Biome diversity in South Asia - How can we improve vegetation models to understand global change impact at regional level?

Kumar, Dushyant; Scheiter, Simon

doi:10.1016/j.scitotenv.2019.03.251

Cited by 25 publications

(36 citation statements)

References 243 publications

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“…Woody vegetation cover was projected to increase in most of the study area, except along the Himalayas and northern Indonesia (Yu et al., 2014). Using aDGVM, the predecessor of aDGVM2, we simulated substantial transitions from grasslands to savannas and from savannas to forests until 2100 in South Asia (Kumar & Scheiter, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…While the region is included in global‐scale DGVM simulations (e.g. Hickler, Prentice, Smith, Sykes, & Zaehle, 2006; Sato, Itoh, & Kohyama, 2007; Smith et al., 2014), studies explicitly focusing on this region are rare (Chaturvedi et al., 2011; Kumar & Scheiter, 2019; Ravindranath, Joshi, Sukumar, & Saxena, 2006). Accordingly, important features of vegetation at regional scale might not be well represented in global‐scale simulations.…”

Section: Introductionmentioning

confidence: 99%

“…These ecosystems are often misinterpreted as degraded forest, with afforestation being considered as appropriate conservation policy (Kumar, Pfeiffer, Gaillard, Langan, Martens, et al, 2020; Ratnam, Tomlinson, Rasquinha, & Sankaran, 2016). Models often simulate savanna areas as forest (Kumar & Scheiter, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Fourth, vegetation models require a capacity to represent the various vegetation types forming biomes of tropical Asia. Vegetation types such as bamboo thickets or mangroves are typically not included in DGVMs, and aDGVM2 does not simulate giant trees present in Asian forests Kumar and Scheiter (2019). proposed concepts on how to model these vegetation types.…”

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confidence: 99%

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Climate change promotes transitions to tall evergreen vegetation in tropical Asia

Scheiter

Kumar

Corlett

et al. 2020

Global Change Biology

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Climate change promotes transitions to tall evergreen vegetation in tropical Asia

Scheiter

Kumar

Corlett

et al. 2020

Global Change Biology

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“…Despite the demand of the scientific community for the inclusion of lianas in models (van der Heijden, Schnitzer, Powers, & Phillips, ; Kumar & Scheiter, ; McDowell et al, ; Phillips et al, ) and the increase in liana abundance in the Neotropics, no single dynamic global vegetation model (DGVM) so far includes lianas (Verbeeck & Kearsley, ). Given that an increasing amount of data on different aspects of liana ecology has emerged (Gianoli, ; Laurance et al, ; Schnitzer, ; Schnitzer & Bongers, ), we argue that now is the time to start building such models (Verbeeck & Kearsley, ).…”

Section: Introductionmentioning

confidence: 99%

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests

Brugnera

Meunier

Longo

et al. 2019

Global Change Biology

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There is mounting empirical evidence that lianas affect the carbon cycle of tropical forests. However, no single vegetation model takes into account this growth form, although such efforts could greatly improve the predictions of carbon dynamics in tropical forests. In this study, we incorporated a novel mechanistic representation of lianas in a dynamic global vegetation model (the Ecosystem Demography Model). We developed a liana‐specific plant functional type and mechanisms representing liana–tree interactions (such as light competition, liana‐specific allometries, and attachment to host trees) and parameterized them according to a comprehensive literature meta‐analysis. We tested the model for an old‐growth forest (Paracou, French Guiana) and a secondary forest (Gigante Peninsula, Panama). The resulting model simulations captured many features of the two forests characterized by different levels of liana infestation as revealed by a systematic comparison of the model outputs with empirical data, including local census data from forest inventories, eddy flux tower data, and terrestrial laser scanner‐derived forest vertical structure. The inclusion of lianas in the simulations reduced the secondary forest net productivity by up to 0.46 tC ha−1 year−1, which corresponds to a limited relative reduction of 2.6% in comparison with a reference simulation without lianas. However, this resulted in significantly reduced accumulated above‐ground biomass after 70 years of regrowth by up to 20 tC/ha (19% of the reference simulation). Ultimately, the simulated negative impact of lianas on the total biomass was almost completely cancelled out when the forest reached an old‐growth successional stage. Our findings suggest that lianas negatively influence the forest potential carbon sink strength, especially for young, disturbed, liana‐rich sites. In light of the critical role that lianas play in the profound changes currently experienced by tropical forests, this new model provides a robust numerical tool to forecast the impact of lianas on tropical forest carbon sinks.

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Estimation of Net Primary Productivity: An Introduction to Different Approaches

Burman

Kumar²

2020

Spatial Modeling in Forest Resources Management

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Biome diversity in South Asia - How can we improve vegetation models to understand global change impact at regional level?

Cited by 25 publications

References 243 publications

Climate change promotes transitions to tall evergreen vegetation in tropical Asia

Climate change promotes transitions to tall evergreen vegetation in tropical Asia

Modeling the impact of liana infestation on the demography and carbon cycle of tropical forests

Estimation of Net Primary Productivity: An Introduction to Different Approaches

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