Vegetation responses to burning in a rain forest in Borneo

See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/216786702 Vegetation responses to burning in a rain forest in Borneo Article in Plant Ecology · April 2005 DOI: 10.1007/s11258-005-2107-0 CITATIONS READS 20 63 2 authors, including: Daniel Francis Richard Cleary University of Aveiro 129 PUBLICATIONS 2,038 CITATIONS SEE PROFILE All content following this page was uploaded by Daniel Francis Richard Cleary on 18 December 2013. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original document and are linked to publications on ResearchGate, letting you access and read them immediately. Plant Ecology (2005) 177: 145–163 DOI 10.1007/s11258-005-2107-0
Springer 2005 Vegetation responses to burning in a rain forest in Borneo Daniel F.R. Cleary1,2,* and Aldrianto Priadjati1,3 1 Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, P.O. Box. 94766, 1090 GT Amsterdam, the Netherlands; 2National Museum of Natural History ‘Naturalis’, P.O. Box 9517, 2300 RA Leiden, the Netherlands; 3BOS–Samboja Lestari, The Borneo Orangutan Survival Foundation (BOS), P.O. BOX 500, Balikpapan, 76100, Indonesia, email: [email protected]; *Author for correspondence (e-mail: [email protected], [email protected] or [email protected]) Received 1 February 2003; accepted in revised form 10 May 2004 Key words: Borneo, Disturbance, ENSO (El Niño Southern Oscillation), Fire, Indonesia, Kalimantan, Regeneration, Succession Abstract During the 1997/98 ENSO (El Niño Southern Oscillation) event more than 5 million ha of East Kalimantan, Indonesia burned. Here we quantify the initial stages of regeneration (1998–2001), both in forest that burned and in unburned controls. Sapling and seedling density and species richness remained significantly lower in burned than in unburned forest and community composition remained substantially different between both forest types throughout the sampling period. The only pronounced edge effect was a significantly higher density of seedlings in the interior of unburned forest. Sapling density increased and seedling density declined in both unburned and burned forest during the four-year study period. In the unburned forest, sapling and seedling species richness remained stable, but sapling species richness declined significantly with time in the burned forest. The pioneer community in the burned forest was, furthermore, characterisedby higher growth and recruitment than in the unburned forest but mortality did not differ between both forest types. Differences in environment (burned versus unburned: 29–65% of variation explained) and the distance between sample sites (13–23% of variation explained) explained substantial amounts of variation in sapling and seedling community similarity. Similarity was, however, only marginally (< 1% explained) related to the edge position and temporal variation (difference among sample events). Our results, four years after the initial burn, indicate that burned forest still differed greatly from unburned forest in terms of density, species richness and community composition. There was also no clear trend of a return to pre-disturbance conditions, which indicates that the burned forest may remain in a severely degraded state for a prolonged period of time. Introduction In 1997 and 1998 record-breaking fires occurred in forested areas of Indonesia and Brazil that are normally considered too moist to burn (Abramovitzand Dunn1998). While the moist microclimate of a closed forest naturally limits fires, anthropogenic alteration can cause microclimatic shifts that make fire both possible and likely (Uhl and Kauffman1990). Forest can initially be affected by human activities, such as logging, or slash-andburn agriculture, which creates areas especially susceptible to burning due to canopy opening, forest soil desiccationand the accumulation of burnable debris (Nepstad et al. 1998). Recent fires are therefore primarily associated with human activity and especially with forest edges. Undisturbed forest, on the contrary, is highly resilient to 146 fires because the trees can effectively trap transpired moisture thereby increasing ambient forest humidity (Cochrane 2003). A matrix that facilitates burns along forest edges will eventually lead to forest degeneration as the edge recedes following accidental and intentional burns (Gascon et al. 2000). During severe drought, fire can spread from these disturbed matrices into undisturbed, virgin forest where it will creep over the ground and destroy most of the vegetation in its path. Both logging and fire increase the vulnerability of affected forest to future burning. Post-disturbance vegetation patterns have, for example, been shown to influence subsequent disturbance events in addition to species dispersal, and ecosystem processes including nutrient cycling (Tilman 1999; Adler et al. 2001). By altering vegetation patterns, large-scale disturbances can have a pronounced impact on ecosystem functioning (Tilman 2000). Large areas of forest are burned every year, and this can take on catastrophic proportions in certain periods (e.g., 1982/83 and 1997/98) when severe ENSO events alter the normal climatological conditions prevalent in many tropical regions such as Borneo. During severe ENSOepisodes net carbon emissions to the atmosphere can double (Nepstadet al. 1999). There is, furthermore, evidence that ENSOevents are increasing in both strength and duration as a result of global warming (Trenberth and Hoar 1996). Relatively little is, however, known about rainforest regeneration following severe ENSO-induced fires. Clark and Clark (1992)suggest that in order to understand the processes affecting regeneration of tropical forest trees much more attention should be paid to seedling and small sapling stages. Seedlings and saplings also show the greatest response to fire in terms of mortality and regeneration. Although the fireline intensity of tropical fires is very low it is nonetheless deadly because it tends to burn at the base of contacted trees for long periods (Cochrane and Schulze1999). Most tropical trees are characterised by thin bark (Uhl and Kauffman 1990) so that they are very sensitive to damage by fire. The thickness of the bark is also diameter dependent, which is why smaller trees (i.e., seedling and saplings) are more susceptible to fire than larger conspecifics(Cochrane1998). Understanding patterns of succession in recently burned landscapes is crucial for predicting the probability of future burn events. In logged forest, for example, gap size is positively related to the rate at which a forest becomes susceptible to fire. This susceptibility declines over time as gaps become densely packed with saplings so that four years after logging, conditions in a logged forest can resemble those in virgin forest (Holdsworth and Uhl1997). Sapling composition in logging gaps and burned forest may, however, differ substantially and primary-like conditions may not be replicated as rapidly in burned forest. With this study we aim to: 1. Compare growth, mortality, recruitment and sapling and seedling density during five sampling events (1998–2001) in edge and interior sectors of unburned and burned forest. 2. Compare sapling and seedling species richness during five sampling events (1998–2001) in unburned and burned forest. 3. Determine whether sapling and seedling community similarity are significantly related to environmental variables associated with burning, edge, vegetation density and sampling event and/or the geographic distance between sampling sites. Materials and methods Field site Our focal research area was the Sungai Wain Protected Forest Reserve (1.16 S, 116.54 E) in the Balikpapan-Samarinda region of East Kalimantan Indonesia (Figure 1). The reserve is strictly protected by law, which prohibits all forms of economic activity within officially recognised boundaries. During the 1997/98 ENSO event two thirds (approximately 6500 ha) of the reserve burned. The forest fires destroyed most of the affected forest with some small patches left unburned, particularly along a floodplain (Eichhorn unpublished data; van Nieuwstadt 2002). A central core of the forest remained unburned (Figure 1). During the fires in Sungai Wain regular patrols and a firebreak protected the unburned part (approximately 3500 ha) of the reserve. The firebreak now forms the border between burned and unburned forest. Because all rectangular plots are perpendicular to this border (Figure 1) it creates 147 Figure 1. (a) Map of the Sungai Wain protected forest showing the unburned remnant forest (light grey) surrounded by the burned forest (dark grey). Arrows indicate the location of areas in which the plots (numbered 1–18) were sampled in Sungai Wain. Plots were always located perpendicular to the border between burned and unburned forest. (b) Location of the study area on the island of Borneo. (c) Plot design showing the edge and interior sectors. an ideal situation for comparing regeneration in burned forest with proximate unburned forest that presumably had a similar vegetation composition before the fires. Visually, the edge immediately after the fire was very sharp because the fire crept right up to the firebreak and burned most of the vegetation. Sampling started in September 1998 and ended in April 2001. The sequence of sampling events was T1) September-October 1998, T2) December 1998, T3) September-October 1999, T4) August-September 2000 and T5) March-April 2001. Unfortunately, it was not possible to sample at regular time intervals due to logistical constraints. Each sampling event took two to three weeks depending on weather conditions. Before the 1997/98 ENSO event, the whole of Sungai Wain (10,000 ha) was covered with mixed dipterocarp forest, which is the most common lowland forest type in Borneo. Elevation in the reserve varies from 40 to 140 m above sea level. The main soil type consists of ultisols, very deep, acidic infertile soils with a high fraction of loam and clay (van Bremenet al. 1990). Rainfall in the area is relatively a seasonal and averages 2790 mm per year, with a monthly minimum of 147 mm in July during the ‘dry season’ to a maximum of 272 mm in March during the ‘wet season’ (RePPProT1987; MacKinnon et al. 1997). Prior to 1980, there were no recorded dry periods (< 100 mm rain per month) that lasted longer than two months. Since then, the area has been affected by two major ENSO-induced droughts, viz., in 1982/ 83 and 1997/98. During the 1997/98 ENSO event rainfall was reduced to a sum total of only 48 mm from the 12thof July 1997 until the 5thof October 1997. This was followed by a relatively wet period from the 6thof October 1997 until the 12thof January 1998 with 388 mm of rain recorded. The next drought occurred from the 13thof January 1998 until the 24thof April 1998 during which rainfall was reduced to a sum total of only 13 mm and which coincided with the fires in Sungai Wain (van 148 Nieuwstadt 2002). Both droughts were accompanied by large-scale fires, of which those in 1997/98 were by far the most severe and widespread that have ever been recorded in Borneo (Harrison 2000). Sampling design Both burned forest and unburned controls were sampled with the same basic design. Two sets of nine master plots were established along a manmade firebreak that did not correspond to any obvious topographical feature. The plots covered an area of approximately 20 km2. Each plot (18 in total; Figure 1) was 200 · 20 m. Each plot in the unburned forest was contiguous with a plot in the burned forest; together they covered a continuous 400 · 20 m area. Three main sites were sampled in Sungai Wain. Within each site three pairs of plots were placed in burned and unburned areas. The whole area was designed so as to try to capture the maximum diversity within the area while avoiding pseudoreplications. All seedlings (height < 1.5 m) and saplings (height > 1.5 m and diameter at breast height < 8 cm) were sampled within subplots of varying size (see below). Within each plot we established 10 systematically spaced (at 10 m intervals) subplots. Each subplot was 5 · 5 m and all non-liana dicotyledonous saplings larger than 1.5 m and with a diameter at breast height (dbh) less than 8 cm were mapped (X–Y position recorded), measured (dbh and height in cm), labelled, and identified to species, if possible. This often proved rather problematic due to lack of diagnostic characters. The nomenclature of species follows Sidiyasaet al. (1999). Nested within each 5 · 5 m subplot was a 2 · 2 m subplot in which we repeated the above procedure for all seedlings. These were all non-liana, dicotyledonous woody plants that were < 1.5 m tall. The plots, plot location, and sampling design have been previously described by van Nieuwstadt (2002). Because densities were low for seedlings and saplings in the burned forest we pooled subplots and assessed patterns at the larger spatial scale. We did, however, distinguish between edge and interior sectors by pooling the five edge subplots into a single edge sector and the five interior subplots into a single interior sector in the burned and unburned forest plots (Figure 1c). Analyses Growth, mortality and recruitment We assessed actual and realisedgrowth during four periods of assessment: (a) T1–T2, (b) T2–T3, (c) T3–T4 and (d) T4–T5. For calculating actual vertical growth we only included zero or positive growth measurements whereas realised growth also included negative measurements. A negative measurement could be the result of measurement error, damage to a plant due to falling debris or animal grazing. Since actual growth, realisedgrowth, mortality (senescence of an individual plant between two sampling periods) and recruitment (establishment of a new plant between two sampling periods) values were not normally distributed, we used a Kruskal-Wallis ANOVA to test for significant differences among edge and interior sectors of unburned and burned forest followed by post-hoc comparisons of mean ranks of all pairs of groups within Statistica for Windows 6.1 (Statsoft, Tulsa, OK, USA). Differences among sectors and burn treatments were assessed for each sampling period separately. Density Because density was normally distributed, we used a three-way factorial ANOVA within Statistica for Windows 6.1 to test for significant differences in seedling and sapling density between (1) unburned and burned plots, (2) between edge and interior sectors, and (3) among sampling events. Species richness Because of the low densities of saplings and seedlings in burned forest we only tested for differences between unburned and burned plots (thus pooling edge and interior sectors) and among sampling events. Disturbances such as burning are known to affect density so it is important to disentangle the effects of disturbance on species richness by rarefying (McCabe and Gotelli 2000). Rarefied species richness is the expected number of species for a given number of randomly sampled individuals (McCabe and Gotelli 2000) and facilitates comparison of areas in which densities may differ. Using the number of individuals as the basic unit of comparison by rarefying, furthermore, helps to avoid problems such as the impact of observer bias, which can confound genuine differences in 149 Figure 2. Median (crosses) actual growth in burned edge (B–I), burned interior (B–I), unburned edge (U–E) and unburned interior (U– I) sectors of plots in the Sungai Wain Protected Forest Reserve. Each sampling period (a) T1–T2 (2 months between sampling events), (b) T2–T3 (9 months between sampling events), (c) T3–T4 (8 months between sampling events) and (d) T4–T5 (6 months between sampling events) is shown separately. Boxes represent 25–75% quartiles and error bars represent the non-outlier range. Significance based on a post hoc test is indicated by a letter above the bars for each sector. Means that differ significantly (P<0.05) do not share any letter. species richness between sites (Willott 2001). Estimates of rarefied species richness (at an n of 10) were obtained with the DIVERSE option of the program PRIMER (Clarke and Gorley 2001). Plots with less than 10 individuals were excluded from the analyses. Since species richness values were normally distributed we tested for differences in rarefied species richness of saplings and seedlings between unburned and burned forest, and among sampling events with a two-way factorial ANOVA within Statisticafor Windows 6.1. Community composition For sapling and seedling assemblages separately, we assessed the density of each species in each sector (i.e., edge and interior sectors of unburned and burned forest). Within Primer 5 (Primer-E Ltd, Plymouth, UK), these values were log10(x+1) transformed and used to generate a measure of similarity between sectors using the Bray-Curtis similarity index (Bray and Curtis, 1957), an index frequently used in ecological studies (Clarke and Gorley 2001; Legendre and Gallagher 2001; Ellingsen 2002; Cleary 2003). To examine whether community similarity was dependent upon environmental variables and distance between sectors, we used non-parametric matrix regression within the program Permute! 3.4.9 (Casgrain 2001). First, we constructed a Bray-Curtis community similarity matrix and then tested whether this community similarity matrix was dependent upon a set of environmental and distance predictor matrices. For saplings, these matrices included (1) Euclidean distance (log10 transformed) between sectors; (2) Euclidean difference in burning during the 19971998 ENSO event: 0 = not burned or 1 = burned; (3) Euclidean difference in edge type: 0 = interior or 1 = edge; (4) Euclidean difference in sampling event: T1 = 1, T2 = 2, T3 = 3, T4 = 4, T5 = 5.; (5) Tree abundance: normalised Euclidean difference between sectors based on log10(x+1) transformed tree density. For seedlings, we additionally included sapling abundance, which was the normalised Euclidean difference between sectors based on log10(x+1) transformed sapling density. The options for 999 permutations, forward selection and a Bonferroni-corrected p-to-enter value of 0.10 were selected. 150 Figure 3. Median (crosses) realised growth in burned edge (B–E), burned interior (B–I), unburned edge (U–E) and unburned interior (U–I) sectors of plots in the Sungai Wain Protected Forest Reserve. Each sampling period (a) T1–T2, (b) T2–T3, (c) T3–T4 and (d) T4– T5 is shown separately. Boxes represent 25–75% quartiles and error bars represent the non-outlier range. Significance based on a post hoc test is indicated by a letter above the bars for each sector. Means that differ significantly (P<0.05) do not share any letter. Results Growth Vertical actual growth (T1–T2: Kruskal-Wallis H = 277.43, P < 0.001; T2–T3: Kruskal-Wallis H = 216.52, P < 0.001; T3–T4: Kruskal-Wallis H = 235.92, P < 0.001; T4–T5: Kruskal-Wallis H = 401.29, P < 0.001; Figure 2) and realised growth (T1–T2: Kruskal-Wallis H = 267.58, P < 0.001; T2-T3: Kruskal-Wallis H = 230.41, P < 0.001; T3-T4: Kruskal-Wallis H = 252.72, P < 0.001; T4–T5: Kruskal-Wallis H = 394.64, P < 0.001; Figure 3) were both consistently and significantly higher in burned forest than unburned forest. There was no difference, however, between edge and interior sectors within burned or unburned forest. Kruskal-Wallis H = 2.89, P = 0.409; Figure 4) among edge and interior sectors of unburned and burned forest. Recruitment, however, was significantly higher in the interior sector of burned forest than the unburned sectors and significantly higher in the edge sector of burned forest than the unburned edge sector in the period T2–T3 (KruskalWallis H = 21.12, P < 0.001; Figure 5). In the other periods there were no significant differences in recruitment among edge and interior sectors of unburned and burned forest (T1–T2: KruskalWallis H = 1.01, P = 0.071; T3–T4: KruskalWallis H = 3.39, P = 0.336; T4–T5: KruskalWallis H = 3.47, P = 0.325). In addition to spatial variation in recruitment among sectors, there also appeared to be some temporal variation with a recruitment pulse occurring in both burned and unburned forest during the period T3–T4. Density Mortality and recruitment There was no significant difference in mortality (T1–T2: Kruskal-Wallis H = 2.98, P = 0.395; T2T3: Kruskal-Wallis H = 0.59, P = 0.898; T3–T4: Kruskal-Wallis H = 0.032, P = 0.999; T4–T5: Sapling density (Figure 6a)differed significantly between burned and unburned forest (F1, 160= 573.751, P < 0.001) and among sampling events (F4, 160= 6.678, P < 0.001), but there was no 151 Figure 4. Median (crosses) mortality in burned edge (B–E), burned interior (B–I), unburned edge (U–E) and unburned interior (U–I) sectors of plots in the Sungai Wain Protected Forest Reserve. Each sampling period (a) T1–T2, (b) T2–T3, (c) T3–T4 and (d) T4–T5 is shown separately. Boxes represent 25–75% quartiles and error bars represent the non-outlier range. Figure 5. Median (crosses) recruitment in burned edge (B–E), burned interior (B–I), unburned edge (U–E) and unburned interior (U–I) sectors of plots in the Sungai Wain Protected Forest Reserve. Each sampling period (a) T1–T2, (b) T2–T3, (c) T3–T4 and (d) T4–T5 is shown separately. Boxes represent 25–75% quartiles and error bars represent the non-outlier range. Significance based on a post hoc test is indicated by a letter above the bars for each sector. Means that differ significantly (P<0.05) do not share any letter. 152 Figure 6. Mean density (± 95% confidence intervals) of (a) saplings and (b) seedlings in burned edge (BE), burned interior (BI), unburned edge (UE) and unburned interior (UI) sectors of plots in the Sungai Wain Protected Forest Reserve. Figure 7. Mean rarefied (n = 10) species richness (± 95% confidence intervals) of (a) saplings and (b) seedlings in burned (B) and unburned (U) plots of the Sungai Wain Protected Forest Reserve. significant difference between edge and interior sectors (F1, 160= 0.772, P = 0.381), nor were there any significant interaction effects. Density was significantly higher in unburned than burned forest and significantly higher during the sampling events T4 and T5 than during the events T1, T2 and T3 (Bonferronitest, P < 0.05). Seedling density (Figure 6b)differed significantly between unburned and burned forest (F1, 160= 166.083, P < 0.001) and among sampling events (F4, 160= 3.246, P = 0.014), but there was no significant difference between edge and interior sectors (F1, 160= 1.607, P = 0.207). There was, however, a significant interaction (F1, 160= 7.330, P = 0.008) between forest type (unburned and burned) and edge type (edge and interior sectors). Seedling density was significantly higher in the unburned interior sector than all other sectors (Bonferronitest, P < 0.05) and significantly higher in the unburned edge sector than the burned edge and interior sectors (Bonferroni test, P < 0.001). Species richness Sapling species richness (Figure 7a)differed significantly between unburned and burned forest (F1, 124= 58.322, P < 0.001) and among sampling events (F4, 124= 5.091, P < 0.001). There was also a significant interaction between forest type and sample event (F4, 124= 5.631, P < 0.001). Species richness was significantly higher in unburned forest during all sample events and in burned forest during T1 and T2 than in burned forest during T3, T4 and T5 (Bonferroni test, P < 0.05). Seedling species richness (Figure 7b) was significantly higher in unburned forest than burned forest (F1, 124= 40.681, P < 0.001) but did not differ significantly among sampling events (F4, 124= 0.869, P = 0.485), nor was there a significant interaction between forest type and sampling event (F4, 124= 1.095, P = 0.362). 153 Figure 8. Relationship between similarity and distance for (a) saplings and (b) seedlings. Each point represents a single pairwise comparison of Bray-Curtis similarity between a pair of sectors. The fitted lines are logarithmic functions obtained using Statistica for Windows 6.1. Table 1. Results of the nonparametric forward matrix regression analysis within PERMUTE! Partial P Partial R2 0.809 0.355 0.189 0.034 0.021 0.001 0.001 0.001 0.001 0.002 0.654 0.125 0.016 0.001 0.000 0.540 0.481 0.073 0.056 0.024 0.001 0.001 0.001 0.001 0.003 0.292 0.228 0.005 0.002 0.001 Class Independent Partial b Saplings Burning Distance Tree density Edge Time Seedlings Burning Distance Edge Sapling density Time Community composition Variation in community composition (Figure 8) of both saplings and seedlings was predominantly and significantly related to differences in composition between unburned and burned forest (29– 65% of total variation explained) and the distance between sample plots (13–23% of total variation explained). Although there was significant residual variation explained by vegetation density, edge and sampling event, this only accounted for very little (< 2%) of the total explained variation (Table 1). Discussion Sapling and seedling density, species richness and composition differed significantly between burned and unburned forest. Most of the variation in similarity among sample plots was due to differences between burned and unburned forest and the distance between sectors. Distance decay of community similarity can be related to spatial environmental processes (niche-width differences among groups), or dispersal limitation. Dispersal limitation can arise due to the spatial configuration of habitat, whereby the habitat matrix can play an important role, or because of intrinsic differences in the dispersal ability among groups of species. The relationship between the spatial configuration of habitats and the habitat matrix, and intrinsic dispersal ability will also influence the duration of historical effects on ecosystems. This relationship, for example, can influence the rate of succession from a disturbed secondary state to primary-like conditions. Because the distance decay of community similarity describes how biodiversity is distributed in space, it can have important consequences for conservation strategies (Nekola and White 1999). Importantly, in the present study both environment (difference between unburned and burned forest) and distance between sample sectors significantly structured both sapling and seedling assemblages. Time (difference between sample events), however, only explained a marginal amount of variation in similarity with no evidence of a return to pre-burn conditions in the burned forest. Surprisingly, there was also little evidence of a pronounced edge effect, particularly in the burned forest, although we did find higher seedling density in the interior of unburned forest. In Puerto Rico, Cubinaand Aide (2001)found that of 35 fruitproducing species, only 14 were detected in the 154 seed rain in adjacent pasture and of these only 0.3% of the seeds and 3 species dispersed beyond 4 m of the forest edge. Likewise in the seed bank there was a dramatic decline in seedling densities and species richness at very short distances away from the forest edge. This indicates that few seeds disperse into pastures or other severely perturbed environments and they do not accumulate because of short-term seed viability and/or high seed predation. The lack of a pronounced edge effect in this study may also be related to the spatial scale of assessment, which was probably larger than the edge effect itself. In Uganda, Duncan and Duncan (2000), however, found that recruited trees and seedlings were scarce in degraded land adjacent to forest and seed survival was low. Patterns of succession were also similar at 10 and 25 m from the edge although they suggested that distance may be an important factor at different spatial scales. Despite fire exclusion, they suggested that forest succession can be very slow, even when proximate to remnant unburned forest. We noted a significant decline in the density of seedlings in both burned and unburned forest and a significant increase in the density of saplings in both forest types. In contrast to density there was very little change in species richness (and composition) in the unburned forest. In the burned forest, however, sapling species richness declined with time as pioneer assemblages became established. These assemblages were characterised by elevated growth and recruitment when compared to the assemblages in unburned forest. Mortality did not differ between unburned and burned forest although there appeared to be an increase in mortality with time. The decline in density in the unburned forest is probably due to the interannualmastingeffect of ENSO events on dipterocarpsand other tree species (Curran et al. 1999; Curran and Leighton 2000). As a case in point, the number of Shorealaevis (Dipterocarpaceae) seedlings in unburned forest declined from 61 in 1998 to 37 in 2001, whereas the number of Shorea laevis saplings increased from 37 in 1998 to 54 in 2001. The rarity of dipterocarpsin the burned forest and their inability to recoloniseis partially related to their particular life history. They produce very large seeds and are usually absent from the seed bank (Curran and Leighton 2000). Dipterocarp growth following disturbance is almost always from resident seedlings and saplings. These seedlings and saplings are, however, extremely sensitive to fires (Turner et al. 1997). In the burned forest only two dipterocarp seedling species survived the fires (Cotylelobium melanoxylon and Shorea ovalis, both represented by a single individual) and there was no further recolonisation (establishment) of dipterocarps throughout the sampling period. Common dipterocarp species such as Shorealaevis (n= 61 during T1) were completely absent from the burned forest. The same basic pattern held for saplings with only a fraction of the total dipterocarp species pool present and then in very low densities. The majority of seedling and sapling species showed a clear preference for unburned forest (Appendix I and II). There were, however, some unburned forest taxa that appeared to have survived and recolonisedthe burned forest viz., Pternandra sp., Aglaia sp., Gironniera nervosa and Fordia splendidissima of which the last was most successful. The few (pioneer) taxa with marked preferences for the burned forest included Vernoniaarborea, Dilleniasp., Macaranga gigantea, M. hypoleuca and M. trichocarpa. Most of the seedlings that were recorded in the burned forest in 1998 and 1999 were non-dipterocarp species that could regenerate from the seed bank, from dispersed seeds, or resproutedfrom burned stumps (this was especially the case with Fordia splendidissima; D. F. R. Cleary, personal observation). In Sungai Wain, van Nieuwstadt (2002) recorded a (re)sprout density of 129 ± 38 stems per 100 m2 in unburned forest and 22 ± 9.6 stems per 100 m2 in burned forest. Nearly 24% of all stems belonged to F. splendidissima. Virtually all of the F. splendidissimastems in the burned forest, furthermore, appeared to be sprouting when stem density in unburned forest was compared with sprout density in burned forest. For other shade tolerant species, however, sprouting was generally less than 10%, and only 2.5% and 0.4% for the dipterocarps Dipterocarpusconfertus and Shorealaevis (van Nieuwstadt 2002). The decline in seedling density in the burned forest is probably related to the particular pattern of regrowth following fires. The two principal sources of regrowthin the burned forest were rapidly growing pioneer trees (especially Macaranga gigantea) and ferns. We, in fact, witnessed massive colonisation of ferns, probably by means 155 of long-distance wind-mediated spores, in the burned forest. Dominant ferns included Blechnumorientale, Microlepia speluncae and the cosmopolitan Pteridium aquilinum (Dennstaedtiaceae), or bracken, a species noted for colonising extremely perturbed acidic environments (Roberts and Gilliam 1995). When dense, fern stands can exclude other plants (Whitmore 1984; Richards 1996). In Sungai Wain, van Nieuwstadt (2002) suggested that ferns spores arrived in very high densities in recently burned forest and were probably derived from distant source areas. He also observed fern stands to have reached a height of 1.5 2 m one year after the fires and to have overgrown many seedlings and resprouts. The ferns may therefore inhibit regeneration and explain why seedlings declined so strongly in the burned forest and why seedling and sapling density remained so much lower in burned forest than unburned forest. The nutrient poor acidic soil of Sungai Wain may also be playing a role in providing an ideal environment for bracken ferns to the detriment of woody species. In another study of the herbaceous layer in the burned and unburned Sungai Wain forest, K. A. O. Eichhorn (unpublished data) found that 14% of small 8-m2 (2 · 4 m) plots (n= 80) had low fern cover (0–10%), 29% of plots had moderate fern cover (10–30%), 50% of plots had high fern cover (30–70%) and 7% of plots had very high fern cover (>70%) in the burned forest. In the unburned forest, all plots had low (0–10%) fern cover and ferns were in fact absent from the majority of unburned forest plots. Variation in fern abundance within the burned forest may be primarily related to local edaphic conditions in combination with burn intensity. The local seedling community is thus probably subject to a suite of environmental factors that determine the eventual composition. In a study of photosynthetic responses of tree seedlings to grass, forest gap and shrub habitats, Loik and Holl (2001) found that the success of tree seedlings was the result of complex interactions of facilitation and competition and not just physiological responses to photosynthetic flux density. Local community succession can also be significantly influenced by the history of land use. Age was a good indicator of biomass accumulation in lightand moderate-use sites but not on heavy-use sites, which remained in a degraded state (Uhl et al. 1988). Likewise, two Amazonian secondary forests that had been clearcut without further disturbance were dominanted by Cecropia stands with speciesrich understories whereas other sites that were clearcut and used as pasture for a number of years were dominated by Vismia stands with impoverished understories (Mesquita et al. 2001). The Sungai Wain reserve was a protected forest with no history of heavy land-use. During the course of this study it, nevertheless, remained in a degraded state with little tendency towards regeneration to a primary-like state. Severe fires can degrade a primary rainforestto a state resembling that of secondary vegetation on recently abandoned agricultural land (Cochrane1998). Despite the fact that Sungai Wain was never commercially exploited, the burned area is now covered with a scrub of ferns and small pioneer trees typical of long-abandoned agricultural areas. Even if forest is re-established in the burned area it will probably remain different from the unburned forest. In Puerto Rico, Aide et al. (2000)found that density, basal area, aboveground biomass and species richness of secondary forest sites resembled old growth forest after c. 40 years. The species composition of the secondary forest was, however, still substantially different. Regeneration of the SungaiWain burned forest will probably be a very long drawn-out process. We also suggest that this probably extends to many of Borneo’s burned forests on nutrient poor soils. Unless access into forested lands via roads, electrical grids, and water transport systems is sharply curtailed, large areas of forest will continue to burn with potentially disastrous consequences for the biota and people of Indonesia. In addition to this, fragments embedded in low diversity pioneer stands may lose deep-forest species due to local extinction. By passing the early domination of these pioneers may, however, help to reduce this loss. Planting dispersal-limited forest trees may also accelerate succession in areas distant from remnant unburned forest. MartinezGarza and Howe (2003) suggest that planting dispersal limited trees on recently disturbed open ground may even bypass 30–70 years of species attrition by stimulating seed dispersal by animals. Remnant trees may also play a crucial factor in stimulating succession. In Samoa, Elmqvist et al. (2002) found that plant species richness and density were significantly higher under the canopies of remnant trees in burned forest whereas there were 156 no (or only marginal) differences among plots in unburned forest. They also found that the seed rain from vertebrate dispersers was much higher under the canopy of remnant trees in burned forest. They suggest that the three most important factors that should be targeted for forest management are remnant trees, refugia and vertebrate dispersers. In summary, we found no evidence of rapid rain forest succession in Sungai Wain towards primarylike conditions. Rather, ferns and impoverished pioneer sapling and seedling assemblages dominate the burned area. However, the area still harbours tracts of remnant primary vegetation, particularly around the floodplain and remnant forest trees so that active protection and restoration projects may facilitate and accelerate restoration. Acknowledgements All field assistants in Kalimantanare thanked for their help. Y. Pitoy, M. Buntu, A. Pakala, I. Sharif, B. van Helvoort, T. deKam, W. Smits, M. Oman, N. Boestani, K. Eichhorn all provided valuable help in Indonesia. Arifin, Insah and K. Eichhorn provided help with the plant identification. The Indonesian Ministry of Forestry and Crop Estates, the Kayu Mas concession, and ITCI concession provided field facilities. This study was supported by grant 895.100.005 of the Dutch Science Foundation (NWO), within the Priority Programme ‘Biodiversity in Disturbed Ecosystems’. Appendix Table A1. Abundance of saplings species recorded during each sampling event. B: burned, U: unburned, T: sample event. For certain taxa the species is indicated between brackets. This was the case when we could not positively identify all individuals to species-level, but all those individuals that we could identify belonged to a single species. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Acmena sp. Actinodaphne sp. (glabra) Adenanthera sp. Adinandra dumosa Aglaia sp. Alangium sp. (ridleyi) Alseodaphne sp. Alstonia sp. Anacolosa frutescens Anthocephalus chinensis Antidesma sp. (neurocarpum) Aporusa sp. Aquilaria malaccensis Archidendron sp. Ardisia sp. (korthalsiana) Artocarpus sp. Atuna racemosa Baccaurea sp. Barringtonia sp. (macrostachya) Beilschmiedia sp. Bhesa paniculata Bouea oppositifolia Buchanania sp. (sessifolia) Calophyllum nodosum Calophyllum wallichianum Canarium sp. Castanopsis sp. (fulva) Chaetocarpus sp. (castanocarpus) Chionanthus sp. Myrtaceae Lauraceae Fabaceae Theaceae Meliaceae Alangiaceae Lauraceae Apocynaceae Olacaceae Rubiaceae Euphorbiaceae Euphorbiaceae Thymelaeaceae Fabaceae Myrsinaceae Moraceae Chrysobalanaceae Euphorbiaceae Lecythidaceae Lauraceae Celastraceae Anacardiaceae Anacardiaceae Guttiferae Guttiferae Burseraceae Fagaceae Euphorbiaceae Oleaceae 13 20 5 5 231 26 54 2 5 12 31 453 10 49 80 130 5 259 81 62 5 6 5 17 5 59 20 51 2 0 0 0 0 2 0 0 0 0 0 0 3 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 3 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 4 0 0 0 2 0 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 3 0 0 1 0 0 0 4 0 2 0 5 0 1 1 1 0 0 0 0 0 0 0 4 0 0 1 0 0 3 0 0 1 0 0 0 4 0 2 0 3 0 1 1 1 0 0 0 0 0 0 0 4 0 3 3 1 1 42 5 11 0 0 3 6 84 2 9 14 24 1 48 15 11 0 2 1 3 1 12 4 8 0 3 3 1 1 42 5 11 0 0 3 6 82 2 9 14 24 1 48 15 11 0 1 1 3 1 12 4 8 0 3 4 1 1 43 5 10 0 1 2 6 81 2 9 14 24 1 49 15 11 1 1 1 2 1 12 4 9 0 2 4 1 1 46 5 11 0 2 2 7 95 2 9 19 25 1 56 16 12 2 1 1 4 1 12 5 9 1 2 4 1 1 46 6 11 0 2 2 6 93 2 9 19 23 1 53 15 12 2 1 1 5 1 11 3 9 1 157 Table A1. Continued. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Cinnamomum sp. Cleistanthus sp. Clerodendrum disparifolium Cotylelobium melanoxylon Cratoxylum sp. (glaucum) Croton sp. (argyratus) Crudia sp. (bantamensis) Crypteronia sp. (griffithii) Cryptocarya sp. (crassinervia) Dacryodes rostrata Dacryodes rugosa Dehaasia sp. Dialium sp. (indum) Dillenia sp. Dimocarpus sp. (longan) Dimorphocalyx sp. (muricatus) Diospyros sp. Dipterocarpus confertus Dipterocarpus cornutus Dipterocarpus tempehes Drymicarpus luridus Drypetes kikir Drypetes longifolia Drypetes oblongifolia Durio sp. Dysoxylum sp. (alliaceum) Elaeocarpus sp. (stipularis) Ellipanthus beccarii Ellipanthus tomentosus Elmerillia sp. (tsiampacca) Endiandra sp. (kingiana) Endospermum diadenum Endospermum peltatum Engelhardia serrata Erycibe sp. Eugenia sp. Euonymus castaneifolius Eurycoma longifolia Eusideroxylon zwageri Fagraea racemosa Ficus sp. Fordia sp. (splendidissima) Galearia fulva Garcinia sp. Gardenia sp. Geunsia pentandra Gironniera nervosa Glochidion sp. (glomerulatum) Gluta sp. Gomphia serrata Goniothalamus sp. Gonocaryum sp. Gonystylus sp. (affinis) Gordonia sp. (boornensis) Guioa sp. Lauraceae Euphorbiaceae Verbenaceae Dipterocarpaceae Hypericaceae Euphorbiaceae Fabaceae Crypteroniaceae Lauraceae Burseraceae Burseraceae Lauraceae Fabaceae Dilleniaceae Sapindaceae Euphorbiaceae Ebenaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Anacardiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Bombacaceae Meliaceae Elaeocarpaceae Connaraceae Connaraceae Magnoliaceae Lauraceae Euphorbiaceae Euphorbiaceae Juglandaceae Convolvulaceae Myrtaceae Celastraceae Simaroubaceae Lauraceae Loganiaceae Moraceae Fabaceae Euphorbiaceae Guttiferae Guttiferae Verbenaceae Ulmaceae Euphorbiaceae Anacardiaceae Ochnaceae Annonaceae Icacinaceae Thymelaeaceae Theaceae Sapindaceae 5 146 5 117 6 28 71 14 47 256 25 32 15 223 25 24 120 116 71 50 3 141 10 5 212 92 18 23 13 12 58 6 5 11 6 411 1 49 64 10 83 387 15 45 8 2 220 19 87 9 26 15 48 18 2 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 15 0 0 0 0 2 0 0 2 0 0 1 0 0 0 1 0 0 0 0 0 0 3 0 0 0 0 0 4 0 0 0 0 2 4 0 0 1 0 1 0 0 0 0 0 2 1 0 1 0 0 1 0 0 0 83 0 0 2 0 2 0 0 1 0 0 2 1 0 0 1 5 0 3 0 0 0 4 0 0 1 0 38 20 0 0 0 1 5 7 0 0 2 0 1 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 78 0 0 2 2 2 0 0 1 0 0 2 1 0 0 1 5 0 3 0 0 0 4 0 0 4 0 36 19 0 0 0 1 4 6 0 0 2 0 1 0 1 1 28 1 21 0 5 13 2 9 45 4 7 3 8 5 4 23 21 12 10 1 26 2 1 40 17 4 4 2 0 11 0 1 2 0 79 0 10 12 3 1 66 2 9 2 0 36 0 18 1 3 3 7 3 0 1 28 1 20 0 5 14 2 9 46 4 7 3 8 5 4 23 22 12 10 0 26 2 1 40 17 4 4 2 0 11 0 1 2 0 80 0 10 12 2 1 65 2 9 2 0 35 0 18 2 3 3 8 3 0 1 28 1 20 0 6 14 2 10 49 4 7 3 9 5 4 24 23 12 10 0 26 2 1 41 17 4 4 2 0 11 0 1 2 0 79 0 10 12 1 1 66 3 9 2 0 39 0 17 2 3 3 9 4 0 1 31 1 26 2 6 13 4 9 57 7 6 3 11 5 6 23 24 13 10 1 28 2 1 43 22 3 5 2 1 13 0 1 3 5 79 1 10 12 2 3 73 4 9 1 0 51 1 17 2 5 3 10 4 0 1 31 1 24 2 6 12 4 10 57 6 5 3 11 5 6 23 24 12 10 1 27 2 1 41 17 3 6 2 1 12 0 1 2 1 77 0 9 11 2 3 70 4 9 1 0 48 1 17 2 5 3 9 4 0 158 Table A1. Continued. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Gymnacranthera sp. Heritiera sp. Hopea dryobalanoides Hopea mengerawan Hopea rudiformis Horsfieldia sp. (grandis) Hydnocarpus sp. (polypetala) Hypobathrum sp. Ilex cymosa Irvingia malayana Ixora sp. Kibatalia sp. Knema sp. Koompassia malaccensis Koordersiodendron pinnatum Lansium domesticum Lasianthus sp. Leea indica Lepisanthes sp. Licania splendens Lithocarpus sp (leptogyne) Litsea sp. Lophopetalum sp. (beccarianum) Macaranga aetheadenia Macaranga bancana Macaranga conifera Macaranga gigantea Macaranga hypoleuca Macaranga lowii Macaranga pearsonii Macaranga trichocarpa Macaranga triloba Madhuca kingiana Madhuca pallida Madhuca pierrei Madhuca sericea Magnolia lasia Mallotus macrostachyus Mallotus mollissimus Mallotus paniculatus Mallotus penangensis Mammea acuminata Meiogyne sp Melanochyla castaneifolia Melanochyla fulvinervis Melastoma malabathricum Melicope glabra Meliosma sp. (sumatrana) Memecylon sp. Mezzettia parviflora Microcos sp. Monocarpia kalimantanensis Moultonianthus lembruggianus Myristica sp. (iners) Nauclea sp. (subdita) Myristicaceae Sterculiaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Myristicaceae Flacourtiaceae Rubiaceae Aquifoliaceae Simaroubaceae Rubiaceae Apocynaceae Myristicaceae Fabaceae Anacardiaceae Meliaceae Rubiaceae Leeaceae Sapindaceae Chrysobalanaceae Fagaceae Lauraceae Celastraceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Sapotaceae Sapotaceae Sapotaceae Sapotaceae Magnoliaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Guttiferae Annonaceae Anacardiaceae Anacardiaceae Melastomataceae Rutaceae Sabiaceae Melastomataceae Annonaceae Tiliaceae Annonaceae Euphorbiaceae Myristicaceae Rubiaceae 30 5 15 16 5 5 15 27 8 5 52 5 360 42 9 8 2 6 19 2 50 59 30 5 4 30 394 22 639 6 41 16 105 48 25 12 5 13 29 4 20 3 2 10 3 3 2 10 52 4 146 6 10 11 5 0 0 0 0 1 0 0 0 0 0 0 0 5 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 2 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 5 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 2 0 0 0 1 0 0 0 0 2 3 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 4 0 0 0 0 0 1 0 0 2 0 0 0 2 49 1 2 1 8 0 1 0 0 0 0 3 4 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 2 0 0 0 3 0 0 0 0 3 1 0 0 3 0 0 2 15 176 5 3 3 12 5 1 0 0 0 0 4 4 2 1 0 1 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 3 0 0 0 0 3 1 0 0 3 0 0 2 13 161 6 3 2 13 5 1 0 0 0 0 4 3 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 6 1 3 3 0 1 3 6 1 1 9 1 67 8 1 1 0 0 2 0 10 9 7 1 0 0 0 2 122 0 2 0 20 9 5 2 1 0 0 0 3 0 0 2 0 0 0 2 9 1 27 0 2 2 1 6 1 3 3 0 1 3 6 1 1 10 1 66 8 1 1 0 0 2 0 10 9 7 1 0 0 0 2 122 0 1 0 20 9 5 2 1 0 1 0 3 0 0 2 0 0 0 2 9 1 27 0 2 2 1 6 1 3 3 0 1 3 5 1 1 11 1 68 8 1 2 0 0 2 0 10 9 7 1 0 0 0 2 123 0 1 0 20 9 5 2 1 0 2 0 3 1 0 2 0 0 0 2 9 1 27 2 2 2 1 7 1 3 3 0 1 3 5 1 1 11 1 71 9 3 2 1 0 4 1 11 11 5 1 0 0 4 2 136 0 2 3 20 11 5 3 1 0 6 0 3 1 0 2 2 0 0 2 14 1 33 2 2 3 1 5 1 3 4 0 1 3 5 1 1 11 1 68 9 3 2 1 0 4 1 9 11 4 1 0 0 3 2 124 0 2 3 20 10 5 3 1 0 6 0 3 1 0 2 1 0 0 2 11 0 32 2 2 2 1 159 Table A1. Continued. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Neolitsea sp. Neonauclea gigantea Neoscortechinia sp. (kingii) Nephelium cuspidatum Nephelium uncinatum Ochanostachys amentacea Palaquium quercifolium Palaquium rostratum Palaquium stenophyllum Paracroton pendulus Parinari oblongifolia Payena sp. (lucida) Pentace sp. (triptera) Phoebe sp. Pimelodendron griffithianum Piper aduncum Polyalthia lateriflora Polyalthia rumphii Polyalthia sumatrana Pometia pinnata Popowia sp. (hirta) Porterandia anisophylla Prismatomeris sp. (beccariana) Prunus beccarii Psychotria sp. Pternandra sp. Quassia indica Quercus sp. Rhodamnia sp. (cinerea) Rhodomyrtus sp. Sandoricum koetjape Santiria sp. Saurauia sp. Scaphium macropodum Schima wallichii Scorodocarpus borneensis Shorea johorensis Shorea laevis Shorea leprosula Shorea ovalis Shorea parvifolia Shorea parvistipulata Shorea smithiana Sindora sp. Sterculia sp. (rubiginosa) Syzygium sp. Tabernaemontana macrocarpa Teijsmanniodendron sp. Terminalia foetidissima Timonius sp. Trema sp. Trigoniastrum sp. Trigonostemon sp. (laeavigatus) Tristaniopsis sp. Urophyllum sp. (arborescens) Lauraceae Rubiaceae Euphorbiaceae Sapindaceae Sapindaceae Olacaceae Sapotaceae Sapotaceae Sapotaceae Euphorbiaceae Chrysobalanaceae Sapotaceae Tiliaceae Lauraceae Euphorbiaceae Piperaceae Annonaceae Annonaceae Annonaceae Sapindaceae Annonaceae Rubiaceae Rubiaceae Rosaceae Rubiaceae Melastomataceae Simaroubaceae Fagaceae Myristaceae Myrtaceae Meliaceae Burseraceae Actinidiaceae Sterculiaceae Theaceae Olacaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Fabaceae Sterculiaceae Myrtaceae Apocynaceae Verbenaceae Combretaceae Rubiaceae Ulmaceae Trigonoceae Euphorbiaceae Myrtaceae Rubiaceae 5 2 30 4 5 31 4 5 12 20 5 45 8 10 22 2 29 33 83 7 41 10 31 5 5 152 30 5 5 5 1 58 146 23 7 10 12 228 17 107 13 20 56 5 30 125 10 23 5 5 1 12 18 2 96 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 9 0 0 0 0 1 0 1 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 1 0 8 0 0 0 0 0 0 1 1 0 1 0 6 0 1 6 0 1 2 4 1 9 1 2 4 0 6 6 17 1 8 2 5 1 1 26 6 1 1 1 0 11 30 4 0 2 0 39 3 22 3 4 12 0 6 18 2 4 1 1 0 2 3 0 18 1 0 6 0 1 6 0 1 2 4 1 9 1 2 4 0 6 6 17 1 8 2 5 1 1 26 6 1 1 1 0 11 28 4 0 2 0 41 3 21 3 4 11 0 6 18 2 4 1 1 0 2 3 0 18 1 0 6 0 1 6 0 1 2 4 1 9 2 2 5 0 6 6 17 1 8 2 5 1 1 26 6 1 1 1 0 11 30 4 0 2 0 43 3 20 3 4 11 0 6 18 2 4 1 1 0 2 3 0 19 1 0 6 2 1 7 1 1 3 4 1 9 2 2 5 0 7 6 16 2 8 2 9 1 1 31 6 1 1 1 1 13 29 6 0 2 6 51 4 24 2 4 11 0 6 25 2 6 1 1 0 3 3 0 21 1 0 6 2 1 6 1 1 3 4 1 9 2 2 4 0 4 6 16 2 9 2 7 1 1 29 6 1 1 1 0 12 29 5 0 2 6 54 4 20 2 4 11 0 6 27 2 5 1 1 0 3 3 0 20 160 Table A1. Continued. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Vatica pauciflora Vatica umbonata Vatica venulosa Vernonia arborea Vitex pinnata Walsura pinnata Xanthophyllum sp. Xylopia sp. Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Compositae Verbenaceae Meliaceae Polygalaceae Annonaceae 3 139 5 92 2 5 126 44 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 4 0 0 0 0 0 1 0 42 1 0 0 0 0 1 0 38 1 0 0 0 0 27 1 0 0 1 25 8 0 26 1 0 0 1 25 8 0 27 1 0 0 1 25 8 2 28 1 4 0 1 26 11 1 26 1 4 0 1 25 9 Table A2. Abundance of seedling species recorded during each sampling event. B: burned, U: unburned, T: sample event. For certain taxa the species is indicated between brackets. This was the case when we could not positively identify all individuals to species-level, but all those individuals that we could identify belonged to a single species. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Actinodaphne sp. (glabra) Aglaia sp. Agrostistachys borneensis Aidia sp. Alangium sp. (ridleyi) Alseodaphne sp. Alstonia sp. Anacolosa frutescens Antidesma sp. (neurocarpum) Aporusa sp. Aquilaria malaccensis Archidendron sp. Ardisia sp. (korthalsiana) Artocarpus sp. Baccaurea sp. Barringtonia sp. (macrostachya) Bhesa paniculata Borassodendron borneensis Bouea oppositifolia Buchanania sp. (sessifolia) Calophyllum nodosum Camellia sp. Chaetocarpus sp. (castanocarpus) Cleistanthus sp. Cotylelobium melanoxylon Croton sp. (argyratus) Crudia sp. (bantamensis) Cryptocarya sp. (crassinervia) Dacryodes rostrata Dacryodes rugosa Dehaasia sp. Desmos cochinchinensis Dialium sp. (indum) Dillenia sp. Diospyros sp. Dipterocarpus confertus Dipterocarpus cornutus Dipterocarpus gracilis Lauraceae Meliaceae Euphorbiaceae Rubiaceae Alangiaceae Lauraceae Apocynaceae Olacaceae Euphorbiaceae Euphorbiaceae Thymelaeaceae Fabaceae Myrsinaceae Moraceae Euphorbiaceae Lecythidaceae Celastraceae Palmae Anacardiaceae Anacardiaceae Guttiferae Theaceae Euphorbiaceae Euphorbiaceae Dipterocarpaceae Euphorbiaceae Fabaceae Lauraceae Burseraceae Burseraceae Lauraceae Annonaceae Fabaceae Dilleniaceae Ebenaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae 2 120 2 2 4 8 2 10 32 124 5 20 43 32 45 15 5 3 10 2 7 8 20 10 16 13 10 1 61 13 3 4 12 115 49 26 11 5 0 1 0 0 0 0 1 0 0 1 0 2 2 3 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 28 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 2 2 3 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0 33 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 3 2 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 24 0 0 0 0 0 3 1 0 0 0 0 0 0 0 0 2 2 2 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 15 0 0 0 0 0 3 1 0 0 0 0 0 0 0 0 1 2 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 10 0 0 0 0 1 24 0 0 1 1 0 3 6 25 1 2 8 7 10 2 2 1 2 0 2 2 4 2 1 3 3 0 16 3 1 0 2 2 9 7 2 1 1 24 0 0 1 1 0 3 6 25 1 2 7 6 10 2 2 1 2 0 2 2 4 2 2 3 2 0 15 3 1 0 2 2 10 6 2 1 0 22 0 0 1 2 0 2 6 25 1 2 7 5 9 2 1 1 2 0 2 2 3 2 2 2 2 0 12 3 1 0 2 1 9 5 2 1 0 20 0 1 1 2 0 1 7 24 1 2 6 2 9 3 0 0 2 0 1 1 3 2 3 3 2 1 9 2 0 2 3 0 11 4 2 1 0 18 0 1 0 2 0 1 7 23 1 2 5 2 7 3 0 0 2 0 0 1 3 2 3 2 1 0 9 2 0 2 3 0 10 4 3 1 161 Table A2. Continued. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Drymicarpus luridus Drypetes kikir Durio sp. Dysoxylum sp. (alliaceum) Elaeocarpus sp. (stipularis) Ellipanthus beccarii Ellipanthus tomentosus Endiandra sp. (kingiana) Endospermum diadenum Erycibe sp. Eugenia sp. Eurycoma longifolia Eusideroxylon zwageri Fagraea racemosa Ficus sp. Fordia sp. (splendidissima) Galearia fulva Garcinia sp. Gironniera nervosa Glochidion sp. (glomerulatum) Gluta sp. Gomphia serrata Gonystylus sp. (affinis) Gordonia sp. (boornensis) Guioa sp. Gymnacranthera sp. Hopea mengerawan Horsfieldia sp. (grandis) Hypobathrum sp. Ilex cymosa Ixora sp. Knema sp. Koompassia excelsa Koompassia malaccensis Koordersiodendron pinnatum Lithocarpus sp (leptogyne) Litsea sp. Lophopetalum sp. (beccarianum) Macaranga conifera Macaranga gigantea Macaranga hypoleuca Macaranga lowii Macaranga pearsonii Macaranga trichocarpa Madhuca kingiana Madhuca pallida Mallotus macrostachyus Mallotus mollissimus Mallotus paniculatus Mallotus penangensis Mammea acuminata Memecylon sp. Microcos sp. Mitrella sp. Monocarpia kalimantanensis Anacardiaceae Euphorbiaceae Bombacaceae Meliaceae Elaeocarpaceae Connaraceae Connaraceae Lauraceae Euphorbiaceae Convolvulaceae Myrtaceae Simaroubaceae Lauraceae Loganiaceae Moraceae Fabaceae Euphorbiaceae Guttiferae Ulmaceae Euphorbiaceae Anacardiaceae Ochnaceae Thymelaeaceae Theaceae Sapindaceae Myristicaceae Dipterocarpaceae Myristicaceae Rubiaceae Aquifoliaceae Rubiaceae Myristicaceae Fabaceae Fabaceae Anacardiaceae Fagaceae Lauraceae Celastraceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Sapotaceae Sapotaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Euphorbiaceae Guttiferae Melastomataceae Tiliaceae Annonaceae Annonaceae 4 66 31 3 5 1 2 8 5 12 129 25 15 1 19 354 2 14 95 10 30 1 8 2 8 10 19 10 10 2 32 75 8 5 1 20 16 3 4 168 89 330 5 47 8 6 4 4 1 15 2 2 40 4 4 0 1 1 0 0 0 1 0 2 0 3 3 0 0 3 24 0 0 7 4 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 2 0 1 59 30 3 2 20 0 0 3 3 1 0 0 0 0 0 0 0 1 1 0 0 0 1 0 2 0 3 3 0 0 3 28 0 0 7 4 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 2 0 1 63 27 3 2 19 0 0 1 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 1 0 3 3 0 0 3 29 0 0 4 2 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 1 0 1 29 17 3 1 4 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 3 3 0 0 2 23 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 8 8 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0 0 0 0 3 3 1 0 1 16 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 4 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 12 5 2 1 0 0 2 0 0 24 2 3 0 1 49 1 2 19 0 7 1 3 1 1 2 4 2 2 0 7 17 2 1 0 4 2 1 0 0 1 75 0 1 2 1 0 1 0 3 1 0 9 0 2 1 12 5 1 1 0 0 2 0 0 23 2 3 0 1 50 1 2 20 0 6 0 2 1 1 2 4 2 2 0 6 17 2 1 0 4 2 1 0 0 1 74 0 1 2 1 0 0 0 3 1 0 9 0 2 1 12 4 0 1 0 0 2 0 0 22 2 3 0 1 48 0 2 16 0 6 0 1 0 1 2 4 2 2 0 5 13 2 1 0 4 2 1 0 3 1 67 0 1 2 1 0 0 0 3 0 0 9 0 0 1 12 4 0 1 1 0 1 0 6 24 2 2 1 2 46 0 3 12 0 6 0 1 0 1 2 4 2 2 1 5 14 1 1 1 4 2 0 0 1 1 56 0 0 1 1 0 0 0 3 0 1 7 2 0 1 12 4 0 1 0 0 1 0 6 21 2 3 0 2 41 0 3 10 0 5 0 1 0 1 2 3 2 2 1 4 11 1 1 0 4 2 0 0 1 1 49 0 0 1 0 0 0 0 3 0 1 6 2 0 162 Table A2. Continued. Species FAMILY Total BT1 BT2 BT3 BT4 BT5 UT1 UT2 UT3 UT4 UT5 Moultonianthus lembruggianus Nauclea sp. (subdita) Neoscortechinia sp. (kingii) Payena sp. (lucida) Pentace sp. (triptera) Pimelodendron griffithianum Piper aduncum Polyalthia lateriflora Polyalthia microtus Polyalthia rumphii Polyalthia sumatrana Popowia sp. (hirta) Prismatomeris sp. (beccariana) Psychotria sp. Pternandra sp. Rhodamnia sp. (cinerea) Rinorea sp. Santiria sp. Saurauia sp. Scaphium macropodum Schima wallichii Shorea laevis Shorea leprosula Shorea ovalis Stemonurus sp. Symplocos sp. Syzygium sp. Teijsmanniodendron sp. Timonius sp. Trema sp. Trigonostemon sp. (laeavigatus) Urophyllum sp. (arborescens) Vatica umbonata Vernonia arborea Xanthophyllum sp. Xylopia sp. Euphorbiaceae Rubiaceae Euphorbiaceae Sapotaceae Tiliaceae Euphorbiaceae Piperaceae Annonaceae Annonaceae Annonaceae Annonaceae Annonaceae Rubiaceae Rubiaceae Melastomataceae Myristaceae Violaceae Burseraceae Actinidiaceae Sterculiaceae Theaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Icacinaceae Symplocaceae Myrtaceae Verbenaceae Rubiaceae Ulmaceae Euphorbiaceae Rubiaceae Dipterocarpaceae Compositae Polygalaceae Annonaceae 10 9 3 5 22 3 4 3 5 8 7 11 10 10 63 8 9 8 201 5 2 239 5 23 5 5 150 5 7 1 6 38 49 45 36 5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 1 0 1 3 0 1 0 1 0 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 1 0 1 3 0 1 0 1 0 0 9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 5 1 0 0 0 0 0 0 0 1 0 1 7 0 0 0 0 0 0 8 0 0 0 3 0 0 0 0 0 0 0 0 0 1 0 0 12 1 0 0 0 0 0 0 0 1 0 1 3 0 0 0 0 0 0 8 0 0 0 3 0 0 0 0 0 0 0 0 0 1 0 0 8 1 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 0 0 4 0 0 2 0 1 1 5 1 1 1 1 2 1 2 2 1 7 1 2 2 40 1 0 61 1 4 1 0 28 1 1 0 1 8 11 1 8 1 2 0 1 1 5 1 1 1 1 2 1 2 2 1 7 1 2 2 42 1 0 55 1 4 1 0 26 1 1 1 1 8 10 1 8 1 2 0 1 1 4 0 1 0 1 2 1 2 2 1 6 1 2 2 40 1 0 44 1 4 1 0 26 1 1 0 0 7 9 1 8 1 2 1 0 1 4 0 1 0 1 1 2 2 2 2 9 1 2 1 40 1 0 42 1 3 1 0 28 1 1 0 1 8 9 3 8 1 2 2 0 1 4 1 0 1 1 1 2 1 2 2 7 1 1 1 39 1 0 37 1 3 1 0 24 1 1 0 1 7 10 3 4 1 References Abramovitz J.N. and Dunn S. 1998. 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