Distribution and characteristics of soil thickness and effects upon water storage in forested areas of Cambodia

Ohnuki, Yasuhiro; Kimhean, Chansopheaktra; Shinomiya, Yoshiki; Toriyama, Jumpei

doi:10.1002/hyp.6937

Cited by 35 publications

(37 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Cambodia is located in the center of the peninsula and still maintains relatively high forest coverage (59.1% in 2006) compared with adjacent countries in the same JARQ 51 (4) 2017 K. Tanaka et al thinner soil depth and drier soil conditions (Sakurai et al 1998, Toriyama et al 2011. Several researchers have been pointed out that a thicker soil depth with large water storage in DEF may allow leaf transpiration activity during the dry season, and consequently trees could maintain evergreen leaves (Murata et al 2012, Ohnuki et al 2008). Thus, drought stress for forest trees may be higher in DDF, which has smaller soil water storage as compared with DEF.…”

Section: Comparison Of Wood Density and Water Content Between Dry Evementioning

confidence: 99%

“…1). The soil type in DEF was primarily Acrisols based on FAO and WRB classification, and the depth of the soil layer reached 10 m (Ohnuki et al 2008).…”

Section: Study Sitementioning

confidence: 99%

“…1, Kenzo et al 2016c). The surface geology consisted of old sedimentary rocks and terrace gravel, and the soil type was Plinthosol according to the FAO classification: the depth of the soil layer ranged from 100 to 300 cm (Ohnuki et al 2008). Another DDF stand in Kampong Thom Province was also similar in terms of vegetation and environmental conditions.…”

Section: Study Sitementioning

confidence: 99%

See 2 more Smart Citations

Comparison of Wood Density and Water Content Between Dry Evergreen and Dry Deciduous Forest Trees in Central Cambodia

Tanaka

Sano

Yoneda

et al. 2017

JARQ

View full text Add to dashboard Cite

We compared wood density (WD) and water content (WC) between a dry evergreen forest (DEF) and dry deciduous forest (DDF) in central Cambodia. Wood core samples of 53 species from DEF and 54 species from DDF were collected. Average WD and WC in all species were similar between DEF (0.64 g/cm 3 of WD; 0.40 g/cm 3 of WC) and DDF (0.64 g/cm 3 of WD; 0.42 g/cm 3 of WC), although the average WC of five tree species that appeared in both forest types was higher in DDF than that in DEF. Tree size effects on WD and WC were negligible in both DEF and DDF. Intraspecific differences of those effects on WD and WC were also not observed in major canopy species in DDF and DEF, except for WD of Shorea obtusa in DDF, whose value increased with increasing tree diameter. Tree life-forms such as canopy, subcanopy, and understory species did not affect WD and WC in both forest types, although canopy gap species in DEF showed the smallest WD among the life-forms. The relationships between WD and WC in DEF and DDF were negatively correlated, and both regression equations did not differ between forest types. Overall, there were little differences on average WD and WC between DEF and DDF trees, even though their species composition and tree ecological traits were significantly different between forest types in central Cambodia.Discipline: Forestry and forest products Additional key words: Biomass, plant functional group, REDD+, wood specific gravity, Dipterocarpaceae IntroductionTropical dry forests occur in the Indochina Peninsula, which experiences severe dry spells, sometimes lasting several months without rainfall. In this region, there are two distinct types of dry forests in lowland areas (Ashton 2014, Hozumi et al. 1969, Ogawa et al. 1965, namely dry evergreen forests (DEF) and dry deciduous forests (DDF). Cambodia is located in the center of the peninsula and still maintains relatively high forest coverage (59.1% in 2006) compared with adjacent countries in the same This paper reports the results obtained in the project on "Estimation and simulation of carbon stock change of tropical forest in Asia

show abstract

Section: Comparison Of Wood Density and Water Content Between Dry Evementioning

confidence: 99%

“…1). The soil type in DEF was primarily Acrisols based on FAO and WRB classification, and the depth of the soil layer reached 10 m (Ohnuki et al 2008).…”

Section: Study Sitementioning

confidence: 99%

Section: Study Sitementioning

confidence: 99%

See 1 more Smart Citation

Comparison of Wood Density and Water Content Between Dry Evergreen and Dry Deciduous Forest Trees in Central Cambodia

Tanaka

Sano

Yoneda

et al. 2017

JARQ

View full text Add to dashboard Cite

show abstract

“…In particular, Cambodian lowland dry evergreen forest has unique biodiversity 61 and scarcity, because it has disappeared from other countries of the Indochina Peninsula due to the impact of human development 46 . Moreover, the lowland dry evergreen forest is eco-hydrologically unique due to the abundant groundwater supplied from a large area of the watershed 2,3,29 . By utilizing the groundwater resources stored in a thick soil layer (>10 m deep) 30 , year-round active stand transpiration is realized in these forests 6 even in a highly seasonal environment characterized by a 6-month dry season 28 .…”

Section: Introductionmentioning

confidence: 99%

“…Despite recent intensive investigations into Cambodian forest ecosystems 39 , especially concerning forest soil [47][48][49] , groundwater resource capacity 2,29,51 , and tree biomass C stock 20,38 , the linkage between above-and belowground C stock information remains scant 19,53 . Additionally, information on the effects of forest changes on soil properties mainly concern land-use conversion (e.g.…”

Section: Introductionmentioning

confidence: 99%

Physicochemical Surface-soil Properties after Litter-removal Manipulation in a Cambodian Lowland Dry Evergreen Forest

Ito

Toriyama²,

Araki³

et al. 2014

JARQ

Self Cite

View full text Add to dashboard Cite

Litter plays key roles in forest ecosystems, and forest degradation is likely to spur a further decline in leaf litterfall inputs to forest soils. However, the effects on physicochemical surface-soil properties remain largely unknown, especially in seasonal tropical forest ecosystems. We initiated a litterremoval manipulation experiment in a Cambodian lowland evergreen forest undergoing intensive selective logging. Litter removal performed for 2 and 4.4 years respectively triggered an increase in bulk density and decrease in surface-soil carbon (C) and nitrogen (N) contents to 67 and 73% of the original levels, respectively. After only 2 years of treatment, bulk density rose to very high value (>1.40 Mg m -3 ) likely preventing further soil compaction, while the C and N reduction effects lasted over 2 years. Greater soil compaction occurs in stands with a smaller initial bulk density. However, C (N)-rich soils did not necessarily lose a greater relative proportion of C (N) than C (N)-poor soils. Although N remained above C following the litter removal, conservative trends in the C:N ratio suggested a limited capacity for N retention. Together, our data suggest that shifts in leaf litter inputs in response to localized human disturbances may have rapid and lasting consequences on physicochemical surface-soil properties; possibly accelerated by a tropical climate. Moreover, a speedy recovery to an adequate litter supply, at least before reaching the upper soil compaction limit, is essential to conserve forest ecosystems.

show abstract

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

Gomes

Vrugt

Vargas

2016

Water Resources Research

View full text Add to dashboard Cite

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom-up control hypothesis using high-resolution topographic data Abstract The depth to bedrock controls a myriad of processes by influencing subsurface flow paths, erosion rates, soil moisture, and water uptake by plant roots. As hillslope interiors are very difficult and costly to illuminate and access, the topography of the bedrock surface is largely unknown. This essay is concerned with the prediction of spatial patterns in the depth to bedrock (DTB) using high-resolution topographic data, numerical modeling, and Bayesian analysis. Our DTB model builds on the bottom-up control on freshbedrock topography hypothesis of Rempe and Dietrich (2014) and includes a mass movement and bedrock-valley morphology term to extent the usefulness and general applicability of the model. We reconcile the DTB model with field observations using Bayesian analysis with the DREAM algorithm. We investigate explicitly the benefits of using spatially distributed parameter values to account implicitly, and in a relatively simple way, for rock mass heterogeneities that are very difficult, if not impossible, to characterize adequately in the field. We illustrate our method using an artificial data set of bedrock depth observations and then evaluate our DTB model with real-world data collected at the Papagaio river basin in Rio de Janeiro, Brazil. Our results demonstrate that the DTB model predicts accurately the observed bedrock depth data. The posterior mean DTB simulation is shown to be in good agreement with the measured data. The posterior prediction uncertainty of the DTB model can be propagated forward through hydromechanical models to derive probabilistic estimates of factors of safety.

show abstract

Distribution and characteristics of soil thickness and effects upon water storage in forested areas of Cambodia

Cited by 35 publications

References 17 publications

Comparison of Wood Density and Water Content Between Dry Evergreen and Dry Deciduous Forest Trees in Central Cambodia

Comparison of Wood Density and Water Content Between Dry Evergreen and Dry Deciduous Forest Trees in Central Cambodia

Physicochemical Surface-soil Properties after Litter-removal Manipulation in a Cambodian Lowland Dry Evergreen Forest

Toward improved prediction of the bedrock depth underneath hillslopes: Bayesian inference of the bottom‐up control hypothesis using high‐resolution topographic data

Contact Info

Product

Resources

About