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Does Forest Certification Enhance Forest Structure? Empirical Evidence fromCertified Community-Based Forest Management in Kilwa District, TanzaniaAuthor(s): S.K. Kalonga, F. Midtgaard and T. EidSource: International Forestry Review, 17(2):182-194.Published By: Commonwealth Forestry AssociationURL: http://www.bioone.org/doi/full/10.1505/146554815815500570

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182 International Forestry Review Vol.17(2), 2015

Does forest certification enhance forest structure? Empirical evidence from certified community-based forest management in Kilwa District, TanzaniaS.K. KALONGA, F. MIDTGAARD and T. EID

Department of Ecology and Natural Resource Management, Faculty of Environmental Sciences and Technology, Norwegian University of Life Sciences, Post Box 5003, NO-1432 Ås, Norway

Email: [email protected], [email protected] and [email protected]

SUMMARY

Forest Stewardship Council (FSC) standards support enhancement of certified forests. However, the performance of certified forests in enhanc-ing forest structure has rarely been examined empirically. Forest structure, human forest use and forest governance indicators are assessed in a comparative study of FSC-certified community forests, open access forests (non-FSC) and state forest reserves (non-FSC) in Kilwa District, Tanzania. The FSC-certified forests have better forest structure, appropriate regeneration, and lower fire incidences than open access forests and state forest reserves. Certified forests also provide more economic benefits to communities compared to non-FSC forests. These findings imply that forest certification could be an appropriate management intervention, and that adoption of FSC standards may lead to more effective man-agement in human-dominated landscapes. However, because of the short time certification has been operational, it is hard to precisely identify all effects of certification. Further empirical evidence on effects, in space and time, is therefore desirable.

Keywords: forest certification, forest governance, forest management regimes, responsible forest management, confounding factors

La certification forestière améliore-t-elle la structure forestière? Preuves empiriques tirées de la gestion d’une forêt à base communautaire dans le district de Kilwa en Tanzanie

S.K. KALONGA, F. MIDTGAARD et T. EID

Les standards du Conseil d’administration forestière (FSC) soutiennent une amélioration des forêts certifiées. Toutefois, la performance des forêts certifiées dans l’amélioration de la structure forestière a rarement été examinée empiriquement. La structure forestière, l’utilisation de la forêt par les humains et les indicateurs de gestion forestiers sont évalués dans une étude comparative de forêts communautaires certifiées par le FSC, de forêts à accès ouvert (non FSC), et de réserves forestières d’état (non FSC) dans le district de Kilwa en Tanzanie. Les forêts certifiées par le SFC ont une meilleure structure forestière, une régénération appropriée et une moindre incidence de feux que les forêts à accès ouvert et que les réserves forestières d’état. Les forêts certifiées produisent également davantage de bénéfices économiques dans les communautés com-parées aux forêts non FSC. Ces résultats indiquent que la certification forestière pourrait-être une intervention de gestion appropriée et que l’adoption des standards du FSC pourrait résulter en une gestion plus efficace dans les paysages dominés par l’homme. Il est néanmoins difficile d’identifier précisément tous les effets de la certification, dû au temps limité pendant lequel la certification a été opérationnelle. Il est par conséquent désirable d’obtenir plus des preuves empiriques sur ses effets dans le temps et dans l’espace.

¿Mejora la certificación forestal la estructura del bosque? Pruebas empíricas de la gestión forestal de base comunitaria certificada en el distrito de Kilwa (Tanzania)

S.K. KALONGA, F. MIDTGAARD y T. EID

Los estándares del Forest Stewardship Council (FSC) ayudan a la mejora de los bosques certificados. Sin embargo, rara vez se ha examinado empíricamente el desempeño de los bosques certificados en cuanto a la mejora de la estructura del bosque. Se evalúan la estructura del bosque, el aprovechamiento forestal humano e indicadores de la gobernanza forestal en un estudio que compara bosques comunitarios certificados FSC con bosques de acceso abierto (no-FSC) y con las reservas forestales del Estado (no-FSC) en el distrito de Kilwa (Tanzania). Los bosques certificados FSC cuentan con una mejor estructura forestal, una regeneración adecuada, y una menor incidencia de incendios que los bosques de acceso abierto y las reservas forestales del Estado. Los bosques certificados proporcionan también más beneficios económicos a las comu-nidades en comparación con los bosques no FSC. Estos resultados implican que la certificación forestal podría ser una intervención de gestión adecuada, y que la adopción de los estándares del FSC puede lograr una gestión más eficaz en paisajes dominados por el hombre. Sin embargo, debido al poco tiempo que la certificación ha estado en funcionamiento, es difícil identificar con precisión todos los efectos de la certificación. Por lo tanto, sería deseable obtener más pruebas empíricas sobre sus efectos, en el espacio y el tiempo.

Does forest certification enhance forest structure? 183

4) community relations; 5) benefits from the forest; 6) envi-ronmental values and impacts; 7) management planning; 8) monitoring and assessment; 9) conservation values; and 10) implementation of management activities.

There are about 1 400 village land FRs under CBFM in Tanzania (MNRT 2008), of which six were FSC-certified by the end of 2012. The certified FRs were established to dem-onstrate how responsible forest management may enhance forest structure through sustainable resources utilisation. However, the performance of FSC-certified community FRs has rarely been examined empirically, neither internationally (e.g. see Cubbage et al. 2010, Romero et al. 2013) nor in Tanzania.

The authors are aware of previous studies that have been carried out to evaluate performance of various forest manage-ment regimes (FMRs) in Tanzania (e.g. see Blomley et al. 2008, Lund and Treue 2008, Meshack et al. 2006, Mongo et al. 2014, Mbwambo et al. 2012, Sauer and Abdallah 2007, Treue et al. 2014, Vyamana 2009). Although these studies are valuable for providing insights into the performance of vari-ous FMRs, none of them has evaluated any forest certification approaches.

Moreover, some of these studies suffer from potential methodological flaws that make it difficult to assess the valid-ity of their findings. In two critical reviews of such studies, Lund et al. (2009) and Bowler et al. (2012) mention flaws such as inadequate data, lack of comprehensive background information, methodological inconsistence (some using only a single research method) or lack of reasoning (some using livelihoods indicators only or forest stocking indicators only to evaluate forest management). These reviews suggest that the flaws may be addressed by providing better and more detailed descriptions on the actual forest policy and legal framework and on the indicators used to study the impacts of different FMRs. They in addition suggest including more con-siderations on how to disentangle (i.e. identify and separate) the impact of the actual policy from other confounding factors (i.e. factors affecting the results but not easy to control for) influencing the conditions.

Also other studies have expressed similar concerns on studies evaluating the performance of various FMRs. Ostrom and Nagendra (2006), for example, claim that changes in forest management may impact differently on biophysical and socioeconomic indicators. Vatn (2005) and Ostrom and Nagendra (2006) also claim that studies focusing on a single research method and data type do not provide a full under-standing of how individuals affect complex social-ecological systems outcomes.

The present study attempts to answer the following basic question: Does forest certification enhance forest structure? Specifically, the study assesses forest structure indicators, human forest use indicators and forest governance system indicators in a comparative study of FSC-certified community forests, de facto open access forests (non-FSC) and state FRs (non-FSC) FMRs in Kilwa District, Tanzania.

The present study also attempts to address some of the described methodological flaws. Firstly, the study assesses

INTRODUCTION

Tropical forests provide a variety of valuable ecosystem services such as biodiversity, carbon sequestration, water cycling and scenic beauty (Gardner et al. 2009, Sell et al. 2007). Yet there is a great deal of what may be called ungov-erned deforestation and forest degradation going on in these forests due to illegal exploitation and poor management (FAO 2010), compromising their potential to provide these ecosystem services.

Forest resources in Tanzania have been managed by the state during and after the colonial eras by undertaking a num-ber of forest policy reform programmes aiming at improving the management of natural resources (Burgess and Clarke 2000, Zahabu et al. 2009). Most of these reforms; however, have not given the expected results (e.g. see Burgess and Clarke 2000, Zahabu et al. 2009), as deforestation and forest degradation have escalated (Milledge et al. 2007). In combat-ing this problem, the new Forest Policy was approved in 1998 and the new Forest Act enacted in 2002. This led to the intro-duction of a communal regime, whereby the villagers have the mandate to set aside part of their village ‘‘general land’’ forests as forest reserves (FRs) under community-based forest management (CBFM). The CBFM programme was initiated as a tool to restore degraded forests (Blomley et al. 2010). This implies that the FRs were generally established in forests with poor condition (Blomley and Iddi 2009). In spite of the institutional and legal frameworks settled, and the aim of restoring degraded forests by controlling forest exploitation, illegal exploitation of forest resources in these areas has continued (Milledge et al. 2007).

In response to escalating deforestation and forest degrada-tion, particularly in the tropics, non-governmental bodies formed Forest Stewardship Council (FSC) in 1993 (e.g. see Auld et al. 2008, Marx and Cuypers 2010). The FSC is an international not-for-profit, multi-stakeholder organisation responsible for promoting an environmentally appropriate, socially beneficial, and economically viable management of forests through forest management certification standards (principles and criteria) (Blackman and Rivera 2010, Karmann and Smith 2009). The standards certify responsible forest management for the production of forest products (Karmann and Smith 2009), aiming at meeting not only public expectations for better forest management and envi-ronmental practices, social standards and economics analy-ses, but also promoting high quality management practices (Cubbage et al. 2010). They control legal and monitor illegal logging (FSC 2012). In this way, FSC standards support the maintenance and enhancement of forest resources in certified forests (Karmann and Smith 2009, Medjibe et al. 2013) by halting deforestation and forest degradation (FSC 2012). However, how to achieve this is challenging (e.g. Auld et al. 2008).

The FSC certification standards have 10 principles and 70 criteria which provide details on how to manage forests responsibly (see details in FSC 2012). The principles are related to: 1) compliance with laws; 2) workers’ rights and employment conditions; 3) indigenous peoples’ rights;

184 S.K. Kalonga et al.

the actual policy and legal framework related to forest man-agement by using forest governance and institutions indica-tors as a proxy for rule compliance (see Kaufmann et al. 2011). Secondly, the study acquires biophysical data, used as forest structure indicators, and socioeconomic data and infor-mation, used as human forest use indicators, to evaluate the performance of various FMRs. To collect and use such data and information, the study applies integrated natural and social sciences research approaches (see Creswell 2013, Lund et al. 2014). Specifically, the study focuses on the indicators of impacts, and on how to disentangle their effects from other confounding factors that may impact on forest structure, and forest governance and institutions. This is made possible by triangulation (i.e. use of multiple data sources and methods of analysis) of the observations from the study.

METHODS

Study area

The study was conducted in Kilwa District in Lindi Region. The district is located between 8°15’–10°00’S and 38°40’–39°40’E with an area of 13 347.50 km2. The district has a coastal climate with a mean annual temperature ranging from 22°C to 30°C with 98–100% humidity and a mean annual rainfall of 1 034 mm (KDC 2008). The study area falls on the western part of Kilwa which is characterised by miombo woodlands with some patches of coastal forests, and north Zambezian undifferentiated woodlands and wooded grass-land (Lillesø et al. 2014). Indicator miombo tree species such as Acacia polyacantha Willd, Lonchocarpus capassa Rolfe, Piliostigma thonningii Schum and Xeroderris stuhlmannii (Taub.) Mendonça & E.P. Sousa were observed during fieldwork. The miombo woodlands in Kilwa District are open allowing easy access for selective logging, which is the norm in the area (Ball 2011). The accessibility of these woodlands means that they have been heavily exploited for domestic consumption and for export, as one of the earliest sources of timber from East Africa in the 1950s to 1980s (Burgess and Clarke 2000). Also presently, the woodlands are heavily influenced by informal economic activities like logging and pit-sawing (KDC 2011) and they are everywhere threatened

by an ever-increasing demand for farmland, fuelwood and charcoal production (Burgess and Clarke 2000).

Six forests, and four villages adjacent to these forests, were chosen for this comparative study (see Figure 1, Table 1). Kikole and Kisangi are FSC-certified community forests under CBFM. Likawage and Mchakama forests are village ‘‘general land’’ forests under open access regime with-out certification and Mitarure and Rungo forests are state FRs under state management without certification. The sampled forests were all in the same agro-ecological zone and with similar vegetation type. Inclusion of non-FSC CBFM forests in the sample would have been valuable for this study. How-ever, no non-FSC CBFM forests with similar vegetation type in the same agro-ecological zone were available.

In theory, these forests have similar legal management requirements. The Forest Act of 2002 requires the state and village FRs to have forest management plans clearly defining management objectives. Lund and Treue (2008), however, claim that while resource rights are shaped by de jure legal provisions in the state FRs and village ‘‘general land’’ forests, the access to these resources is shaped by de facto situation. The Village Natural Resource Committee (VNRC) is respon-sible for the management of the village land FRs, Kilwa District Forest Office (KFO) manages all operations in the state FRs, while the village ‘‘general land’’ forests are co-managed by VNRC and KFO (Table 1). The utilisation of forest resources from the village ‘‘general land’’ forests under open access regime are preceded by preparation of a harvest-ing plan as per Government Notice No. 60 and 70 of 2006, whereby harvesting is manned by the VNRC (de jure rights) with technical support from KFO. The VNRC or KFO or both are required to identify and mark all harvestable trees before harvesting in both village land FRs and village ‘‘gen-eral land’’ forests. High quality mature trees are also selected and marked to remain for seed production to enhance natural regeneration.

Kikole, Kisangi, Likawage and Mchakama villages were the villages investigated alongside with these forest sites (Figure 1). Before 1974, the forests adjacent to these villages were under open access regime. During the villagisation process in 1974, whereby people were urged to establish per-manent settlements as a control of previously scattered rural population, land clearing for settlement and farming started.

TABLE 1 Forests description

Forest Area (ha)

Elevation (m)

Distance to town

(km)

Current forest management regime

Forest certifica-tion

Forest legal statusForest owner

Forest manager

Kikole 454 71–112 33.7 CBFM FSC, 2009 Village Land Forest Reserve Village VNRC

Kisangi 1 966 99–158 33.5 CBFM FSC, 2009 Village Land Forest Reserve Village VNRC

Likawage 17 000 121–293 100.8 Open access Non-FSC Village General Land Forest State VNRC/KFO

Mchakama 3 000 153–358 54.4 Open access Non-FSC Village General Land Forest State VNRC/KFO

Mitarure 60 484 92–172 30.6 State Non-FSC State Forest Reserve State KFO

Rungo 22 586 120–277 89.9 State Non-FSC State Forest Reserve State KFO


FIGURE 1 Study site in Kilwa District, Lindi Region, Tanzania


Kikole and Kisangi village forests changed management from open access regime to CBFM regime in 2007, and were later on FSC-certified in 2009 (Table 1). Likawage and Mchakama forests are still under open access regime. Currently, the main use of the FSC-certified community forests and the open access forests is commercial timber production. These forests are also used for grazing and supply of subsistence and cash from forest products including fuelwood, construction mate-rials and medicinal plants. Mchakama forest is less disturbed along the gorge of the Mavuji River (Perkin et al. 2008) due to limited access because of physiographic factors (Figure 1).

Mitarure and Rungo state FRs (Table 1) were gazetted in 1957 and 1956, respectively, for protection and production purposes. Before then they were under open access regime. After their gazettement, the reserves have rarely been man-aged except that forest boundaries were maintained up to the late 1970s. Thereafter KFO, as the manager on behalf of the state, has only been carrying out sporadic surveillance patrols in the reserves due to limited funds and human resources. From 1980 to1984, the reserves were legally and extensively harvested by Tanzania Wood Industries Company without any harvesting plan. In 1985, Mitarure was also harvested by Ushirikiano Wood Products Company, a Chinese company, in partnership with the state. Legal harvesting stopped in 1986 and 1990 in Mitarure and Rungo, respectively. Since then, the reserves have illegally been harvested. Extensive illegal harvesting in Mitarure occurred during the time of oil explo-ration in 1987–1988. In addition to illegal harvesting, the reserves are threatened by other human activities such as uncontrolled wildfires, and recently from livestock grazing, because pastoralists are moving into the area. The reserves do not have forest management plans, although the Forest Act of 2002 requires them to have plans. The state has de jure rights to these reserves, but the local communities and private indi-viduals are the de facto managers (see FAO 2002, Lund et al. 2009).

Data collection

In the present study, systematic sample plot forest inventories were used to collect data on forest structure and human forest use indicators, whereas participatory rural appraisals (PRA) and household surveys were used to collect data and informa-tion on forest governance and institutions indicators.

Forest structure indicators’ data A reconnaissance survey was first done to determine the statistically required number of sample plots per forest based on between plot variability and the area. Systematic sample plot inventories were then carried out for each forest in 2013. For all forests, the first plot was located randomly at 100 m from the boundary of the forest. By using Global Positioning System (GPS), subsequent plots were located systematically at 500 m, 500 m, 1 500 m, 1 000 m, 2 000 m and 1 500 m intervals along transects for Kikole, Kisangi, Likawage, Mchakama, Mitarure and Rungo, respectively. The distance

between transects varied from 500 m to 5 000 m depending on the size of the forest and the required number of sample plots. A total of 131 sample plots with radius of 20 m (0.126 ha), distributed with 22, 18, 24, 20, 18 and 29 plots to Kikole, Kisangi, Likawage, Mchakama, Mitarure and Rungo, respec-tively, were established. For all trees on a plot, diameter at breast height (dbh) for trees with dbh ≥3 cm was recorded. In addition, two sample trees on each plot, i.e. the first and second nearest tree to the plot centre, were selected for measurements of basal diameter (30 cm from ground), dbh and total tree height. A count of seedlings ≤10 cm tall was also carried out from plots of 1m radius (0.0003 ha).

Human forest use indicators’ data Stumps and fire incidences were also recorded from all 20 m radius plots. Basal diameter was recorded for all stumps ≤5 years old. The age of stumps was assessed by local infor-mants based on the colour and degree of decay of the cut surface, combined with their knowledge on whether harvesting activities recently had taken place in the respective forests. Proportion of area burnt (%) was also recorded for each plot. Other information recorded at plot level included distances (in kilometres) to access roads and nearby towns by using GPS.

Forest governance and institutions indicators’ data Mixed methods of qualitative (PRA) and quantitative (house-hold survey) approaches (see Creswell 2013) were used for data and information collection in the four villages. For the PRA, focus group discussions and key informants interviews were carried out using meetings and semi-structured inter-views, respectively. Participants were randomly selected by the researcher from the village register. The size of focus groups ranged from 6–12 people. The PRA provided an overview of the prevailing forest governance and institutional conditions including history of forest management and resources use patterns, forest policies, laws and regulations, i.e. forest bylaws, and forest management plans.

The household surveys were conducted using structured questionnaires. The sampling frame for the surveys was stratified by wellbeing. A participatory wellbeing ranking was therefore first carried out in a village assembly in each village, facilitated by the research team, whereby the house-holds were categorised into three groups according to well-being (rich, middle and poor). The rankings were carried out using criteria established by the villagers themselves, i.e. a combination of food security, landholding, education level of family members, social status and recognition, and physical assets. Households were then sampled, approximately in proportion to the size of each wellbeing category. A total of n = 176 households (n = 44 per village) were surveyed to provide quantitative data on household’s knowledge and implementation of forest governance and institutions, i.e. about access to forest resource use, the role of relevant institu-tions, and forest resource governance (see details in Kalonga and Kulindwa 2014).


RESULTS

Forest structure and human forest use indicators

Forest structure and human forest use indicators varied among the forests (Table 2). Number of trees (N/ha), basal area (m2/ha), volume (m3/ha) were significantly larger in Kisangi and Mchakama than the other forests. Although the number of seedlings (N/ha) in Kikole and Mchakama was higher than the other forests, they were not significantly different from them. Number of stumps (N/ha) and fire (area burnt/ha) were significantly larger in Mitarure than the other forests. Also stumps’ volume (m3/ha) was higher in Mitarure than the other forests, but insignificant.

Analyses by means of GLM, with stumps’ volume as a proxy for harvesting rate (human forests use) showed that there was an effect in Mitarure (p = 0.0500) and Rungo (p = 0.0434), while there were no effects in the other forests. Fire showed an effect in Likawage (p = 0.0121), Mitarure (p = 0.0038) and Rungo (p = 0.0010), but no effect in the other forests.

The diameter class distribution of all the forests to some extent showed inverse J-shaped curves (Figure 2), i.e. relatively more trees in the lower diameter classes than in the highest. However, for all forests, except Kisangi and Mchakama, the number of small trees was still relatively low and the largest trees were to some extent lacking.

In Mchakama and Rungo, the harvests were concentrated to relatively big trees, i.e. relatively high volumes (m3/ha) came from relatively few stumps (N/ha), whereas the harvests in Kisangi, Likawage and Mitarure were concentrated to smaller trees (Figure 3). It should be noted that during the forest inventories recent and ongoing harvesting activities (last two years) were observed in Mchakama forest, whereas

Data analyses

Data analyses involved estimation of the following forest structure indicators: number of trees (N/ha), basal area (m2/ha), volume (m3/ha), and number of seedlings (N/ha). Human forest use indicators estimates included number of stumps (N/ha) and associated volume (m3/ha), as well as proportion of area burnt/ha. In order to estimate dbh for the trees that were cut (stumps) for the purpose of estimating volume (m3/ha), dbh - basal diameter equations were developed per forest from the sample trees. A local volume model using dbh as independent variable developed by Mauya et al. (2014) for Lindi miombo woodlands was used for the volume estimate.

The variations in forest structure and human forest use indicators among the forests were tested in pairs (pair- wise comparison) using Bonferroni t-test (see Holland and Copenhaver 1988). To assess the influence of FMRs in enhancing forest structure, the generalised linear model (GLM) was used to establish the relationships between human forest use indicators (response variables), i.e. stump volume and fire incidences, and the FMRs (forests) as categorical explanatory variables (with six levels: Kikole, Kisangi, Likawage, Mchakama, Mitarure and Rungo). The GLM was employed using a quasipoisson family to take care of non-normally distributed data (see Crawley 2013), which was the case for the present dataset. Spearman rank correla-tion test was used to measure the direction and the strength of the relationships between the plot level human forest use indicators (stumps, fire and distances) and forest structure indicators. All these statistical analyses were conducted in R statistical data analysis programme, version 3.0.1. The varia-tions in forest governance and institutions indicators among FMRs from household survey data were analysed using a statistical package for social science (SPSS).

TABLE 2 Forest structure and human forest use indicators among the forests

Kikole Kisangi Likawage Mchakama Mitarure Rungo

Forest structure indicators:

Trees (N/ha) 841A ± 98 1 385B ± 154 633A ± 70 1 434B ± 149 739A ± 82 461A ± 55

Basal area (m2/ha) 11.0A ± 1.2 16.6B ± 1.6 7.7A ± 0.7 21.4B ± 1.9 9.9A ± 0.9 7.4A ± 0.9

Volume (m3/ha) 100.8A ± 25.7 167.4B ± 42.7 74.4A ± 19.8 228.2B ± 52.5 93.0A ± 19.6 74.1A ± 24.6

Seedlings (N/ha) 12 009A ± 3 728 6 897A ± 3 206 5 040A ± 2 756 12 732A ± 5 474 6 543A ± 4 161 6 476A ± 2 660

Human forest use indicators:

Stumps (N/ha) 0.0A ± 0.0 0.9A ± 0.6 1.7A ± 0.8 0.4A ± 0.4 5.7B ± 3.1 0.8A ± 0.6

Stumps (m3/ha) 0.0A ± 0.0 0.7A ± 0.5 1.3A ± 0.6 0.9A ± 0.9 2.4A ± 1.2 1.7A ± 1.1

Fire (Area/ha) 0.014A ± 0.007 0.034A ± 0.011 0.046A ± 0.009 0.035A ± 0.011 0.060B ± 0.013 0.044A ± 0.009

Values after ± are standard errors of the means at 95% confidence intervalThe same superscript letters in the same row denote mean values which do not differ significantly from each other at α = 0.05 level.


old stumps (within two to five years) were observed in all the other forests.

Generally, there were negative correlations between stumps’ volume harvested and the distances, except Mchakama forest (Table 3), i.e. the longer the distance to the plot, the less harvest. For Mchakama, the correlations between volume harvested and distances were positive, but insignificant. The negative correlations were stronger for distance to access road than for distance to nearby town in Kisangi and Likawage. For Rungo, the negative correlation was stronger for distance to nearby town as compared to distance to access road.

In general, the area burnt was relatively low, while the seedling density was relatively high for Kikole and Mchakama as compared to Likawage and Mitarure, whereby the area burnt was relatively high and the seedling density low (Figure 4). Correlation analyses showed negative correlations

between area burnt and number of seedlings, i.e. the larger the area burnt, the less the seedlings, with statistical significance in Likawage (r = –0.6350, p = 0.0009), Mchakama (r = –0.5030, p = 0.0238) and Rungo (r = –0.5290, p = 0.0032). The correlations were also negative for the other forests, but insignificant.

Forest governance and institutions indicators

Forest management in Tanzania is governed by the Forest Act of 2002. The villagers develop forest bylaws to implement the Act in managing their village forests. Generally, more people living adjacent to the FSC-certified community forests were aware of the forest bylaws, and also positive to them, as compared to those living adjacent to the non-FSC forests (Table 4). However, the awareness of the bylaws was also

FIGURE 2 Distribution of number of trees (N/ha) by diameter classes among the forests


TABLE 3 Correlation coefficients between stumps’ volume (m3/ha) and distances (km) among the forests

Forest Access road Nearby town

Kikole - -

Kisangi r = –0.5069* r = –0.3790ns

Likawage r = –0.5798** r = –0.3351ns

Mchakama r = 0.3616ns r = 0.1596ns

Mitarure r = –0.2112ns r = –0.1148ns

Rungo r = –0.3778* r = –0.5253**

ns: not significant; *: significant at α = 0.05; **: significant at α = 0.01

FIGURE 3 Number of stumps (N/ha) and stumps’ volume (m3/ha) among the forests (Error bars: 95% C.I’s)

FIGURE 4 Fire (area burnt/ha) and seedling density (N/ha) among the forests (Error bars: 95% C.I’s)

high in non-FSC Likawage. Those living adjacent to the FSC-certified community forests were also more motivated to implement sustainable forest management and also had a more positive attitude towards governance and institutions than those living adjacent to non-FSC forests. Key informants reported that FSC villages used these bylaws also to manage open access forests within their landholdings.

In the household survey the villagers were also asked to rank the most damaging human activities taking place in the forests (Table 5). Kikole and Mchakama ranked illegal timber extraction as the most damaging activity, whereas Kisangi and Likawage ranked charcoal production as the most damag-ing activity. Uncontrolled wildfires were ranked as the second most damaging in three of the villages, while cultivation and establishment of settlements generally were ranked as low damaging factors.

Although all the forests have similar legal management requirements as per Forest Act of 2002, in practice the forest management implementation was different among the FMRs (Table 6). Generally, there were much more responsi-ble forest management activities taking place in FSC-certified community forests as compared to non-FSC forests.

DISCUSSION

The lack of empirical evidence on the performance of certi-fied community forests in enhancing forest structure moti-vates this study. The basic question is: does forest certification


TABLE 4 Forest governance and institutions indicators (%) among FSC and Non-FSC villages in Kilwa (n = 44 per village)

IndicatorsFSC Non-FSC

Kikole Kisangi Likawage Mchakama

Awareness of forest bylaws 40.9AB 86.4C 56.8B 27.3A

Effectiveness of forest bylaws 50.0AB 72.7B 43.2A 27.3A

Motivation to implement sustainable forest management 50.0B 53.3B 4.5A 11.4A

Attitudes towards forest governance and institutions 68.2A 4.5B 6.8B 15.9B

Each superscript letter denotes a pair of villages whose column proportions do not differ significantly from each other at the α = 0.05 level

TABLE 5 Villagers’ ranking of most damaging human activities to forest structure in Kilwa (n = 44 per village)

ActivitiesFSC Non-FSC

Kikole Kisangi Likawage Mchakama

Illegal timber extraction 1 6 2 1

Charcoal production 4 1 1 5

Fuelwood extraction 2 3 4 2

Cultivation 4 6 4 4

Establishment of settlements 6 2 6 5

Uncontrolled wildfires 2 4 2 2

TABLE 6 Implementation of forest governance and institutional arrangement among FMRs in Kilwa

Forest governance systemsCBFM FRs

(FSC)Open access

forests (Non-FSC)State FRs

(Non-FSC)

Village Natural Resource Management Committee (VNRC) Yes Yes No

Demarcated area of forest on village land Yes Yes No

Undertake participatory forest resource assessment Yes No No

Forest management plan which includes harvesting plan Yes No No

Identify and mark trees that are of harvestable size before harvesting Yes No No

Supervision of harvesting operations Yes No No

Bylaws that support forest management plan Yes No No

Bylaws compliance or enforcement VNRC KFO KFO

Timber harvesting permit issuance VNRC KFO KFO

Transit Passes issuance to allow for movement of timber KFO KFO KFO

Bylaws monitoring or auditing Third Party Surveillance Unit Surveillance Unit

enhance forest structure? The answer to this question is searched for by evaluating variations in forest structure among FSC-certified CBFM forests, open access forests (non-FSC) and state forest reserves (non-FSC) forest management regimes (FMRs).

For comparisons, it would have been valuable to include non-FSC CBFM forests in this study. Unfortunately, non-FSC CBFM forests were not available for miombo woodlands in this agro-ecological zone. There may also be several

confounding factors (i.e. factors affecting the results but not easy to control for) influencing the variations in forest struc-ture seen among the FMRs. To discern the influence of FMRs on forest structure, the confounding factors were disentangled (see Lund et al. 2009) by assessing and comparing forests and villages with fairly similar biophysical characteristics and socioeconomic activities, respectively. All the selected forests are of the same vegetation type and are located in the same agro-ecological zone, with similar ranges in soil types, slope,


elevation and climate (Figure1, Table 1). The forests have also undergone similar historical management processes (e.g. see Ball 2010, Burgess and Clarke 2000). Socially, the sampled households have similar household characteristics and socio-economic activities (see Kalonga and Kulindwa 2014). Still; however, confounding factors related to, for example, differ-ences among the villagers in market access and differences in forest products prices are not fully controlled for.

In general, the FSC-certified community forests exhibit the best forest structure (i.e. high number of trees, basal area and volume), followed by open access forests (non-FSC forests) and state FRs (non-FSC) as the poorest (Table 2, Figure 2). The possible factors explaining these results include a combination of human forest use, i.e. harvesting levels and fire incidences, distance from forests to forest products utilisation centres and forest governance and institutions.

The relatively sound forest structure in Mchakama as open access forest, is probably due to physiographic factors (Figure 1, Table 1), i.e. Mavuji River is a barrier for access to the forest resulting in a low level of human forest use (Table 2, Figure 3). Good forest governance in FSC-certified community forest management (Table 4, 6) could be one of the reasons for better forest structure seen in Kikole and Kisangi.

The relatively poor forest structure in Likawage, Mitarure and Rungo (Table 2, Figure 2) could be attributed to previous over-harvesting, or to relatively high present harvesting lev-els. The legal and illegal (de facto) harvesting in these forests could be due to poor forest governance and inadequate moni-toring compared to FSC-certified community forests (Table 4, 6). This finding is similar to those of Blomley et al. (2008) and Persha and Blomley (2009). They reported that there is reduced unsustainable forest use in forests with some form of community involvement in management because there is enhanced institutional effectiveness as compared to open access forests and state FRs. Moreover, Blomley et al. (2010) claim that the rights held by the users (de jure) of community forests are important institutional predictors of good forest management because forest bylaws here are viewed as legitimate. The perceived awareness and effectiveness of the bylaws seen among the households adjacent to the FSC-certified community forests in the present study (Table 4) are supporting this.

The open access forests and state FRs have higher propor-tions of burnt area/ha as compared to FSC-certified commu-nity forests (Table 2, Figure 4). This conforms to FAO (2013) who found that state FRs account for more than 70% of annu-ally burnt area in Tanzania. The lower number of trees in the lowest diameter class in Likawage, Mitarure and Rungo FRs compared to the FSC-certified community forests could also be attributed to fire effects. Fire may reduce tree density by killing seedlings in the lower diameter classes (e.g. see Gambiza et al. 2000, Ryan and Williams 2011). However, fire as a tool in the land and resource management (Frost 1999, Kikula 1986) may also stimulate germination of the seeds by causing abrasion in hard-seeded species (Frost and Robertson

1987). In the present study, fire incidence is negatively correlated with the number of seedlings. This may explain the relatively low number of seedlings and the relatively low number of trees in the smallest diameter class found in Likawage, Mitarure and Rungo as compared to the FSC-certified community forests. These findings are in line with a study by Mapaure and Moe (2009) who reported increased proportions of seedlings because of longer forest fire-free periods.

Analogous to fire, heavy grazing and browsing may be detrimental to tree regeneration (see Chidumayo et al. 1996). While fire incidence has been observed as a major problem in Likawage, Mitarure and Rungo (Figure 4), grazing and brows-ing are not very common in the study area because livestock keeping is limited (KDC 2011). These forests border with Selous Game Reserve, and during fieldwork a few signs of wildlife grazing and browsing, tracks and droppings were observed. However, no signs of wildlife grazing and browsing were observed on the plots in any of the forests.

The number of larger trees is low in Likawage, Mitarure and Rungo (Figure 2). This phenomenon may partly be attributed to historical legal and illegal selective harvesting of larger trees for timber reported from the area (see Milledge et al. 2007). Also the higher present harvesting rate in Likawage, Mitarure and Rungo compared to those in the FSC-certified community FRs (Table 2, Figure 3) may imply that unsustainable harvesting activities are still taking place. Although Mchakama forest is not heavily utilised because of difficult accessibility, and thus remain with a relatively good distribution of trees over size classes, this forest might be under threat in future due to ‘‘leakage’’ as a consequence of the intensified FSC-certified community forest manage-ment. The fact that Likawage, Mitarure and Rungo currently lack good sizeable timber may also lead to increased harvest-ing pressure in Mchakama. Mchakama villagers also ranked illegal timber extraction as the most damaging activity to forest structure (Table 5).

Previous studies have reported that harvesting rate decreases with increasing distance from settlements (Chidumayo 2002) and market centres (Treue et al. 2014). Similar results were also seen in the present study (Table 3), except for Mchakama forest, whereby Mavuji River is a barrier for the access to the forest. The significant and strong correlation between access road distance and stumps’ volume for Kisangi and Likawage forests, may imply that these for-ests are mainly used by the villagers for fuelwood, poles and charcoal production, as relatively small trees are harvested (Figure 3). The significant and strong correlation between nearby town distance and stumps’ volume for Rungo forest may imply that this forest is mainly used for production of timber sold in the nearby town, as larger trees are harvested. Also in Mitarure, with weak correlation between stumps’ volume and access road distance, mainly the small trees were harvested, indicating that many villagers utilise the forest for fuelwood, poles and charcoal production.

Forest certification is voluntary (Higman et al. 2005). Forest managers and owners ought to be aware of what the


CONCLUSIONS

The FSC-certified forests have better forest structure, appro-priate regeneration, and lower fire incidences than open access forests (non-FSC) and state forest reserves (non-FSC). Certified forests also provide additional economic benefits to communities compared to non-FSC forests. These findings imply that forest certification could be an appropriate forest management intervention, and that in the context of the Tanzanian forest resource policy and institutional framework, adoption of FSC standards could possibly lead to more effec-tive forest management in human-dominated landscapes. However, because of the short time the certification has been operational, it is hard to identify the precise effects of the certification. Further empirical evidence on such effects in space and time is therefore desirable.

ACKNOWLEDGEMENT

This study was funded by the Climate Change Impacts, Adaptation and Mitigation (CCIAM) Programme in Tanzania. Authors are very grateful to the programme for the financial support. Authors are also grateful to field assistants Mr. Rashid Matanda (Forest inventory) and Mr. Selemani Haji (Tree identification) and Mr. Crawford Ndanshau (Driver). This study would have not have been completed without their assistance. The valuable suggestions made by anonymous referees are also gratefully acknowledged.

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