A sub-canopy structure for simulating oil palm in the Community Land Model (CLM-Palm): phenology, allocation and yield

Abstract

Abstract. In order to quantify the effects of forests to oil palm conversion occurring in the tropics on land–atmosphere carbon, water and energy fluxes, we develop a new perennial crop sub-model CLM-Palm for simulating a palm plant functional type (PFT) within the framework of the Community Land Model (CLM4.5). CLM-Palm is tested here on oil palm only but is meant of generic interest for other palm crops (e.g., coconut). The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced so that each phytomer has its own prognostic leaf growth and fruit yield capacity but with shared stem and root components. Phenology and carbon and nitrogen allocation operate on the different phytomers in parallel but at unsynchronized steps, separated by a thermal period. An important phenological phase is identified for the oil palm – the storage growth period of bud and "spear" leaves which are photosynthetically inactive before expansion. Agricultural practices such as transplanting, fertilization and leaf pruning are represented. Parameters introduced for the oil palm were calibrated and validated with field measurements of leaf area index (LAI), yield and net primary production (NPP) from Sumatra, Indonesia. In calibration with a mature oil palm plantation, the cumulative yields from 2005 to 2014 matched notably well between simulation and observation (mean percentage error = 3 %). Simulated inter-annual dynamics of PFT-level and phytomer-level LAI were both within the range of field measurements. Validation from eight independent oil palm sites shows the ability of the model to adequately predict the average leaf growth and fruit yield across sites and sufficiently represent the significant nitrogen- and age-related site-to-site variability in NPP and yield. Results also indicate that seasonal dynamics of yield and remaining small-scale site-to-site variability of NPP are driven by processes not yet implemented in the model or reflected in the input data. The new sub-canopy structure and phenology and allocation functions in CLM-Palm allow exploring the effects of tropical land-use change, from natural ecosystems to oil palm plantations, on carbon, water and energy cycles and regional climate.

Representing agriculture in Earth System Models: Approaches and priorities for development

“…To better understand the biophysical impacts, Fan et al . [] developed specific growth and nutrient cycling parameterizations for the CLM4.5. Such developments enable a range of regional and global climate assessments pertinent to evaluating oil palm sustainability.…”

“…These parameterizations generally have dependencies on temperature, and use various growing degree day or heat accumulation formulations to determine the time to and the duration of particular growth phases. Many such crop PFTs and/or growth models have been developed, and can be as general as “temperate cereals” or as specific as oil palm [ Bondeau et al ., ; Osborne et al ., ; Lokupitiya et al ., ; Levis et al ., ; Fan et al ., ; Liu et al ., ]. For example, the Lund‐Potsdam‐Jena managed Land model (LPJmL)—a standalone DGVM—explicitly includes 13 agricultural PFTs, including 11 crops, and two managed grass types [ Bondeau et al ., ].…”

Minimum forest cover required for sustainable water flow regulation of a watershed: a case study in Jambi Province, Indonesia

“…In recent years, monoculture plantations have rapidly expanded in Southeast Asia, and the areas under oil palm (Elaeis guineensis) and rubber (Hevea brasiliensis) plantations are expected to increase further (Fox et al, 2012;Van der Laan et al, 2016). In Indonesia, which is currently the largest palm oil producer worldwide, the oil palm plantation area increased from 7000 km 2 in 1990 to 110 000 km 2 in 2015 (Ditjenbun, 2015;Tarigan et al, 2016b), and a further 170 000-200 000 km 2 is projected for future oil palm development (Colchester et al, 2006;Wicke et al, 2011;Afriyanti et al, 2016).…”

“…Although oil palm is of economic value to farmers and the local regions in which it is grown, it has received environmental and social criticism, often being held responsible for deforestation (Wicke et al, 2011;Vijay et al, 2016;Gatto et al, 2017), biodiversity loss (Fitzherbert et al, 2008;Koh and Wilcove, 2008;Wilcove and Koh, 2010;Carlson et al, 2012;Krashevska et al, 2015), decreased soil carbon stocks (Guillaume et al, 2015Pransiska et al, 2016), and increased greenhouse gas emissions (Allen et al, 2015;Hassler et al, 2017). Similarly, rubber plantations have environmental impacts such as reducing the soil infiltration capacity, accelerating soil erosion, increasing stream sediment loads (Ziegler et al, 2009;Tarigan et al, 2016b), and decreasing soil carbon stocks (Ziegler et al, 2011).…”

Reconciling Canopy Interception Parameterization and Rainfall Forcing Frequency in the Community Land Model for Simulating Evapotranspiration of Rainforests and Oil Palm Plantations in Indonesia

“…Fan et al () developed the CLM‐Palm model to simulate the canopy structure, growth, yield, and associated carbon, water, and energy cycles for oil palms within the framework of CLM4.5 (Oleson et al, ). CLM‐Palm inherits the canopy hydrological parameterization of CLM4.5, which was primarily designed for forest PFTs and optimized to global average patterns of ET under six‐hourly forcing (Lawrence et al, ).…”