Tree size and stem status (multiple or single stemmed) were both significantly related to the probability that a tree present in the 1982 BCI census would resprout in one or more of six subsequent census intervals. For trees smaller than 5 cm, 30% of trees with multiple stems in 1980 census (that survived until 2010) were recorded as a resprout in a succeeding plot census, compared to 22% of single-stemmed individuals. For tree greater than 10 cm, this discrepancy increased, as the probability of resprouting multi-stemmed trees (45%) was three times greater than the probability for single stemmed trees (15%). In line with this pattern, we found a significant interaction between stem status and DBH in our generalized linear model (F =
179.96, P < 0.001; Table S4). This interaction indicates that while the smallest trees had a similar probability of resprouting regardless of stem status, the probability of resprouting declined sharply with DBH in single stemmed trees, whereas resprouting probability increased slightly with DBH in multiple-stemmed trees (Figure 4.2).
Taxonomic and size class variation in multiple stem frequency
The frequency of multi-stemmed trees, and taxonomy control over multiple stem
frequency varied among size classes on Barro Colorado Island (Table 4.1). Trees in the smallest size class (1-5 cm) had the highest proportion of individuals with multiple stems (10.9%), whereas the proportion of multi-stemmed trees in the largest size class examined (>10 cm DBH) was the lowest (5.8%). While the overall frequency of multi-stemmed trees declined with size, the proportion of variance in multiple stem frequency explained by taxonomy was greater for large trees compared to small trees. Across all trees > 1 cm in the 2005 BCI census, species, genus, and family together explained 17% of the variation in multiple stem frequency. For trees 1-5 cm DBH, taxonomic levels explained 11% of variance in multiple stem frequency. The proportion of variance explained by taxonomy increased to 25% when evaluated for tree 5-10 cm, 34% for trees > 5 cm, and 52% for trees > 10 cm. Genus explained the greatest proportion of variance among taxonomic levels for all size classes except for trees > 10 cm, for which species had the highest VPC (0.31; Table 4.1). Together these results suggest that while nearly all species are capable of maintaining multiple stems as juveniles, only some species retain the ability to create multiple stems as pole-sized and larger trees. For the following species level results, we evaluate multiple stem frequency for trees > 5 cm because very little variance was explained by taxonomy in saplings (1-5 cm) and too few trees > 10 cm are present to constrain species estimates.
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datasets having multiple stem frequencies of < 10% and nine species having no individuals with multiple stems.
Multivariate trait relationships
In the principal component analysis of the 71 species in the BCI trait dataset, the first three principal component (PC) axes together explained 66% in variance among species. Phab,
foliar N, and foliar P co-varied significantly (Table 4.8) and loaded strongly in the same
direction on the first PC axis (PC1), which explained 32% of the variation among species (Figure 4.3a, Table 4.8). The second PC axis (PC2) explained 20% of variance and represented a
previously described growth-mortality axis, which positively correlated with wood density and negatively correlated with growth and mortality rates. Contrary to our hypothesis, multiple stem frequency did not load strongly on either axis, but instead was significant positively correlated with the PC3 (Figure 4.3a, Table 4.8), which explained 14% of variance. The multivariate relationships among traits in the Fortuna dataset were similar to those observed in the BCI dataset (Figure 4.3b). Among 43 Fortuna species, tissue nutrient concentrations co-varied in the same direction as multiple stems on the first PC axis which explained 46% of variance among species, and RGR and wood density loaded in opposite directions on the second PC axis which explained 18% of the variance. Multiple stem frequency loaded most strongly on the third axis, which explained 13% of the variance (Table 4.8).
Examination of pairwise trait relationships revealed that species soil P association
coefficient, or Phab was the only trait significantly correlated with multiple stem frequency (Table
3; Figure 4a), although this relationship was fairly weak. Foliar N and P were not significantly associated with multiple stem frequency (Figure 4.4b, Table 4.3). When species were grouped by
effect of soil association group on species multiple stem frequency in trees >5 cm (F2,68 = 1.76, P
= 0.18; Figure 4.5a). However, the effect of soil association on the species frequency of multiple stems in trees > 10 cm was significant (F2,46 = 4.64, P = 0.014): species with a positive P affinity
had a higher proportion of multiple stems (11% ± 4%) than species with neutral (3.8% ± 0.9%) or negative (1.3 % ± 0.4%) soil P affinities (Figure 4.5b). In contrast to BCI, three of four nutrient allocation traits examined (foliar P, wood P, and wood N) were significantly positively correlated with species multiple stem frequency among species across the fertility gradient at Fortuna (Figure 4.4c-d). Similar to the BCI dataset, multiple stem frequency was not
significantly related to wood density or RGR at Fortuna (Table 4.4). Forest-level multiple stem frequency
There was considerable variation among forest plots in the proportion of woody dicot individuals > 10 cm with at least one multiple stem. Multiple stem frequency ranged between 0.9 and 21.3% across 49 Panamanian plots with an average frequency of 9.0% ± 0.7%. There was no significant difference in the average multiple stem frequency between lowland plots (8.9% ± 0.9%) and lower montane plots (9.5% ± 0.9%) plots.
When montane plots (all old growth) and lowland plots were combined in the same model, there was no significant effect of forest age on multiple stem frequency of woody trees (F2,46 = 2.78, P= 0.072; Figure 4.6). However, when lowland plots were analyzed alone, there
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average soil K and NH4 concentrations than mature secondary forest, and lower soil resin P
concentrations than both mature and young secondary forest (Table 4.9).
Across both lowland and montane forest plots, multiple stem frequency at the level of the tree community increased with soil fertility, as multiple stem frequency was significantly
positively correlated with soil PC1 (r2 = 0.25, df = 1,47, P < 0.001; Fig. 4.6a), which was
positively associated with measures of soil fertility including soil pH and soil resin P, NO3, Ca,
K, and Mg concentrations (Table 4.6). Soil PC2, on which soil NH4 loaded most strongly, was
not significantly correlated with multiple stem frequency (r2 = 0.0, df = 1,47, P = 0.26). Multiple stem frequency was not significantly correlated with mean annual precipitation (r2=0.0, df = 1,47, P = 0.923) or dry season rainfall (r2=0.0, df = 1,47, P = 0.864) across all plots, nor were these variables significant when the effect of rainfall on multiple stem frequency was evaluated for seasonally dry lowland plots or wet montane plots separately.
When LASSO variable selection was used to identify which specific environmental variables best predict multiple stem frequency, soil resin P was the only variable included in the model with the lowest lambda value (lambda = 0.578). Multiple stem frequency increased significantly with log transformed soil resin P (r2 = 0.44, df = 1,47, P < 0.001; Figure 4.6b). When we excluded secondary growth plots, which had significant higher soil resin P than the mature forest plots, the relationship between multiple stem frequency and soil resin P remained significant (r2 = 0.31, df = 1,19, P < 0.005).
DISCUSSION