Large-sized trees and altitude drive aboveground carbon stock in Brazilian Atlantic Cloud Forests: An approach based on carbon hyperdominant taxa.

Tropical montane forests (TMFs) play an important role as a carbon reservoir at a global scale. However, there is a lack of a comprehensive understanding on the variation in carbon storage across TMF compartments [namely aboveground biomass (AGB), belowground biomass (BGB), and soil organic matter] along altitudinal and environmental gradients and their potential trade-offs. This study aims to: 1) understand how carbon stocks vary along altitudinal gradients in Andean TMFs, and; 2) determine the influence of climate, particularly precipitation seasonality, on the distribution of carbon stocks across different forest compartments. The study was conducted in sixty 0.1 ha plots along two altitudinal gradients at the Podocarpus National Park (Ecuador) and Río Abiseo National Park (Peru). At each plot, we calculated the amount of carbon in AGB (i.e. aboveground carbon stock, AGC), BGB (i.e. belowground carbon stock, BGC), and soil organic matter (i.e. soil organic carbon stock, SOC). The mean total carbon stock was 244.76 ± 80.38 Mg ha–1 and 211.51 ± 46.95 Mg ha–1 in the Ecuadorian and Peruvian plots, respectively. Although AGC, BGC, and SOC showed different partitioning patterns along the altitudinal gradient both in Ecuador and Peru, total carbon stock did not change with altitude in either site. The combination of annual mean temperature and precipitation seasonality explained differences in the observed patterns of carbon stocks across forest compartments between the two sites. This study suggests that the greater precipitation seasonality of colder, higher altitudes may promote faster turnover rates of organic matter and nutrients and, consequently, less accumulation of SOC but greater AGC and BGC, compared to those sites with lesser precipitation seasonality. Our results demonstrate the capacity of TMFs to store substantial amounts of carbon and suggest the existence of a trade-off in carbon stocks among forest compartments, which could be partly driven by differences in precipitation seasonality, especially under the colder temperatures of high altitudes.

Tree-size dimension inequality shapes aboveground carbon stock across temperate forest strata along environmental gradients

The importance of terrestrial ecosystems for carbon sequestration and climate regulation is acknowledged globally. However, the underlying structural drivers are still not well understood, particularly across distinct tropical forest ecosystems where trees species have different growth habits and potential to reach different maximal size. In particular, how important are different tree size classes in contributing to stand aboveground carbon (AGC) remains unclear across forest ecosystems. Here, we hypothesized that (i) tree size classes would contribute differently to stand AGC across forest ecosystems; and (ii) few species, possibly dominant, would determine most of stand AGC. We tested these hypotheses using a 17-ha sampled inventory data from gallery forests, woodlands and savannahs in the Republic of Benin. We examined (i) how AGC stocks vary among small- (<20 cm), medium- (20–40 cm) and large-size (>40 cm diameter at breast height - dbh) trees; (ii) how the large size class and its individual species contribute to AGC; and (iii) how size class-based taxonomic and structural variables influence AGC?Stand AGC was 23 ± 5, 30 ± 8 and 42 ± 12 MgC ha−1 in savannah, woodland and gallery forest, respectively. There were significant main and interaction effects of vegetation types and size classes. As expected, medium and large-size classes contained more of the AGC, irrespective of the vegetation type. However, gallery forests had the lowest AGC in the <20 cm dbh class, but higher values in medium- and large-size classes as compared to woodlands and savannahs. The top 10 species contributed 82%, 89% and 91% of AGC in gallery forests, woodlands and savannahs, respectively. In addition, five of the top 10 dominant species were shared by the three vegetation types and alone contributed 70–76% of AGC. Tree basal area was the most constant structural attribute influencing AGC; however, its influence shifted with vegetation type and size class, with greater effects of large-size tree basal area in gallery forests, and of medium trees and small trees’ basal area in woodlands and savannahs, respectively. The study shows that (i) AGC allocation to size class varied across vegetation types, and (ii) small and medium trees are also important in predicting AGC, especially in semi-arid environments dominated by high densities of small-size trees (e.g. woodlands and savannahs). It also highlights the importance of few dominant species in contributing a large proportion of AGC stocks. The conservation of these dominant species is essential to avoid substantial decline of AGC stock.

Despite the importance of agroforestry parkland systems for ecosystem and livelihood benefits, evidence on determinants of carbon storage in parklands remains scarce. Here, we assessed the direct and indirect influence of human management (selective harvesting of trees), abiotic factors (climate, topography, and soil) and multiple attributes of species diversity (taxonomic, functional, and structural) on aboveground carbon (AGC) stocks in 51 parklands in drylands of Benin. We used linear mixed-effects regressions and structural equation modeling to test the relative effects of these predictors on AGC stocks. We found that structural diversity (tree size diversity, HDBH) had the strongest (effect size β = 0.59, R2 = 54%) relationship with AGC stocks, followed by community-weighted mean of maximum height (CWMMAXH). Taxonomic diversity had no significant direct relationship with AGC stocks but influenced the latter indirectly through its negative effect on CWMMAXH, reflecting the impact of species selection by farmers. Elevation and soil total organic carbon content positively influenced AGC stocks both directly and indirectly via HDBH. No significant association was found between AGC stocks and tree harvesting factor. Our results suggest the mass ratio, niche complementarity and environmental favorability as underlying mechanisms of AGC storage in the parklands. Our findings also highlight the potential role of human-driven filtering of local species pool in regulating the effect of biodiversity on AGC storage in the parklands. We conclude that the promotion of AGC stocks in parklands is dependent on protecting tree regeneration in addition to enhancing tree size diversity and managing tall-stature trees.

Species diversity and stand structural diversity of woody plants predominantly determine aboveground carbon stock of a dry Afromontane forest in Northern Ethiopia

Woody plant species in homegarden agroforestry store a large proportion of carbon stocks. However, there is limited information on the carbon stock potential of homegarden agroforestry along altitudinal gradients in southwest Ethiopia. Therefore, this study aims to estimate aboveground and belowground carbon stocks in homegardens using a non-destructive allometric model. Data were collected from 72 homegardens selected using a random sampling method. Woody plants were measured for diameter at breast height (DBH) of ≥ 5 cm and height of ≥ 1.5 m. The study revealed that the mean aboveground carbon stock (14.39 ± 2.95 Mg C ha−1) was significantly (p &amp;lt; 0.05) higher in the middle altitude than (6.12 ± 0.72 Mg C ha−1) in the low altitude. Carbon stocks were significantly different between middle and low altitudes. The overall mean carbon stock was 11.25 ± 1.60, with mean aboveground and belowground carbon stocks of 9.39 ± 1.34 and 1.88 ± 0.27 Mg C ha−1, respectively. The top 10 woody species contributed to 78.50% of the total carbon stock, of which 56.73% were Persea americana and Cordia africana. Wealth status and size of homegardens were significantly correlated (r = 0.298 and r = 0.307, respectively) with the carbon stock. The overall woody carbon stock distributions varied primarily due to altitudinal gradients, woody species, and socioeconomic factors. As a result, this study will assist researchers and policymakers in selecting optimal ecological areas and addressing socioeconomic gaps for agroforestry practices that produce biomass and store carbon for long-term climate change mitigation.

Quantifying the variability and allocation patterns of aboveground carbon stocks across plantation forest types, structural attributes and age in sub-tropical coastal region of KwaZulu Natal, South Africa using remote sensing

Human activities in the tropics, particularly large-scale deforestation, significantly contribute to rising greenhouse gas emissions. The carbon storage capacity of the Atlantic Forest, specifically in seasonal forests, needs to be better understood. Therefore, we analyzed the aboveground carbon stock (AGC) in a semideciduous seasonal forest (SSF) remnant in southeastern Minas Gerais through comprehensive vegetation inventory and wood density sampling. The 20 species that counted for half of the total basal area corresponded to a surprising AGC of 58.05 Mg.ha-1. The AGC found is similar to other studies in second-growth SSF, especially the ones with no recent record of human disturbance. However, besides the natural process of increasing AGC in forests over the years, long-term decreasing trends in other forest ecosystems in Brazil have already been reported. Future long-term studies are crucial to understanding how the forest carbon stock will respond to the ongoing environmental and climate change scenario.

Studying community phylogenies along elevation gradients can inform us about the influences of environmental conditions on the structuring communities, and therefore allow predictions on how future environmental changes may affect them. The aim of the work was to evaluate the processes that govern tree communities along an altitudinal gradient in an upper montane Atlantic Forest in the Mantiqueira Range, southeastern Brazil. To do so, we analyzed the phylogenetic structure of angiosperm tree communities in four elevations (ranging from 1500 to 2100 m) and verified if it varies significantly with altitude. We also analyzed the phylogenetic beta diversity among local angiosperm tree communities along the altitudinal gradient. Further, we evaluated the soil and temperature influences over these communities. The results showed tendency of increasing phylogenetic clustering with the elevation. We also verified that the phylogenetic lineages of the tree communities are replaced along the altitudinal gradient influenced by changes in temperature and soil, indicating phylogenetic niche conservatism. This suggest that these communities could move to higher altitudes in a global warming scenario, and that would change their species composition and abundance due to changes in soil along the altitudinal gradient. Thus, the highest areas would be threatened as they would not have higher altitude locations to migrate to. In addition, phylogenetic lineages which only occur, or occur in their large majority, at highest altitudes (i.e., Cunoniaceae and Winteraceae) would be locally extinct by the current (or future) climatic scenario.

This chapter analyses the climatic conditions prevailing at sites where tropical montane cloud forests (TMCF) have been reported. Spatial data‐sets of climate were used to describe the climate at 477 cloud forest sites identified by United Nations Environment Program (UNEP)‐WCMC. Some 85% of the sites are found at altitudes between 400 and 2800 m a.s.l., with an average altitude of 1700 m. The range of altitudes at which cloud forests are found is extensive (220–5005 m). The climate of cloud forests is highly variable from site to site, with an average rainfall of ∼2000 mm year−1 and an average temperature of 17·7 °C. In addition, cloud forests are found in seasonal and aseasonal environments alike, both in terms of rainfall and temperature. There are some clear differences in the climates of cloud forests found in Africa, Latin America and the Caribbean, and those in Asia. Cloud forests are found to be wetter (with incident rainfall being 184 mm year−1 higher on average), cooler (by 4·2 °C on average), and less seasonally variable than other montane forests not affected significantly by fog and low cloud. Cloud forests are also almost completely confined to a zone within 350 km from the nearest coast. Finally, the climatic representativity of 14 intensively studied cloud forest sites (ISS) was analysed, as a group, the sites provided a fair representation of the climates found in cloud forests, evenly covering the ranges in temperature and rainfall. The majority of cloud forest sites occur in regions with 2000–2600 mm of rainfall and annual mean temperatures (Tmean) of 14–18 °C. Relatively dry cloud forest sites (&lt;1000 mm of rain year−1) are under‐represented in the UNEP‐WCMC data‐base. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Carbon and biodiversity cobenefits of second-growth tropical forest: The role of leaf phenology

In forests, a few large trees (L-trees) versus small–medium trees (S-trees) are often considered the major reservoir of aboveground carbon stock (AGCS). Here, we hypothesize that tree species’ functional strategies regulate AGCS by tree sizes in temperate deciduous forests across local scale environmental gradients. Using data from 99 plots, we modelled the multivariate effects of the tree-based (tree diversity, stand density and multidimensional tree size inequality) versus the trait-based (multi-trait diversity and single-trait dominance) attributes of L-trees versus S-trees, along topographic and soil conditions, to predict AGCS through four L-trees threshold size (i.e., ≥ 50 cm fixed-diameter, top 95th percentile, ≥ top 50% cumulative AGCS descending-ranked ordered, and mean threshold size) approaches. The tree-based and trait-based attributes of L-trees and S-trees shaped species co-occurrence processes but L-trees regulated AGCS more effectively (31.29–93.20%) than S-trees and abiotic factors across four thereshold size approaches and two concepts. Although L-trees threshold size and tree-based attributes mattered for AGCS, the dominant resource-acquisitive strategy of structurally complex L-trees having higher specific leaf area but lower leaf dry matter content and lesser multi-trait dispersion could promote AGCS better than the resource-conservative strategy (low specific leaf area) of S-trees. Capturing tree species’ functional strategies, synergies and trade-offs across tree sizes can enhance our understanding of how to achieve nature-based carbon neutrality and lessen climate change. Thus, forest management and restoration initiatives should prioritize high-functioning tree species with dominant productive traits while conserving multi-trait diversified species in temperate deciduous forests.

The correct estimation of forest aboveground carbon stocks (AGCs) allows for an accurate assessment of the carbon sequestration potential of forest ecosystems, which is important for in-depth studies of the regional ecological environment and global climate change. How to estimate forest AGCs quickly and accurately and realize dynamic monitoring has been a hot topic of research in the forestry field worldwide. LiDAR and remote sensing optical imagery can be used to monitor forest resources, enabling the simultaneous acquisition of forest structural properties and spectral information. A high-density LiDAR-based point cloud cannot only reveal stand-scale forest parameters but can also be used to extract single wood-scale forest parameters. However, there are multiple forest parameter estimation model problems, so it is especially important to choose appropriate variables and models to estimate forest AGCs. In this study, we used a Duraer coniferous forest as the study area and combined LiDAR, multispectral images, and measured data to establish multiple linear regression models and multiple power regression models to estimate forest AGCs. We selected the best model for accuracy evaluation and mapped the spatial distribution of AGC density. We found that (1) the highest accuracy of the multiple multiplicative power regression model was obtained for the estimated AGC (R2 = 0.903, RMSE = 10.91 Pg) based on the LiDAR-estimated DBH; the predicted AGC values were in the range of 4.1–279.12 kg C. (2) The highest accuracy of the multiple multiplicative power regression model was obtained by combining the normalized vegetation index (NDVI) with the predicted AGC based on the DBH estimated by LiDAR (R2 = 0.906, RMSE = 10.87 Pg); the predicted AGC values were in the range of 3.93–449.07 kg C. (3) The LiDAR-predicted AGC values and the combined LiDAR and optical image-predicted AGC values agreed with the field AGCs.

Altitudinal gradients, among other abiotic factors, are directly linked to species’ diversity patterns and distributions. Another important factor to be considered is the geographic position of a mountain chain, with oceanic and continental-facing slopes having distinct environmental conditions reflected in distinct phytophysiognomies. We examined the distributions of species of Passifloraceae sensu stricto along an altitudinal gradient (varying from 300 to 2,199 m.a.s.l.) in the Serra dos Órgãos National Park (PARNASO) in Rio de Janeiro state, southeastern Brazil. Field excursions were undertaken to record and collect specimens. Maps were prepared of the distribution of sampling efforts, taking into consideration altitudinal gradients and rainfall. The statistical analysis was made to define the patterns of richness and abundance within the altitudinal classes. Analyses of similarity, grouping and NMDS were made of the oceanic and continental slopes. A total of 19 species of Passifloraceae s.s. were encountered. The greatest species richness was found at intermediate elevations (1,100–1,300 m.a.s.l). The similarity index between the two exposure slopes was 28%, indicating distinct species compositions on different faces. Our data helps to define the distribution and species composition of Passifloraceae s.s. within the PARNASO, and should be useful for conservation actions there.

Planting forests is an important practice for climate change mitigation, especially in the tropics where the carbon (C) sequestration potential is high. Successful implementation of this mitigation practice requires knowledge of the role of species identity and diversity on carbon accrual of plantations. Despite this need, solid data on the long‐term development of forest plantations are still very scarce. Monospecific and two species mixture plots of a 77‐year‐old tree diversity experiment in Yangambi in the Congo basin were fully inventoried. We calculated above‐ground C stocks using allometric equations, and soil C stocks by analyzing soil samples at multiple depths. Linear mixed effects models were used to analyze the effect of taxonomic and functional identity and diversity on the aboveground and soil carbon stocks. A high variability in aboveground C stocks across tree species combinations was observed. Apart from a species identity effect, the proportion of planted species in the total stand basal area (BApl) and effective species richness were identified as compositional parameters with a significant effect on the aboveground carbon (AGC), with BApl being more important. Both AGC and BApl were coupled to the functional identity of the planted species; the planting of short‐lived pioneers led to low AGC. We found no clear benefits, but also no drawbacks, for AGC of two species mixture plots over monospecific plots or including nitrogen fixing species in the plantation scheme. However, the latter was the only compositional parameter with a significant positive effect on the soil carbon stock up to 1 m depth. We conclude that the different plantation configurations gave rise to a wide range in carbon stocks. This was predominantly caused by large differences in AGC sequestration over the past 77 years. Altogether, short‐lived pioneer species had a low BApl resulting in low carbon sequestration, while partial shade tolerant species achieved the highest AGC stocks. Tolerating spontaneous ingrowth during the plantation development can further increase the AGC stock, given that the appropriate functional type is planted.