Soil characteristics influence species composition and forest structure differentially among tree size classes in a Bornean heath forest

© 2019, Springer Nature Switzerland AG. Background and aims: Whilst several studies have shown that edaphic variability influences species composition in nutrient-poor tropical forests, the determinants of local species distributions and, in particular, how these change from younger to mature individuals in such forests are still under debate, and have been poorly explored in tropical heath forests that are among the least fertile tropical forest ecosystems. Methods: We investigated the influence of soil fertility and topography on a Bornean heath forest species composition, α-, β-diversity and tree size structure among size classes by recording all trees ≥1 cm DBH in 16 forest plots totalling 0.36 ha. Results: Tree species distributions generally followed gradients in available Al and soil depth; α- and β-diversity were linked to soil depth, and to some extent also to pH and the H:Al ratio. In contrast, forest structural attributes (basal area and stem density) were negatively correlated with both available and total P and a wider suite of soil nutrients, although trees ≥10 cm DBH were positively correlated with total P. Conclusion: Our study shows that heath forest species distribution, richness and structure is related to both edaphic and topographic characteristics and that soil acidity might have a strong influence in shaping these forests’ features. Among size classes, small trees are less influenced by soil and topography, whereas the sensitivity to these variables increases with tree size. We thus highlight that multiple edaphic factors influence different aspects of tropical forest structure, including different tree life stages, and species composition

Differences in soil properties among contrasting soil types in Northern Borneo

Soil in the tropics is high in diversity, and despite the diversity of Borneo's forest-soil associations, there is a paucity of data on its soil properties. We investigated the differences between three soil types in the Kabili-Sepilok Forest Reserve, Sabah, Malaysia, encompassing the contrasting alluvial, sandstone and heath forest typologies. We examined the distribution of nutrients between soil types and through soil depths, and assessed the extent of spatial autocorrelation in the three soil types. We confirmed the fertility gradient from alluvial to heath forest soil found by others. Soil elemental concentrations declined in deeper horizons with the exception of exchangeable sodium and aluminium that remained constant through alluvial and sandstone soil profiles. Spatial autocorrelation was present in all three soil types and strongest in the sandstone soil. Overall, we show how bedrock, erosion, leaching and topography influence soil properties across this mosaic of soil types and note their importance in influencing tree communities and their ecological functioning

The mechanical stability of the world’s tallest broadleaf trees

© 2020 The Authors. Biotropica published by Wiley Periodicals LLC on behalf of Association for Tropical Biology and Conservation The factors that limit the maximum height of trees, whether ecophysiological or mechanical, are the subject of longstanding debate. Here, we examine the role of mechanical stability in limiting tree height and focus on trees from the tallest tropical forests on Earth, in Sabah, Malaysian Borneo, including the recently discovered tallest tropical tree, a 100.8 m Shorea faguetiana named Menara. We use terrestrial laser scans, in situ strain gauge data and finite element simulations, to map the architecture of tall tropical trees and monitor their response to wind loading. We demonstrate that a tree's risk of breaking due to gravity or self-weight decreases with tree height and is much more strongly affected by tree architecture than by material properties. In contrast, wind damage risk increases with tree height despite the larger diameters of tall trees, resulting in a U-shaped curve of mechanical risk with tree height. Our results suggest that the relative rarity of extreme wind speeds in north Borneo may be the reason it is home to the tallest trees in the tropics. Abstract in MALAY is available with online material

The World's Tallest Tropical Tree in Three Dimensions

We would like to thank NERC for funding the airborne remote sensing campaign (HMTF grant NE/K016377/1 to the BALI consortium, YM, DC and DB) + direct access grant to MC, DSB, GM and DB), analyses (grants NE/P004806/1 to MC, DSB, GF, DB, GH, and NE/I528477/1 to GH, DSB, GF), and ground-based work (grant NE/P012337/1 to YM, MD and LPB); an ERC Advanced Investigator Award (321131) to YM for funding the UAV work; LAStools’ LASmoons program for a free academic license; and an Anne McLaren Research fellowship by the University of Nottingham to GH for funding the tree climbing. YM is supported by the Jackson Foundation. Data availability statement Generated Statement: The datasets generated for this study are available on request to the corresponding author.Peer reviewedPublisher PD

Logged tropical forests have amplified and diverse ecosystem energetics.

This is the final version. Available from Nature Research via the DOI in this record. Data availability: The per species energetics data and REM parameters (mammals) are available in Supplementary Data 1 and 2.Code availability: The code for processing and statistically analysing the data is available as Supplementary Methods. The REM analysis code is available from the corresponding author on reasonable request or from supplementary methods of ref. 38.Old-growth tropical forests are widely recognized as being immensely important for their biodiversity and high biomass1. Conversely, logged tropical forests are usually characterized as degraded ecosystems2. However, whether logging results in a degradation in ecosystem functions is less clear: shifts in the strength and resilience of key ecosystem processes in large suites of species have rarely been assessed in an ecologically integrated and quantitative framework. Here we adopt an ecosystem energetics lens to gain new insight into the impacts of tropical forest disturbance on a key integrative aspect of ecological function: food pathways and community structure of birds and mammals. We focus on a gradient spanning old-growth and logged forests and oil palm plantations in Borneo. In logged forest there is a 2.5-fold increase in total resource consumption by both birds and mammals compared to that in old-growth forests, probably driven by greater resource accessibility and vegetation palatability. Most principal energetic pathways maintain high species diversity and redundancy, implying maintained resilience. Conversion of logged forest into oil palm plantation results in the collapse of most energetic pathways. Far from being degraded ecosystems, even heavily logged forests can be vibrant and diverse ecosystems with enhanced levels of ecological function.Natural Environment Research CouncilNatural Environment Research CouncilSime Darby FoundationBat Conservation Internationa

Microclimate at SAFE Flux Tower

Microclimate at SAFE Flux Tower above and below canopy recorded with automatic datalogger Project: This dataset was collected as part of the following SAFE research project: Changing carbon dioxide and water budgets from deforestation and habitat modification XML metadata: GEMINI compliant metadata for this dataset is available here Files: This consists of 1 file: SAFE_FluxTower_MetData_2012-2017.xlsxMicroclimate at SAFE Flux Tower above and below canopy recorded with automatic datalogger Project: This dataset was collected as part of the following SAFE research project: Changing carbon dioxide and water budgets from deforestation and habitat modification XML metadata: GEMINI compliant metadata for this dataset is available here Files: This consists of 1 file: SAFE_FluxTower_MetData_2012-2017.xlsx

Changing carbon dioxide and water budgets from deforestation and habitat modification

SAFE Intensive Carbon Plots, part of the Global Ecosystem Monitoring (GEM) network, see http://gem.tropicalforests.ox.ac.uk/ Total soil respiration is measured at 25 points per plot, in the middle of each subplot (16 points per plot in OP, in subplot corners), using 12 cm diameter PVC collars inserted into approximately 5 cm depth Partitioned respiration is measured at four points per plot, a using a cluster of six collars (see below) Disturbance experiment in the plot centre All the methods and installation is described in detail in the GEM Intensive Carbon Plots manual, available at http://gem.tropicalforests.ox.ac.uk/files/rainfor-gemmanual.v3.0.pdf The aim is to measure monthly, but in practice the measurement interval is almost always longer (problems with access, staffing and instruments) EGM-4 infrared CO2 analyser and SRC-1 respiration chamber (PP Systems) Chamber closure time is 124 seconds, CO2 concentration inside the chamber is recorded every 5 s. Flux is calculated from the linear change in concentration in the chamber headspaceSAFE Intensive Carbon Plots, part of the Global Ecosystem Monitoring (GEM) network, see http://gem.tropicalforests.ox.ac.uk/ Total soil respiration is measured at 25 points per plot, in the middle of each subplot (16 points per plot in OP, in subplot corners), using 12 cm diameter PVC collars inserted into approximately 5 cm depth Partitioned respiration is measured at four points per plot, a using a cluster of six collars (see below) Disturbance experiment in the plot centre All the methods and installation is described in detail in the GEM Intensive Carbon Plots manual, available at http://gem.tropicalforests.ox.ac.uk/files/rainfor-gemmanual.v3.0.pdf The aim is to measure monthly, but in practice the measurement interval is almost always longer (problems with access, staffing and instruments) EGM-4 infrared CO2 analyser and SRC-1 respiration chamber (PP Systems) Chamber closure time is 124 seconds, CO2 concentration inside the chamber is recorded every 5 s. Flux is calculated from the linear change in concentration in the chamber headspace

Total and partitioned soil respiration and below-ground carbon budget in SAFE intensive carbon plots

This dataset contains two parts: 1) 'data' worksheet: measured soil respiration, values of individual measurements across all plots. 2) 'Soil C cycle' worksheet: calculated summaries of the components of the below-ground carbon cycle, including total and component soil respiration (this study), soil carbon pools and flows of organic carbon (previous studies). These data form the basis of the below-ground carbon cycle in Riutta et al 2021 GBC. This sheet contains mean values in each 1 ha carbon plot. This worksheet include two addititional carbon plots from Lambir Hills National Park (see Kho et al. 2013 JGR), which are not part of the SAFE Project. SAFE Intensive Carbon Plots, part of the Global Ecosystem Monitoring (GEM) network, see http://gem.tropicalforests.ox.ac.uk/. Total soil respiration is measured at 25 points per plot, in the middle of each subplot (16 points per plot in OP, in subplot corners), using PVC collars of 10.65 cm internal diameter, inserted into approximately 5 cm depth. Partitioned respiration is measured at four points per plot, a using a cluster of six collars (see below). Disturbance experiment in the plot centre to assess the potential bias on fluxes caused by the collar installation. All the methods and installation is described in detail in the GEM Intensive Carbon Plots manual, available at http://gem.tropicalforests.ox.ac.uk/files/rainfor-gemmanual.v3.0.pdf. The aim is to measure monthly, but in practice the measurement interval is almost always longer (problems with access, staffing and instruments). EGM-4 infrared CO2 analyser and SRC-1 respiration chamber (PP Systems). Chamber closure time is 124 seconds, CO2 concentration inside the chamber is recorded every 5 s. Flux is calculated from the linear change in concentration in the chamber headspace. Conversion from parts per million (ppm) of total gas volume per second per unit collar area to mega grams (1 Mg = 10^6 g) of carbon per hectare per month. Idea gas law: pV=nRT --> n=pV/(RT) Mass-Mole: n=m/M --> m=n*M Combined: m=MpV/(RT) p (constant) 101,325 R (constant) 8.314472 T temperature in Kelvins --> AirT_Use + 273.15 V headspace volume M_carbon 12.01 parts per million to absolute units 10^-6 A collar area, m2 0.008825 m2 to hectare 10^4 grams to megagrams 10^-6 seconds to months 2592000 Flux_MgCha-1month-1 = Slope_ppm_s-1 * M* p* V /(R*T) * 10^-6 / A * 10^4 * 10^-6 * 2592000 Soil collar codes Partitioned respiration C1 All soil respiration components: litter, roots, mycorrhiza, soil organic matter (SOM) C2 Roots excluded (litter, mycorrhiza, SOM) C3 Roots and mycorrhiza excluded (litter, SOM) S1 Litter excluded (roots, mycorrhiza, SOM) S2 Litter and roots excluded (mycorrhiza, SOM) S3 Litter, roots and mycorrhiza excluded (only SOM) D1 Double litter, roots, mycorrhiza, soil organic matter (SOM) D2 Roots excluded (double litter, mycorrhiza, SOM) D3 Roots and mycorrhiza excluded (double litter, SOM) X Organic layer of the soil removed Disturbance The purpose of the disturbance experiment is to quantify how much disturbance the removal of the roots and mixing the soil causes, compared to just hammering in the deep collar ND1 Roots severed, not removed and soil not mixed at the installation ND2 ND1-ND5 are replicates, same treatmet ND3 ND4 ND5 D1 Roots removed, soil mixed at the installation D2 D1-D5 are replicates D3 D4 D5 Project: This dataset was collected as part of the following SAFE research project: Changing carbon dioxide and water budgets from deforestation and habitat modification Funding: These data were collected as part of research funded by: Sime Darby Foundation (Grant, SAFE Core data) European Research Council Advanced Investigator Grant, GEM-TRAIT (Grant, Grant number 321131) NERC Human-Modified Tropical Forests Programme: Biodiversity And Land-use Impacts on tropical ecosystem function (BALI) Project (Grant, NE/K016369/1) NERC standard grant: The multi-year impacts of the 2015/2016 El Niño on the carbon cycle of tropical forests worldwide (Grant, NE/P001092/1) HSBC Malaysia (Grant) The University of Zurich (Grant) This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs. Permits: These data were collected under permit from the following authorities: Sabah Biodiversity Council (Research licence JKM/MBs.1000-2/2 JLD.6 (76)) XML metadata: GEMINI compliant metadata for this dataset is available here Files: This dataset consists of 2 files: SAFE_SoilRespiration_Data_SAFEdatabase_update_2021-01-11.xlsx, SAFE_soil_DATA.zip SAFE_SoilRespiration_Data_SAFEdatabase_update_2021-01-11.xlsx This file contains dataset metadata and 2 data tables: Soil respiration data (described in worksheet data) Description: Soil respiration data by individual measurements Number of fields: 21 Number of data rows: 20602 Fields: ForestType: Old-growth, Logged or Oil palm (Field type: categorical) SAFEPlotName: SAFE plot name (Field type: location) PlotName: Plot name (Field type: id) ForestPlotsCode: Plot code in the ForestPlots database (this should be used in publications, instead of plot name). OP plot is not in the ForestPlots database (ForestPlotsCode = NA) (Field type: id) Date: Measurement date (dd/mm/yyyy) (Field type: date) Observers: Observers (Field type: comments) Subplot: Subplot number within each plot, 1-25 (in OP, because the total respiration collars are in subplot corners, no subplot numbers are used, but the collars are refered to as SR1 - SR16. Subplot numbers are used for the partitioned respiration) (Field type: id) MeasurementType: Total, Partitioned or Disturbance (Field type: categorical) CollarType: Total; Partitioned: C1, C2, C3, S1, S2, S3, D1, D2, D3, X; Disturbance: ND1, ND2, ND3, ND4, ND5, D1, D2, D3, D4, D5 (see metadata description for codes) (Field type: id) EGM_RecordNumber: Record number in of the raw flux file. (Field type: id) SoilMoisture: Volumetric soil moisture content (% of pore space) next to the collar. measured with Campbell Scientific Hydrosense sensor with 12 cm rods. (Field type: numeric) SoilT: Soil temperature (°C) is measured with a handheld digital thermometer next to the collar, inserted into 10 cm depth (Field type: numeric) AirT: Air temperature (°C) is measured with a handheld digital thermometer outside the chamber, at the chamber height, in a shaded spot (Field type: numeric) Slope: Slope of the linear regression between time (seconds) from the chamber closure and CO2 concentration (parts per million, ppm) in the chamber headspace. (Field type: numeric) Remarks: Any notes in the field or at data entry stage. 0 = no remarks. If the measurement is repeated in the field multiple times, the other flux estimates are sometimes written in the remarks (not consistent). 2x, 3x etc. indicate multiple repeats. (Field type: comments) CollarHeight: Height from the top of the soil to the top of the collar, mm. This is used for calculating the total headspapce volume (chamber volume + collar volume above the soil surface). (Field type: numeric) HeadspaceVolume: Total headspace volume, sum of the chamber volume (0.001229 m3) and collar volume (d=0.106 m, h=CollarHeight_mm/1000) (Field type: numeric) AirT_Use: Gap filled air temperature data, missing air temperatures replaced with average temperature in logged (27.1), old-growth forest (26.2) and OP (28.7). This is needed for calculating the flux, but should not be used in response functions etc. (Field type: numeric) Flux: Flux corverted from ppm s-1 to Mg carbon per hectare per month. See conversion below. (Field type: numeric) Quality: 1 - good flux; 0 - missing data or bad measurement; 2 - outlier (Field type: numeric) Girdling_0_1: In Tower Plot (SAF-05), subplots 14-25, all trees were girdled in late January - early February 2016. Post-girdling data = 1, if no girdling = 0. (Field type: numeric) Soil carbon cycle (described in worksheet Soil C cycle) Description: Estimates of soil carbon pools (fine and coarse root biomass, root and litter necromass, soil organic carbon); fluxes of organic carbon into and respiration out of the different pools. Values are means for each intensive carbon plot. Number of fields: 41 Number of data rows: 11 Fields: ForestType: Old-growth, Logged or Oil palm (Field type: categorical) SAFEPlotName: SAFE plot name, as in the SAFE Gazetteer (Field type: location) PlotName: Plot name (used in field work) (Field type: id) ForestPlotsCode: Plot code, as in the ForestPlots database (this should be used in publications, instead of plot name) (Field type: id) SOC_0to100cm: Soil carbon stock, 0-100 cm layer (Field type: numeric) CanopyStock: Biomass stock of the canopy (Field type: numeric) LitterStock: Necromass stock of the litter layer (leaf, branch and reproductive litter) (Field type: numeric) NPP_Canopy: Canopy net primary productivity (Field type: numeric) CanopyHerbivory: Canopy herbivory (Field type: numeric) Litterfall: Canopy litterfall (leaves, reproductive parts, twigs < 2 cm diameter) (Field type: numeric) Frassfall1: Frassfall, 1st literature estimate (Field type: numeric) Frassfall2: Frassfall, 2nd literature estimate (Field type: numeric) Frassfall_Mean: Frassfall, mean of the Frassfall 1 and Frassfall 2 (Field type: numeric) FineRootStock: Fine root biomass stock (Field type: numeric) CoarseRootStock: Coarse root biomass stock (Field type: numeric) Delta_FRstock: Change in fine root biomass stock in logged forest (old-growth forest stock assumed to be in quasi-equilibrium) (Field type: numeric) Delta_CRstock: Change in coarse root biomass stock in logged forest (old-growth forest stock assumed to be in quasi-equilibrium) (Field type: numeric) NPP_FR: Fine root net primary productivity (Field type: numeric) NPP_CR: Coarse root net primary productivity (Field type: numeric) Mortality_FR: Fine root mortality (Field type: numeric) Mortality_CR: Coarse root mortality (Field type: numeric) R_Tot: Total soil respiration (litter, roots, mycorrhiza, soil organic matter) (Field type: numeric) R_SOM: Soil organic matter respiration (Field type: numeric) R_Litter: Litter layer respiration (Field type: numeric) R_Root: Root and priming respiration (Field type: numeric) R_Myc: Mycorrhizal respiration (Field type: numeric) R_Rhizosphere: Rhizosphere respiration (Field type: numeric) R_FRdebris: Fine root debris (recently dead, < 1 year) respiration (Field type: numeric) R_CRdebris: Coarse root debris (recently dead, < 1 year) respiration (Field type: numeric) R_RootTurnover: Root turnover respiration (sum of fine and coarse root debris respiration) (Field type: numeric) R_Het: Heterotrophic respiration (Field type: numeric) Exudation1: Root exudation, 1st literature estimate (Field type: numeric) Exudation2: Root exudation, 2nd literature estimate (Field type: numeric) Exudation3: Root exudation, 3rd literature estimate (Field type: numeric) Exudation4: Root exudation, 4th literature estimate (Field type: numeric) Exudation5: Root exudation, 5th literature estimate (Field type: numeric) Exudation_Mean: Root exudation, mean of the five literature-based estimates (Field type: numeric) LitterToSOM: Litter inputs (> 1 year old material) to soil organic matter (Field type: numeric) FRdebrisToSOM: Fine root debris inputs (> 1 year old material) to soil organic matter (Field type: numeric) CRdebrisToSOM: Coarse root debris inputs (> 1 year old material) to soil organic matter (Field type: numeric) OrgInputsToSOM: Total labile organic inputs (> 1 year old material) to soil organic matter (Field type: numeric) SAFE_soil_DATA.zip Description: Raw EGM files and a ReadMe doc explaining how to interpret Date range: 2011-08-25 to 2018-07-17 Latitudinal extent: 4.1830 to 5.0700 Longitudinal extent: 114.0190 to 117.820

Functional traits of tree species in old-growth and selectively logged forest

Traits matrix for tree species in selectively logged forest at SAFE and in old-growth forest in Danum Valley and Maliau Basin. Sampled during the BALI project traits campaign Project: This dataset was collected as part of the following SAFE research project: Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying functional trait distributions across the disturbance gradient Funding: These data were collected as part of research funded by: NERC (Standard grant, NE/K016253/1) This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs. Permits: These data were collected under permit from the following authorities: Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2.2(385))Traits matrix for tree species in selectively logged forest at SAFE and in old-growth forest in Danum Valley and Maliau Basin. Sampled during the BALI project traits campaign Project: This dataset was collected as part of the following SAFE research project: Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying functional trait distributions across the disturbance gradient Funding: These data were collected as part of research funded by: NERC (Standard grant, NE/K016253/1) This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs. Permits: These data were collected under permit from the following authorities: Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2.2(385)

Additional data for: Linking functional traits to multiscale statistics of leaf venation networks

Data are described in Blonder et al., Linking functional traits to multiscale statistics of leaf venation networks. New Phytologist (2020)