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Data from: Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest

Cite this dataset

Newbery, David; Stoll, Peter (2021). Data from: Including tree spatial extension in the evaluation of neighbourhood competition effects in Bornean rain forest [Dataset]. Dryad.


Classical tree neighbourhood models use size variables acting at point distances. In a new approach here, trees were spatially extended as a function of their crown sizes, represented impressionistically as points within crown areas. Extension was accompanied by plasticity in the form of crown removal or relocation under the overlap of taller trees. Root systems were supposedly extended in a similar manner. For the 38 most abundant species in the focal size class (10 - <100 cm stem girth) in two 4-ha plots at Danum (Sabah), for periods P1 (1986-1996) and P2 (1996-2007), stem growth rate and tree survival were individually regressed against stem size, and neighbourhood conspecific (CON) and heterospecific (HET) basal areas within incremented steps in radius. Model parameters were critically assessed, and statistical robustness in the modelling set by randomization testing. Classical and extended models differed importantly in their outcomes. Crown extension weakened the relationship of CON effect on growth versus plot species’ abundance, showing that models without plasticity over-estimated negative density dependence. A significant negative trend of difference in CON effects on growth (P2 − P1) versus CON or HET effect on survival in P1 was strongest with crown extension. Model outcomes did not then support an explanation of CON and HET effects being due to (asymmetric) competition for light alone. An alternative hypothesis is that changes in CON effects on small trees, largely incurred by a drought phase (relaxing light limitation) in P2, and following the more shaded (suppressing) conditions in P1, were likely due to species-specific (symmetric) root competition and mycorrhizal processes. The very high variation in neighbourhood composition and abundances led to a strong ‘neighbourhood stochasticity’, and hence to largely idiosyncratic species’ responses. A need to much better understand the roles of rooting structure and processes at the individual tree level was highlighted.


1. Plot data for the tree neighbour modeling

The data presented here come from the two 4-ha permanent plots in lowland dipterocarp forest within the Danum Valley Conservation Area, Sabah, East Malaysian (NE Borneo), close to the Ulu Segama, set up and maintained for a study of long-term forest dynamics. Full details of the plots’ set-up, coordinates, site background, methods of enumeration, taxonomy, etc. are to be found in previous papers [1-3].

1] Lingenfelder, M. & Newbery, D. M. 2009 On the detection of dynamic responses in a drought-perturbed tropical rainforest in Borneo. Plant Ecology 201, 267-290.

[2] Newbery, D. M., Campbell, E. J. F., Lee, Y. F., Ridsdale, C. E. & Still, M. J. 1992 Primary lowland dipterocarp forest at Danum Valley, Sabah, Malaysia: structure, relative abundance and family composition. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences 335, 341-356.

[3] Newbery, D. M., Campbell, E. J. F., Proctor, J. & Still, M. J. 1996 Primary lowland dipterocarp forest at Danum Valley, Sabah, Malaysia. Species composition and patterns in the understorey. Vegetatio 122, 193-220.

2.  Output results from the regression modeling

These data tables are referenced, and linked to here, in Appendix S4 of the main paper. In the paper a complete explanation is found of the statistical data analysis. It is intended that these tables will be consulted in conjunction with reading the main paper.

Usage notes

1. Plot data for the tree neighbour modeling

The archived text file (nncrexm.inputData.csv) consists of comma-separated values for the following variables: ‘Plot’ – main plots 1 and 2 (MP1, MP2); ‘Tag’ – tree identification number (unique to plot); ‘X, Y’ – tree coordinate positions within each plot; ‘Code07’ – 8-character taxonomic code; ‘GBH86, GBH96, GBH01, GBH07’ – stem girths (in cm) at breast height [normally 1.3 m above ground] of trees ≥ 10 cm GBH, for the censuses of 1986, 1996, 2001 and 2007. Where the GBH is recorded as ‘0.0’ the tree had died in the preceding interval. Cells lacking values are indicated by ‘NA’s: they appear either at censuses before the one in which the tree was recruited, the census after which the tree died, or at the census ending the interval in which the tree regressed (its GBH became < 10 cm). In ‘Code07’ only those necessary are shown, namely the 48 selected focal tree species used in the present modelling work (they are listed with their full nomenclature in Appendix 1: Table S1 of the paper), otherwise coded as ‘NONFOCAL’. The data-table has 23382 rows (= trees). These data form the input to the crown extension programs stored at GitHub (see Appendix 2 of the paper for details) and the related neighbourhood regression modeling.

On tabulation here, the counts of focal trees (10 - < 100 cm gbh) per species at the start of each period, i.e. P1 or P2 (from GBH86 or GBH96 respectively), are the sums of counts of trees potentially usable for growth estimates (i.e. the survivors to end of the period) plus the counts of number of trees dying by the end of the period, as shown in Appendix S1: Table S1 of the paper.

2. Output results from the regression modeling

Four tables of the estimated coefficients, measures of statistical fit and significances, and best fitting radii, of the regression outcomes, for 48 species, non-spatial and two (‘removed’ and ‘relocated’) spatial models, and growth and survival responses in periods P1 and P2 (.xls files).

Table of the effect sizes for CON and HET terms in the non-spatial and all eight combinations of spatial models, for 48 species, and growth and survival responses in periods P1 and P2 (.xls file).

In these files, collected in '', fitted estimates and effect sizes for the CON and HET terms are given for all 48 species first considered. Of them, the first 38 (name codes in black) were selected and they formed the basis for the summaries, tables and graphs, at the species level, in the main paper. The last 10 species (name codes in red) were dropped. The eight-letter species codes in column 1 are explained in AppendixS1: Table S1.


Swiss National Science Foundation, Award: Grant 31003A–110250