tree species: implications for the management of a small-scale carbon sink project. Forest Ecology and Management Journal 246: 208 – 221.

Kivaria F M, Noodhuizen J P T M and Kapaga A M 2006 Prospects and constraints of smallholder dairy husbandry in Dar es Salaam Region, Tanzania. Journal of Outlook on Agriculture 35(3): 209 – 215.

Laclau P 2003 Biomass and carbon sequestration of ponderosa pine plantations and native cypress forests in northwest Patagonia. Forest Ecology and Management Journal 180: 317 – 333.

Lanyasunya T P, Mukisira E A, Lokwaleput I K and Siamba D N 2001 Factors limiting optimization of smallholder peri-urban dairy herd production in Kenya. In: Proceedings of the 10th Conference of the Association of Institutions for Tropical Veterinary Medicine : Livestock community and development. 20 – 23 August 2001, Copenhagen, Denmark. 50 – 58pp.

Löwe H, Seufert G and Raes F 2000 Comparison of methods used within Member States for estimating CO2 emissions and sinks according to UNFCCC and EU Monitoring Mechanism: forest and other wooded land. Biotechnol. Agron. Soc. Environ. Journal 4(4): 315–319.

Lukuyu M, Njehu A, Mwilawa A, Lukuyu B, Omore A and Rao J 2016 A study to understand fodder markets and fodder trading patterns in MoreMilkiT sites and other selected regions in Tanzania. ( https://cgspace.cgiar.org/bitstream/handle/10568/77282/tanzania_fodder_aug2016.pdf?sequence=1 ) Site visited on 4/5/2017.

Mapiye C, Foti R, Chikumba N, Poshiwa X, Mwale M, Chivuraise C and Mupangwa J 2006 Constraints to adoption of forage and browse legumes by smallholder dairy farmers in Zimbabwe. Livestock Research for Rural Development Journal 18(12): 1-13.

Matthews R W and Mackie E D 2006 Forest Mensuration: A handbook for Practitioners. Forest Commission, Edinburg, U.K. 330pp.

MDC 2008 Muheza District Council. District Profile report, Muheza, Tanga. 57pp.

MoA 2003 Ministry of Agriculture. Farming Systems Zonation of Tanzania. Dar es Salaam. 98pp.

Montes N, Gauquelin T, Badri W, Bertaudiere V and Zaoui E H 2000 A non- destructive method for estimating above - ground forest biomass in threatened woodlands. Forest Ecology and Management 130(3): 37 – 46.

NAS 1984 National Academy of Science Leucaena: Promising Forage and Tree crop for the Tropics. Innovations in Tropical Reforestation; Second Edition, National Academy Press, Washington D.C. 100pp.

NBS 2002 National Bureau of Statistics. Tanzania Population and Housing Census. Ministry of Planning, Economy and Empowerment, Dar es Salaam, Tanzania. 51pp.

Ngaga Y M, Mvena Z S K, Rweyamamu C O, Maerere K P, Ndyetabula I L, Kagombola R K and Moshi S S 2007 Socio-economics characteristics of households and current status of growing vanilla in Bukoba District and Kilimanjaro region Tanzania. In: Transforming livelihoods of small scale farmers. Contribution of Agricultural and Natural Resources research. (Edited by Kinabo, L.D.B. and Abel, W.S.). Proceedings of the 1 st Annual PANTIL research workshop held in Morogoro, 25 – 27 September, 2006. pp. 56 – 63.

Ngulube M R 1994 Evaluation of Gliricidia sepium provenances for alley cropping in Malawi. Forest Ecology and Management Journal 64(3): 191-198.

Nkurlu R L 2000 The role of women’s income generating activities in household food security in the Urban Poor: The Case of Temeke District, Dar es Salaam. Dissertation for Award of MSc Degree at Sokoine University of Agriculture, Morogoro, Tanzania, 107pp.

Phiri G Y K, Msiska H D C, Dzowela B H, Ngwira W M M, Njewa M J and Kalanje L L 2000 Fodder yield and nutritive value of leucaena, acacia and calliandra at three cutting regimes and two locations in Malawi. In: Proceedings of the regional conference Malawi, (Edited by: Banda J.W. et al.), 30 October - 1 November 2000. Institute of Management, Lilongwe, Malawi. pp. 1 – 14.

Renezita F S, Rodel D L and Banaticla R N 2004 Carbon Storage and Sequestration Potential of Smallholder Tree Farms on Leyte Island. University of The Philippines Los Banos, College, Laguna. 141pp.

SAS 2004 Statistical Analysis System. SAS/STAT user guide. Statistical Analysis Institute, Inc, Cary. NC. USA. 1028pp.

Simons A and Stewart J 1994 Gliricidia sepium - a Multipurpose Forage Tree Legume [http://www.fao.org/ag/agp/agpc/doc/publicat/gutt-shel/x5556e07.htm] site visited on 23/02/2017.

SPSS 2007 Statistical Package for Social Sciences User’s manual. Chicago SPSS inc. Chicago. 527pp.

Steinfeld H 2006 Livestock’s Long Shadow: Environmental Issues and Options. Food and Agriculture Organization, Rome, Italy. 46pp.

Teendwa A A P 2005 Assessment of dairy production in Tanga region. Farmers awareness and adoption of the available technology for improving feed quality. Dissertation for Award of MSc Degree at Sokoine University of Agriculture, Morogoro, Tanzania, 127pp.

Terakunpisut J, Gaajaseni N and Ruankawe N 2007 Carbon sequestration potential in aboveground biomass of Thong Pha Phum National Forest, Thailand. Applied Ecology and Environmental Research Journal 5(2): 93 – 102.

Thornton P K, Notenbaert A M and Herrero M 2009 The impacts of climate change on livestock and livestock systems in developing countries: A review of what we know and what we need to know. Agriculture System Journal 101: 113 –127.

Urassa J K 1999 The factors influencing milk output of dairy cattle under smallholder farms. Dissertation for Award of MSc Degree at Sokoine University of Agriculture, Morogoro, Tanzania, 131pp.

Van Tol A 2004 Fodder Trees – AGROMISA. [www.agromisa.org/displayblob] site visited on 1/8/2011.

Vesterdal L, Ritter E and Gundersen P 2002 Change in soil organic carbon following afforestation of former arable land. Forest Ecology and Management Journal 169: 137 – 147.

Walshe M J 1993 Dairy Development Issues and Options (with special reference to sub - Saharan Africa) In: Proceedings of Dairy Development Policy and Implementation, 12 - 16 July, 1993 Harare Zimbabwe. pp. 155 – 171.

Williams R, Danchenko, Kylizhskiy A and Nicodemus S M 2009 Comparison of carbon content and carbon equations for tree species in Southern Ohio and Tomsk, Russia. 390pp.


Received 26 April 2017; Accepted 18 July 2017; Published 3 October 2017

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