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Effects of moisture and density-dependent interactions on tropical tree diversity

Nature volume 615, pages 100–104 (2023)Cite this article

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Abstract

Tropical tree diversity increases with rainfall1,2. Direct physiological effects of moisture availability and indirect effects mediated by biotic interactions are hypothesized to contribute to this pantropical increase in diversity with rainfall2,3,4,5,6. Previous studies have demonstrated direct physiological effects of variation in moisture availability on tree survival and diversity5,7,8,9,10, but the indirect effects of variation in moisture availability on diversity mediated by biotic interactions have not been shown11. Here we evaluate the relationships between interannual variation in moisture availability, the strength of density-dependent interactions, and seedling diversity in central Panama. Diversity increased with soil moisture over the first year of life across 20 annual cohorts. These first-year changes in diversity persisted for at least 15 years. Differential survival of moisture-sensitive species did not contribute to the observed changes in diversity. Rather, negative density-dependent interactions among conspecifics were stronger and increased diversity in wetter years. This suggests that moisture availability enhances diversity indirectly through moisture-sensitive, density-dependent conspecific interactions. Pathogens and phytophagous insects mediate interactions among seedlings in tropical forests12,13,14,15,16,17,18, and many of these plant enemies are themselves moisture-sensitive19,20,21,22,23,24,25,26,27. Changes in moisture availability caused by climate change and habitat degradation may alter these interactions and tropical tree diversity.

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Fig. 1: The relationship between soil moisture and changes in seedling diversity over the first year of seedling life for 20 seedling cohorts.
Fig. 2: Mean effects of conspecific and heterospecific neighbours, soil moisture and SPMO on first-year seedling survival.
Fig. 3: Relationships between soil moisture, conspecific seedling neighbour effects and first-year seedling survival.
Fig. 4: Observed and simulated relationships between soil moisture and changes in cohort diversity.

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Data availability

All datasets generated or analysed during the current study are available through Figshare repositories. The first-year seedling survival and diversity datasets, including soil water availability and rainfall71 are available at https://figshare.com/s/a4d2dbb2a73b3eb09f9f. The FDP SWP source data72 are available at https://doi.org/10.6084/m9.figshare.c.4372898.v1, and the Lutz Watershed soil water content73 is available at https://doi.org/10.25573/data.10042517.v2.

Code availability

An R script demonstrating the model fitting routine and containing code to reproduce main and supplementary analyses of the study is available in the Figshare repository at https://figshare.com/s/a4d2dbb2a73b3eb09f9f71.

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Acknowledgements

The authors thank H. Muller-Landau for comments that improved the manuscript, and G. Barabás and M. M. Mayfield for their insights into species coexistence theory. The BCI forest dynamics plot was founded by S. P. Hubbell and R. B. Foster and is now managed by S. Davies, R. Condit, S. Lao and R. Perez. Numerous organizations provided funds for the FDP, principally the US National Science Foundation and the Smithsonian Institution. E.L.-T. thanks Oranim College of Education for funds to visit S.J.W. at STRI. The Environmental Sciences Program of the Smithsonian Institution funded seedling censuses from 1995 through 2008. This research was supported by grant no. 2017044 from the United States–Israel Binational Science Foundation (BSF). Computations of GLMMs were performed on the Hive computer cluster at the University of Haifa, partly funded by ISF grant 2155/15.

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Authors and Affiliations

  1. Department of Biology and Environment, University of Haifa–Oranim, Kiryat Tiv’on, Israel

    Edwin Lebrija-Trejos

  2. Smithsonian Tropical Research Institute, Balboa Ancón, Panama

    Andrés Hernández & S. Joseph Wright

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  1. Edwin Lebrija-Trejos
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  3. S. Joseph Wright
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Contributions

E.L.-T. conceived and conducted the analyses in this study and led writing. S.J.W. designed and maintained censuses for 26 years and contributed to analyses and writing. A.H. supervised data collection and identified seedlings.

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Correspondence to Edwin Lebrija-Trejos.

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Extended data figures and tables

Extended Data Fig. 1 Annual precipitation and mean soil moisture.

Precipitation records at Barro Colorado Island (BCI; 9.15°N, 79.85°W) from 1926 to 2019. Dark gray bars show precipitation during the study period (1995–2015). Black arrows mark years with the lowest (1997) and second highest (2010) precipitation since BCI rainfall records began. The continuous blue line shows annual mean soil moisture content (%) from 1981 to 2019. Monthly mean soil moisture and rainfall are significantly correlated (ties-corrected Spearman’s rho = 0.63, p-value < 2.2 × 10−16, two-tailed asymptotic-t approximation test with 416-2 df). The study of first-year survival ends in 2015 with the most recent census of the 50-ha Forest Dynamics Plot used to quantify two independent variables for the survival analyses. The study of the persistence of first-year changes in diversity continues through 2019.

Extended Data Fig. 2 Observed and simulated relationships between mean wet-season soil moisture (SMw) and changes in cohort diversity over the first year of seedling life (ΔqD) for the effective number of species or Hill numbers 1D (a–d) and 2D (e–g).

Panels a–d contain the information in main text Figs. 1 and 4 for 1D. a. The relationship for observed changes (black dots and line with 95% confidence intervals shown as dashed black lines) is not different than that for changes simulated using all fitted coefficients from the final individual-level survival model (blue dashed line) or simulated using all fitted coefficients except the interaction between soil moisture and species-specific moisture optima (SMw × SPMO; two dot-dash green line). The relationship for changes simulated using all fitted coefficients except the interaction between soil moisture and conspecific seedling density (SMw × CSD; dotted yellow line) is significantly weaker. Panels, b,c and d show the observed slope of the relationship (vertical red dashed line), the distributions of 10,000 simulated slopes and means (\(\bar{\beta }\))and 95% confidence intervals (CI) of simulated slopes including all fitted coefficients from the individual-level survival model (b) and all fitted coefficients except the SMw × SPMO interaction (c) and the SMw × CSD interaction (d). The observed slope (\({\hat{\beta }}_{{\theta }_{g}}\)) and Spearman correlation (rs) for the SMw-Δ1D relationship are in the legend of panel a; the two-sided p-values of a t-test, for \({\hat{\beta }}_{{\theta }_{g}}\), and the AS89 algorithm, for rs, indicate both parameters differ significantly from zero. Panels e,f and g, show Spearman correlation coefficients (rs) between SMw and simulated changes in 2D. The dashed red line shows the observed rs for 20 seedling cohorts. Histograms show distributions of 10,000 simulated rs values. The observed correlation does not differ from simulated correlations that emulated natural conditions by retaining all best-fit coefficients of our individual-level survival model (e) or that zeroed the interaction between wet-season soil moisture (SMw) and species-specific moisture optima (SPMO) to evaluate the role of differential survival of moisture-sensitive species with greater soil moisture (f). In contrast, the observed correlation differs from simulated correlations that zeroed the interaction between SMw and the density of conspecific seedling neighbours (CSD) to evaluate the role of enhanced conspecific seedling negative density dependence with soil moisture (g). See Methods for detailed descriptions of the simulations, seedling survival model, calculations of changes in diversity and fitting of linear models.

Extended Data Fig. 3 Summary of results of the final best-fit generalized linear mixed model of first year seedling survival using wet season soil moisture.

a. Estimate, standard error (SE) and significance of fixed effects (two-tailed Wald-Z tests). Seedling density quantifies all individuals < 1 cm DBH found in the same 1-m2 plot with the focal seedling. Large density quantifies all individuals ≥ 1 cm DBH found within 1.15 crown radii of the seedling plot. With median centred variables, the exponential of the intercept indicates the mean first year survival odds, y = P/(1 – P), where P = survival probability, when fixed effects are set to their medians. The exponential of the fixed effect coefficients indicates the proportional change in first year survival odds with one interquartile range (IQR) increase in the predictor. The slopes of the main effects of predictors involved in interactions indicate the change in the first-year survival odds with a one IQR increase in the predictor when the second predictor in the interaction is at its median value. b. Estimates of the standard deviation (SD) of random effects; SD values are in the same scale as the fixed effects estimates in a thus allowing the comparison of their magnitudes. c. Species-specific (random effect) estimates of the effect of the interaction between conspecific seedling density (CSD) and mean wet-season soil moisture (SMw). Negative values indicate a strengthening of negative CSD effects with increasing SMw. Only 7 out of 215 species are estimated to experience reduced conspecific seedling negative density dependence with increasing SMw.

Extended Data Fig. 4 Distributions of estimated changes in first-year survival probability (Δ p) with one unit increases in HSD (light bars) or CSD (dark bars) at a) low, b) median and c) high values of soil moisture (i.e., 25, 50 and 75 percentiles of SMw).

The distributions fulfil the conditions for potential species stabilization under the assumptions of Modern Coexistence Theory (i.e., CNDD > HNDD) for all values of SMw with stronger effects for wetter soils (i.e., larger values of SMw). The estimates of the difference in effects between CSD and HSD include the observed main effect of seedling density and its interactions with SMw, with other predictors set at their median values. The mean (\(\mathop{{\rm{x}}}\limits^{\mbox{--}}\)) and 95% confidence intervals (in square brackets) of Δ p for each seedling density effect are shown above the corresponding distribution.

Extended Data Fig. 5 Lasting significance of first-year changes in seedling diversity.

a. Persistence of first-year changes in diversity through time. Pearson correlation coefficients (r) between first-year seedling cohort diversity and the diversity of the same seedling cohort two through 15 years after recruitment indicate changes in first-year cohort diversity are lasting. The number of cohorts (N) included in the correlation ranged from 23 to 10, respectively. Black and grey symbols represent correlations with diversity quantified by Hill numbers qD for q = 1 and 2, respectively. All r values are significant (two-sided t test p < 0.028). b. Results of analysis to determine whether future cohort diversity at cohort ages 2 through 10 years is better predicted by cohort diversity at the time of recruitment or one year later. Coefficients of determination (r2) and their difference (fourth column) are presented for relationships between cohort diversity at ages 2 through 10 years and cohort diversity at the year of recruitment (third column) and after 1 year (second column). We use the Dunn and Clark z statistic to test for significant differences in the magnitude of dependent correlations (i.e., obtained from the same observations and having one variable in common, which is diversity at age x; See Methods) estimated for a minimum sample size (N) of 15 cohorts. Diversity is quantified by Hill numbers 2D (upper table) and 1D (lower table).

Extended Data Fig. 6 Covariation between dry-season gravimetric soil water content in the Lutz watershed and soil water potential in the 50-ha forest dynamics plot at Barro Colorado Island.

The two sites are 1.25 km apart. Pearson correlation coefficient r = 0.80 (two-sided t test p = 0.018). Kupers et al.51. measured soil water potential (SWP) during the dry season for samples collected across the 50-ha FDP repeatedly in 2015 and 2016. Gravimetric soil water content (θg) in the Lutz watershed was determined from samples taken every week between December and May across 10 sites separated by 30 to 470 m. Means (+/− s.e.m.) were calculated for measurements made less than four days apart around February 20 and 27, March 20 and 30, and April 2 and 13 in 2015 and March 11 and 16 in 2016. There were n = 44, 200, 119, 125, 129, 174, 112 and 217 widely scattered SWP determinations from the 50-ha FDP per measurement period, respectively, and n = 10 θg determinations from the Lutz watershed for each measurement period excepting 20 March 2015 and 16 March 2016 when n = 9.

Extended Data Fig. 7 Quantile-quantile plot of scaled conditional residuals for the final best-fit first-year seedling survival model produced with the ‘DHARMa’ package.

Kolmogorov-Smirnov test for deviations of scaled residuals from the expected uniform (flat) distribution, D45100= 0.006, two-tailed p = 0.111.

Extended Data Fig. 8 Conditional residuals against predictors.

a,b,e,f,i,j, Smoothed scatterplots of zero-to-one standardized residuals produced with the ‘DHARMa’ package show estimated quantile regressions on the empirical 0.25, 0.5 and 0.75 distribution quantiles (continuous lines) to assist with inspection of deviations from the theoretical quantile expectations (dashed straight lines). Standard error bounds for the predicted quantile regression are too narrow to be seen. Plot shading reflects the density of data points, which are omitted for clarity. Red lines indicate significant deviations from the theoretical expectations for a uniform distribution of residuals. c,d,g,h,k,l, Binned plots of averaged residuals against predictors produced with the ‘arm’ package. The solid lines show plus and minus two standard errors and are expected to contain ~95% of the binned residuals. The predictor variables are scaled and transformed as used in model fitting. The number of bins was set to default values corresponding to the minimum of the square root of the sample size (i.e., 45,100 seedling recruits) or the number of unique values of the predictor (e.g., 20 unique values of mean wet-season soil moisture yields 20 bins in panel l).

Extended Data Table 1 Fixed effect estimates and information criteria metrics for seedling survival GLMMs fitted with alternative soil moisture variables
Full size table
Extended Data Table 2 Relationships between changes in cohort diversity over the first year of life and seasonal mean soil moisture
Full size table

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Discussion regarding theoretical aspects involving HSD effects and conspecific vs heterospecific density dependence in the context of modern species coexistence theory. Also discussed are methodological aspects involving sensitivity of the analysis to abundant species, the use of soil moisture vs rainfall records and model diagnostics (analysis of residuals).

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Lebrija-Trejos, E., Hernández, A. & Wright, S.J. Effects of moisture and density-dependent interactions on tropical tree diversity. Nature 615, 100–104 (2023). https://doi.org/10.1038/s41586-023-05717-1

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