Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot

The impact of land cover change on the carbon stock of moist afromontane forests in the Majang Forest Biosphere Reserve

BACKGORUND

Forest plays an important role in the global carbon cycle by sequestering carbon dioxide and thereby mitigating climate change. In this study, an attempt was made to investigate the effects of land use/land cover (LULC) change (1989-2017) on carbon stock and its economic values in tropical moist Afromontane forests of the Majang Forest Biosphere Reserve (MFBR), south-west Ethiopia. Systematic sampling was conducted to collect biomass and soil data from 140 plots in MFBR. The soil data were collected from grassland and farmland. InVEST modelling was employed to investigate the spatial and temporal distribution of carbon stocks. Global Voluntary Market Price (GVMP) and Tropical Economics of Ecosystems and Biodiversity (TEEB) analysis was performed to estimate economic values (EV) of carbon stock dynamics. Correlation and regression analyses were also employed to identify the relationship between environmental and anthropogenic impacts on carbon stocks.

RESULTS

The results indicated that the above-ground carbon and soil organic carbon stocks were higher than the other remaining carbon pools in MFBR. The mean carbon stock (32.59 M tonne) in 2017 was lower than in 1989 (34.76 Mt) of MFBR. Similarly, the EV of carbon stock in 2017 was lower than in 1989. Elevation, slope, and harvesting index are important environmental and disturbance factors resulting in major differences in carbon stock among study sites in MFBR.

CONCLUSIONS

Therefore, the gradual reduction of carbon stocks in connection with LULC change calls for urgent attention to implement successful conservation and sustainable use of forest resources in biosphere reserves.

Tree species composition along environmental and disturbance gradients in tropical sub-montane forests, Tanzania

Understanding the environmental and disturbance determinants of tree species dominance and community composition in an ecosystem, is important for informing management and conservation decisions, through maintaining or improving the existing forest composition and structure. This study was carried out to quantify the relationship between forest tree composition structure and environmental and disturbance gradients, in a tropical sub-montane forest of Eastern Usambara. Vegetation, environmental, and anthropogenic disturbance data for 58 plots across Amani and Nilo nature forest reserves were obtained. Agglomerative hierarchical cluster analysis and canonical correspondence analysis (CCA) were used to identify plant communities and analyze the influence of environmental variables and anthropogenic disturbances on tree species and community composition respectively. Four communities were identified and CCA results showed that the variation was significantly related to elevation, pH, Annual mean temperature, temperature seasonality, phosphorus nutrients and pressures from adjacent villages and roads. Likewise, environmental factors (climate, soil and topography) explained the most variation (14.5%) of tree and community composition in relation to disturbance pressure (2.5%). The large and significant variation in tree species and community patterns explained by environmental factors suggests a need for site-specific assessment of environmental properties for biodiversity conservation plans. Similarly, the intensification of human activities and associated impacts on natural environment should be minimized to maintain forest species composition patterns and communities. The findings are useful in guiding in policy interventions that focus on minimizing human disturbances in the forests and could aid in preserving and restoring the functional organization and tree species composition of the sub-tropical montane forests.

High aboveground carbon stock of African tropical montane forests

Tropical forests store 40-50 per cent of terrestrial vegetation carbon¹. However, spatial variations in aboveground live tree biomass carbon (AGC) stocks remain poorly understood, in particular in tropical montane forests². Owing to climatic and soil changes with increasing elevation³, AGC stocks are lower in tropical montane forests compared with lowland forests². Here we assemble and analyse a dataset of structurally intact old-growth forests (AfriMont) spanning 44 montane sites in 12 African countries. We find that montane sites in the AfriMont plot network have a mean AGC stock of 149.4 megagrams of carbon per hectare (95% confidence interval 137.1-164.2), which is comparable to lowland forests in the African Tropical Rainforest Observation Network⁴ and about 70 per cent and 32 per cent higher than averages from plot networks in montane^2,5,6 and lowland⁷ forests in the Neotropics, respectively. Notably, our results are two-thirds higher than the Intergovernmental Panel on Climate Change default values for these forests in Africa⁸. We find that the low stem density and high abundance of large trees of African lowland forests⁴ is mirrored in the montane forests sampled. This carbon store is endangered: we estimate that 0.8 million hectares of old-growth African montane forest have been lost since 2000. We provide country-specific montane forest AGC stock estimates modelled from our plot network to help to guide forest conservation and reforestation interventions. Our findings highlight the need for conserving these biodiverse^9,10 and carbon-rich ecosystems.

The Flows of Nature to People, and of People to Nature: Applying Movement Concepts to Ecosystem Services

To date, the provision of ecosystem services has largely been estimated based on spatial patterns of land cover alone, using benefit transfer analysis. Although it is increasingly being recognised that the distribution of the human population affects whether a potential service translates into a realised service, this misses key steps in the process and assumes that everyone accesses ecosystem services in the same way. Here we describe a conceptual approach to ecosystem services in terms of movement and flows. We highlight that ecosystem service flows can be broken down into ‘nature to people’ (the movement of nature towards beneficiaries) and ‘people to nature’ (the movement of beneficiaries towards nature). The former has been relatively well described. Here, we explore the latter by reviewing research on human migration, animal foraging and landscape connectivity. We assess if and how existing theories might be useful in describing how people seek out ecosystem services. We consider some of the ways in which flows of people to nature can be measured. Such measurements may reveal which movement theories best represent how people seek out and access ecosystem services. Overall, our review aims to improve the future modelling of ecosystem services by more explicitly considering how people access potential services and therefore realise them.

Ensembles of ecosystem service models can improve accuracy and indicate uncertainty

Many ecosystem services (ES) models exist to support sustainable development decisions. However, most ES studies use only a single modelling framework and, because of a lack of validation data, rarely assess model accuracy for the study area. In line with other research themes which have high model uncertainty, such as climate change, ensembles of ES models may better serve decision-makers by providing more robust and accurate estimates, as well as provide indications of uncertainty when validation data are not available. To illustrate the benefits of an ensemble approach, we highlight the variation between alternative models, demonstrating that there are large geographic regions where decisions based on individual models are not robust. We test if ensembles are more accurate by comparing the ensemble accuracy of multiple models for six ES against validation data across sub-Saharan Africa with the accuracy of individual models. We find that ensembles are better predictors of ES, being 5.0-6.1% more accurate than individual models. We also find that the uncertainty (i.e. variation among constituent models) of the model ensemble is negatively correlated with accuracy and so can be used as a proxy for accuracy when validation is not possible (e.g. in data-deficient areas or when developing scenarios). Since ensembles are more robust, accurate and convey uncertainty, we recommend that ensemble modelling should be more widely implemented within ES science to better support policy choices and implementation.

Economic, land use, and ecosystem services impacts of Rwanda's Green Growth Strategy: An application of the IEEM+ESM platform

We develop and link the Integrated Economic-Environmental Modeling (IEEM) Platform to ecosystem services modeling (ESM). The IEEM+ESM Platform is an innovative decision-making framework for exploring complex public policy goals and elucidating synergies and trade-offs between alternative policy portfolios. The IEEM+ESM approach is powerful in its ability to shed light on (i) change in land use and ecosystem services driven by public policy and the supply and demand responses of businesses and households; and (ii) impacts on standard economic indicators of concern to Ministries of Finance such as gross domestic product and employment, as well as changes in wealth and ecosystem services. The IEEM+ESM approach is being adopted rapidly and by the end of 2020, IEEM+ESM Platforms will be implemented for about 25 countries. To demonstrate the insights generated by the IEEM+ESM approach, we apply it to the analysis of alternative green growth strategies in Rwanda, a country that has made strong progress in reducing poverty and enhancing economic growth in the last 15 years. The case of Rwanda is particularly compelling as it faces intense pressure on its natural capital base and ecosystem services, already with the highest population density in Africa, which is projected to double by 2050. In applying IEEM+ESM and comparing the outcomes of Rwanda's green growth policies, increasing fertilization of agricultural crops shows the largest economic gains but also trade-offs in environmental quality reflected through higher nutrient export and reduced water quality. Combining crop fertilization with forest plantations better balances critical ecosystem services and their role in underpinning economic development as Rwanda progresses toward its target of middle-income status by 2035. This application to Rwanda's green growth strategy demonstrates the value-added of the IEEM+ESM approach in generating results that speak to both economic outcomes and impacts on market and non-market ecosystem services.

Correction to: Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot

Upon publication of the original article [1], the authors noticed that the figure labelling for Fig. 4 in the online version was processed wrong. The top left panel should be panel a, with the panels to its right being b and c. d and e should be the panels on the lower row, and f is correct. The graphs themselves are all correct. It is simply the letter labels that are wrong.

Aboveground Carbon Storage and Its Links to Stand Structure, Tree Diversity and Floristic Composition in South-Eastern Tanzania

African savannas and dry forests represent a large, but poorly quantified store of biomass carbon and biodiversity. Improving this information is hindered by a lack of recent forest inventories, which are necessary for calibrating earth observation data and for evaluating the relationship between carbon stocks and tree diversity in the context of forest conservation (for example, REDD+). Here, we present new inventory data from south-eastern Tanzania, comprising more than 15,000 trees at 25 locations located across a gradient of aboveground woody carbon (AGC) stocks. We find that larger trees disproportionately contribute to AGC, with the largest 3.7% of individuals containing half the carbon. Tree species diversity and carbon stocks were positively related, implying a potential functional relationship between the two, and a ‘win–win’ scenario for conservation; however, lower biomass areas also contain diverse species assemblages meaning that carbon-oriented conservation may miss important areas of biodiversity. Despite these variations, we find that total tree abundance and biomass is skewed towards a few locally dominant species, with eight and nine species (5.7% of the total) accounting for over half the total measured trees and carbon, respectively. This finding implies that carbon production in these areas is channelled through a small number of relatively abundant species. Our results provide key insights into the structure and functioning of these heterogeneous ecosystems and indicate the need for novel strategies for future measurement and monitoring of carbon stocks and biodiversity, including the use for larger plots to capture spatial variations in large tree density and AGC stocks, and to allow the calibration of earth observation data.

Land cover change and carbon emissions over 100 years in an African biodiversity hotspot

Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the presatellite era. Here, we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo-referenced and digitized historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a fivefold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4-1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha(-1)  yr(-1) . This is at least threefold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8-5.7) Mg C ha(-1) , compared to a committed loss of 11.9 (7.2-16.6) Mg C ha(-1) within areas lacking such protection. Furthermore, for nine protected areas where LULCC data are available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics.

Interactions between Canopy Structure and Herbaceous Biomass along Environmental Gradients in Moist Forest and Dry Miombo Woodland of Tanzania

We have limited understanding of how tropical canopy foliage varies along environmental gradients, and how this may in turn affect forest processes and functions. Here, we analyse the relationships between canopy leaf area index (LAI) and above ground herbaceous biomass (AGB_H) along environmental gradients in a moist forest and miombo woodland in Tanzania. We recorded canopy structure and herbaceous biomass in 100 permanent vegetation plots (20 m × 40 m), stratified by elevation. We quantified tree species richness, evenness, Shannon diversity and predominant height as measures of structural variability, and disturbance (tree stumps), soil nutrients and elevation as indicators of environmental variability. Moist forest and miombo woodland differed substantially with respect to nearly all variables tested. Both structural and environmental variables were found to affect LAI and AGB_H, the latter being additionally dependent on LAI in moist forest but not in miombo, where other factors are limiting. Combining structural and environmental predictors yielded the most powerful models. In moist forest, they explained 76% and 25% of deviance in LAI and AGB_H, respectively. In miombo woodland, they explained 82% and 45% of deviance in LAI and AGB_H. In moist forest, LAI increased non-linearly with predominant height and linearly with tree richness, and decreased with soil nitrogen except under high disturbance. Miombo woodland LAI increased linearly with stem density, soil phosphorous and nitrogen, and decreased linearly with tree species evenness. AGB_H in moist forest decreased with LAI at lower elevations whilst increasing slightly at higher elevations. AGB_H in miombo woodland increased linearly with soil nitrogen and soil pH. Overall, moist forest plots had denser canopies and lower AGB_H compared with miombo plots. Further field studies are encouraged, to disentangle the direct influence of LAI on AGB_H from complex interrelationships between stand structure, environmental gradients and disturbance in African forests and woodlands.