Ecosystems DOI: 10.1007/s10021-010-9376-8 2010 Springer Science+Business Media, LLC
Ecosystem Carbon Storage Across the Grassland–Forest Transition in the High Andes of Manu National Park, Peru
Adam Gibbon,1* Miles R. Silman,2 Yadvinder Malhi,1 Joshua B. Fisher,1 Patrick Meir,3 Michael Zimmermann,3 Greta C. Dargie,3 William R. Farfan,2,4 and Karina C. Garcia2,4
1Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK; 2Department of Biology, Wake Forest University, 1834 Wake Forest Rd., Winston Salem, North Carolina 27106, USA; 3School of Geosciences, University of Edinburgh, Edinburgh EH8 9XP, UK; 4Universidad Nacional de San Antonio Abad, Cusco, Peru
ABSTRACT Improved management of carbon storage by ter- aboveground carbon decreased from 15.8 on the restrial biomes has significant value for mitigating puna to 8.6 in the transition zone and 2.1 in the forest. climate change. The carbon value of such manage- No significant relationships were found between ment has the potential to provide additional income carbon densities and slope, altitude or fire disturbance to rural communities and provide biodiversity and history, though grazing (for puna) was found to re- climate adaptation co-benefits. Here, we quantify duce aboveground carbon densities significantly. We the carbon stores in a 49,300-ha landscape centered scaled our study sites to the study region with remote on the cloud forest–grassland transition of the high sensing observations from Landsat. The carbon Andes in Manu National Park, Peru. Aboveground sequestration potential of improved grazing man- carbon densities were measured across the land- agement and assisted upslope treeline migration was scape by field sampling of 70 sites above and below also estimated. Afforestation of puna at the treeline the treeline. The forest near the treeline contained could generate revenues of US $1,374 per ha over the 63.4 ± 5.2 Mg C ha-1 aboveground, with an addi- project lifetime via commercialization of the carbon tional 13.9 ± 2.8 Mg C ha-1 estimated to be stored credits from gains in aboveground carbon stocks. in the coarse roots, using a root to shoot ratio of Uncertainties in the fate of the large soil carbon stocks 0.26. Puna grasslands near the treeline were found under an afforestation scenario exist. to store 7.5 ± 0.7 Mg C ha-1 in aboveground bio- mass. Comparing our result to soil data gathered by Key words: Peru; Manu National Park; treeline; Zimmermann and others (Ecosystems 13:62–74, puna; upper tropical montane cloud forest; carbon 2010), we found the ratio of belowground: stocks.
Received 25 October 2009; accepted 12 August 2010 INTRODUCTION Author Contributions: AG, MRS, YM, JBF, and PM conceived of or It is now widely recognized that anthropogenic designed this study; AG, MRS, MZ, GCD, WRF, and KCG performed re- search; AG analyzed data; and AG, MRS, YM, and JBF wrote the paper. landuse can either contribute to climate change *Corresponding author; e-mail: [email protected] (through degradation) or mitigate climate change A. Gibbon and others
(through improved management of biosphere car- Hawaii; Weaver and Murphy 1990, Puerto Rico; bon stocks) (Denman and others 2007). The carbon Edwards and Grubb 1977, New Guinea) and also stocks and fluxes in above- and belowground from larger mountain ranges (Moser and others tropical forest components have been increasingly 2008, Ecuador; Kitayama and Aiba 2002, Borneo; studied in attempts to understand their roles in the Delaney and others 1997, Venezuela). Some site- global carbon cycle (Houghton and others 1998; specific studies have quantified carbon stock Malhi and Grace 2000) and their potential valua- changes when plantations or secondary succession tion in the newly created carbon markets and funds occurs on former cropland or pasture (Cavelier (Glenday 2006). Similarly, the size and dynamics of 1995, Columbia; Farley and others 2004, Ecuador; the above-, and, particularly, belowground carbon Fehse and others 2002, Ecuador). Likewise, some stocks of grasslands and pastures are being evalu- studies focusing on the impact of landuse on the ated as important components of the global carbon carbon stocks of high altitude grasslands have been cycle that are affected by human landuse (Scurlock conducted in the Andes (Pucheta and others 1998 and Hall 1998; Schuman and others 2002). and Adler and Morales 1999, both Argentina). In this article, we focused our attention on an However, an integrated carbon stock quantification ecotone with poorly documented carbon stocks and study across the upper treeline of a TMCF has not high sensitivity to human and climate change yet been conducted. pressure—the puna grassland–cloud forest transi- Carbon credits can be generated through the tion of the high Andes. Tropical montane cloud voluntary carbon market for avoided deforestation, forests (TMCFs) are most generally defined as for- afforestation/reforestation and through better ests ‘‘frequently covered by cloud or mists’’ management of grasslands (Hamilton and others (Stadtmuller 1987, p. 18) and represent about 2009). However, historically, the potential to 2.5% of the world’s tropical forests (Bubb and sequester carbon in high-altitude regions has been others 2004). TMCFs are characterized by stunted, neglected, as attention has focused on lowland bi- twisting trees, laden with ephiphytes and a species omes (Fehse and others 2002). assemblage that is significantly different from the This study, from Manu National Park, Peru, tropical forests of lower altitudes (Bruijnzeel and using a combination of field and remotely sensed Veneklaas 1998). data aimed to (1) quantify, at the landscape-scale, The base of the clouds that provide TMCFs with a the aboveground carbon stocks across the upper vital moisture source are anticipated to rise due to treeline of TMCFs into the puna grasslands—an climate change, this drying coupled with rising ecotone facing pressure from climate change and temperatures makes the TMCFs a vulnerable biome landuse, (2) assess the impact of vegetation type, (Foster 2001; Still and others 1999; Bush 2002). slope, altitude, grazing and fire on the distribution The predicted rate of climate change for this cen- of carbon stocks, (3) compare results to below soil tury will require species to migrate upslope at rates carbon data gathered by Zimmerman and others an order of magnitude greater than has been (2010) at the same sample points, and (4) identify experienced in the past 50,000 years to remain in possible management options and calculate their their climatic niche (Bush and others 2004). potential effects on the carbon stocks of the area. However, a second threat to some Andean TMCFs comes from the grazing and burning of puna grasslands above, which as well as degrading the METHODS aboveground vegetation and soil of the puna Site Description (Bustamante Becerra and Bitencourt 2007) are believed to contribute to an anthropogenically Manu National Park (a World Heritage Site) ex- constrained upper limit of the treeline (Braun and tends from the eastern slopes of the Andes into the others 2002; Sarmiento and Frolich 2002; Young lowland Peruvian Amazon (IUCN 2008). The park and Leo´ n 2007). border is defined by the watershed separating the Higher elevation carbon stores are less studied catchment basins of the Urubamba and Madeira than lowland areas, but are also under threat from rivers to the south and west, and the catchment of human disturbance and could potentially benefit the Manu River in the lowlands. The National Park from an influx of carbon financing (Fehse and boundary divides ownership of the high Andean others 2002). Some studies have quantified plateau between the communities to the west and aboveground, coarse root and soil carbon up alti- the National Park to the east (Bustamante Becerra tudinal gradients of montane forests from low- and Bitencourt 2007). The study area was at the altitude island mountains (Raich and others 1997, southern extent of the Manu’s western border on Andean Treeline Carbon Stocks, Manu NP, Peru
a mixture of shrubs and grasses dominated, and (3) upper TMCFs, where closed canopy trees and bam- boo dominated. Puna was predominant in the high elevation areas in the west of the study area from 4,061 m to the average treeline height of 3,450 m. The puna terrain was steeply rolling and moun- tainous, punctuated by occasional permanent and semi-permanent small lakes (up to 1 ha in area). Puna vegetation comprised grasses such as Jarava ichu Ruiz & Pav., Calamagrostis vicunarum (Wedd.) Pilg., Festuca dolichophylla J. Presl. with an average height of approximately 30 cm. Descending in altitude, the puna was replaced by a transition zone of 0.5–2.0 m high shrubs of genera including the dominants Baccharis (Asteraceae), Hypericum (Hyp- ericaceae), Lycopodium (Lycopodiaceae), Hesperom- eles (Rosaceae), Brachyotum (Melastomataceae), and Escallonia (Escalloniaceae). The shrubs had an average height of about 1 m. The transition zone was between 1 and 50 m in width, separating the puna from cloud forest, with terrain similar to that of the puna. Below the transition zone, tree species from the Figure 1. The bottom left inset shows the location of the Asteraceae, Cunoniaceae, Melastomataceae, Rosa- study area in central Peru. The top right inset shows the full study area running northwest to southeast along ceae, Rubiaceace, and bamboo in the genus Cusquea the southeastern border of Manu National Park. Dark dominated to comprise the upper TMCFs (referred gray areas were classified as forest and white areas as puna. to hereafter as ‘‘forest’’). Patches of primary suc- The main image shows the distribution of all plots as black cession indicated disturbance from landslides and circles with a white border. The Manu National Park some areas had suffered the impacts of fire started Border is shown as a black line that delimits the western in the puna. The understory had few shrubs and extent of puna classified and goes northeast across the herbaceous plants, and trees were festooned with lowland Amazon. vascular and non-vascular epiphytes (mainly bry- ophytes, ferns, bromeliaceae, ericaceae, and or- the Paucartambo mountain range (Figure 1). The chidaceae) with a high incidence of asteraceous study area was defined as those areas above vines. Most branches were covered in bryophytes. 3,000 m inside the park boundary, extending from The forest terrain was steeply sloping with rocky the southwest boundary of the park to a northern outcrops in places. limit at 12 21¢36¢¢S. An additional area of about A full description of the soil characteristics of the 3,500 ha contiguous with the SW corner of the study site can be found in Zimmerman and others park in the Wayqecha Valley was also included, (2010). Forest soils were characterized by an or- giving a surface area of the study area of approxi- ganic forest floor layer (Oh) of an average 22 cm mately 49,300 ha. with a high fine root density, overlaying a humic Rainfall averaged 1900–2500 mm annually Ah layer (11 cm) and a mineral B layer. Some across the study area, with a wet season from mineral forest soil layers contain mixed mineral October to April. Although no site-specific data layers with a high stone content as a result of an- were available, TMCFs can also receive significant cient landslides. Soil depths in the forest varied cloud water deposition inputs ranging from 0.2 to between 26 and 100 cm, with an average depth of 4mmday-1 (Bruijnzeel and Proctor 1995). Mean 44 cm. Transition zone soils were shallower and annual temperatures at 3,600 m were 11 C with had only a thin Oh layer of about 2 cm, followed by frosts being common on clear nights. Various clas- an average 17-cm thick A(h) layer. Soils in the sifications for the altitudinal transition of vegeta- transition zone were between 23 and 50 cm deep tion types existed for this area (Terborgh 1977; (36 cm on average). Puna soils had no Oh layers at Young and Leo´ n 2000). For the purpose of this all and consisted mainly of organic-rich A layers study, three land-cover classes were used: (1) puna, (19 cm on average) and stony B/C layers. The where grasses dominate (2) a transition zone, where average soil profile in the puna was 33 cm deep. A. Gibbon and others
The puna had been degraded due to grazing Trees and related seasonal burning and was classified as The diameter at breast height (dbh 1.3 m above a ‘‘Zone of Recovery’’ within Manu National ground height on uphill side of stem) and height Park; being identified as an area that had been, were measured for all stems (living and dead) with and continued to be, severely damaged and a height greater than 2 m and a dbh of greater than needed special management to recover (INRENA 1 cm. Where trees did not grow straight or per- 2002). pendicular to the ground, dbh was measured 1.3 m from the base along the main stem. The tree carbon Sampling Strategy data gathered in this study are referred to as data Aboveground carbon stocks were measured across set 1 (DS1). Tree dbh and height measurements the landscape with a stratified sampling regime, from plots comprising two additional data sets col- using methods adapted from De Castro and Ka- lected within the study area were also used, these uffman (1998). Random geographical points were are referred to as DS2 and DS3 (Table 1). In total, generated for the puna or transition zone close to 5.3 ha of forest data were used for the tree biomass the treeline based on a Landsat classification. At estimation from 27 sites. each point, a transect was established that des- Allometric equations were used to estimate bio- cended 100 m in elevation into the forest and mass from the field measurements. Although spe- ascended in increments of 100 m in elevation cies-specific equations were not available for the across the puna to the highest point in the local study area, Chave and others (2005) provided an landscape for a total of 55 points; 35 in the puna, equation based on a large pan-tropical multi-spe- 8 in the transition zone, and 12 in the forest cies data set for wet climates and recommended its (Figure 1). use for montane forests (equation (1)). To compare results from other commonly used allometries, Chave and others’ (2005) dbh only, wet climate Aboveground Carbon Estimation equation (2) was used. To allow further compari- At each sample point, tree, coarse woody debris son, Brown’s (1997) dbh only, wet climate equa- (CWD), and bamboo biomass were measured in tion (3) was used to calculate aboveground tree four 3 9 15 m plots arranged around the central, biomass. Brown’s equation, like Chave and others, randomly generated point. Within each of these was based on a large pan-tropical multi-species data plots, a 1 9 5 m plot was used for shrub biomass set which was not specifically designed for mon- measurement and a 0.5 9 0.5 m plot for litter/ tane regions, and when elevation was considered, moss/grass (LMG) layer biomass determination. An the study site met Brown’s definition of ‘‘wet.’’ additional LMG plot was located at the center of the Only trees with dbh greater than 5 cm were used in arrangement. The methods used to estimate the dry the biomass estimation due to limits in the appli- biomass for each pool are described below. Dry cability of allometric equations at lower dbh values. vegetative biomass was assumed to contain 50% AGB 0:0776 q 2 0:940 carbon (after Glenday 2006). h iest ¼ ð D HÞ ð1Þ
Table 1. The Data Sets Used to Measure the Tree Carbon Stocks of the Tree Pool from Within the Study Area
Data Plot Number Total area Minimum Site Source set area (ha) of plots sampled (ha) dbh measured selection
DS1 0.018 12 0.21 1 Random at 100 m This study altitude below the treeline DS2 0.1 11 1.10 2.5 Arbitrary close W. Farfan, K. Garcia, to treeline and M. Silman1 DS3 1 4 4.00 10 Located on ridge, M. Silman with 250 m gaps in elevation Total – 27 5.31 – – –
1Unpublished. Andean Treeline Carbon Stocks, Manu NP, Peru