Search

Summary: Nutrient limitation may constrain the ability of recovering and mature tropical forests to serve as a carbon sink. However, it is unclear to what extent trees can utilize nutrient acquisition strategies – especially root phosphatase enzymes and mycorrhizal symbioses – to overcome low nutrient availability across secondary succession.Using a large‐scale, full factorial nitrogen and phosphorus fertilization experiment of 76 plots along a secondary successional gradient in lowland wet tropical forests of Panama, we tested the extent to which root phosphatase enzyme activity and mycorrhizal colonization are flexible, and if investment shifts over succession, reflective of changing nutrient limitation. We also conducted a meta‐analysis to test how tropical trees adjust these strategies in response to nutrient additions and across succession.We find that tropical trees are dynamic, adjusting investment in strategies – particularly root phosphatase – in response to changing nutrient conditions through succession. These changes reflect a shift from strong nitrogen to weak phosphorus limitation over succession. Our meta‐analysis findings were consistent with our field study; we found more predictable responses of root phosphatase than mycorrhizal colonization to nutrient availability.Our findings suggest that nutrient acquisition strategies respond to nutrient availability and demand in tropical forests, likely critical for alleviating nutrient limitation. [ABSTRACT FROM AUTHOR]

Topographic heterogeneity and lateral subsurface flow at the hillslope scale of ≤1 km may have outsized impacts on tropical forest through their impacts on water available to plants under water-stressed conditions. However, vegetation dynamics and finer-scale hydrologic processes are not concurrently represented in Earth system models. In this study, we integrate the Energy Exascale Earth System Model (E3SM) land model (ELM) that includes the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), with a three-dimensional hydrology model (ParFlow) to explicitly resolve hillslope topography and subsurface flow and perform numerical experiments to understand how hillslope-scale hydrologic processes modulate vegetation along water availability gradients at Barro Colorado Island (BCI), Panama. Our simulations show that groundwater table depth (WTD) can play a large role in governing aboveground biomass (AGB) when drought-induced tree mortality is triggered by hydraulic failure. Analyzing the simulations using random forest (RF) models, we find that the domain-wide simulated AGB and WTD can be well predicted by static topographic attributes, including surface elevation, slope, and convexity, and adding soil moisture or groundwater table depth as predictors further improves the RF models. Different model representations of mortality due to hydraulic failure can change the dominant topographic driver for the simulated AGB. Contrary to the simulations, the observed AGB in the well-drained 50 ha forest census plot within BCI cannot be well predicted by the RF models using topographic attributes and observed soil moisture as predictors, suggesting other factors such as nutrient status may have a larger influence on the observed AGB. The new coupled model may be useful for understanding the diverse impact of local heterogeneity by isolating the water availability and nutrient availability from the other external and internal factors in ecosystem modeling. [ABSTRACT FROM AUTHOR]

Summary: Among tropical forests, lianas are predicted to have a growth advantage over trees during seasonal drought, with substantial implications for tree and forest dynamics. We tested the hypotheses that lianas maintain higher water status than trees during seasonal drought and that lianas maximize leaf cover to match high, dry‐season light conditions, while trees are more limited by moisture availability during the dry season.We monitored the seasonal dynamics of predawn and midday leaf water potentials and leaf phenology for branches of 16 liana and 16 tree species in the canopies of two lowland tropical forests with contrasting rainfall regimes in Panama.In a wet, weakly seasonal forest, lianas maintained higher water balance than trees and maximized their leaf cover during dry‐season conditions, when light availability was high, while trees experienced drought stress. In a drier, strongly seasonal forest, lianas and trees displayed similar dry season reductions in leaf cover following strong decreases in soil water availability.Greater soil moisture availability and a higher capacity to maintain water status allow lianas to maintain the turgor potentials that are critical for plant growth in a wet and weakly seasonal forest but not in a dry and strongly seasonal forest. [ABSTRACT FROM AUTHOR]

Pre‐dispersal seed mortality caused by premature fruit drop is a potentially important source of plant mortality, but one which has rarely been studied in the context of tropical forest plants. Of particular interest is premature fruit drop triggered by enemies, which—if density dependent—could contribute to species coexistence in tropical forest plant communities.We used a long‐term (31 year) dataset on seed and fruit fall obtained through weekly collections from a network of seed traps in a lowland tropical forest (Barro Colorado Island, Panama) to estimate the proportion of seeds prematurely abscised for 201 woody plant species. To determine whether enemy attack might contribute to premature fruit drop, we tested whether plant species abscise more of their fruit prematurely if they (a) have attributes hypothesised to be associated with high levels of enemy attack and (b) are known to be attacked by one enemy group (insect seed predators). We also tested (c) whether mean rates of premature fruit drop for plant species are phylogenetically conserved.Overall rates of premature fruit drop were high in the plant community. Across all species, 39% of seeds were abscised before completing their development. Rates of premature seed abscission varied considerably among species and could not be explained by phylogeny. Premature seed abscission rates were higher in species which are known to host pre‐dispersal insect seed predators and species with attributes that were hypothesised to make them more susceptible to attack by pre‐dispersal enemies, namely species which (a) have larger seeds, (b) have a greater average height, (c) have temporally predictable fruiting patterns and (d) are more abundant at the study site.Synthesis. Premature fruit drop is likely to be a major source of seed mortality for many plant species on Barro Colorado Island. It is plausible that pre‐dispersal seed enemies, such as insect seed predators, contribute to community‐level patterns of premature fruit drop and have the potential to mediate species coexistence through stabilising negative density dependence. Our study suggests that the role of pre‐dispersal enemies in structuring tropical plant communities should be considered alongside the more commonly studied post‐dispersal seed and seedling enemies. [ABSTRACT FROM AUTHOR]

Nutrient addition experiments indicate that nitrogen and phosphorus limit plant processes in many tropical forests. However, the long‐term consequences for forest structure and species composition remain unexplored. We are positioned to evaluate potential long‐term consequences of nutrient addition in central Panama where we have maintained a factorial nitrogen–phosphorus–potassium fertilization experiment for 21 yr and an independent study quantified the species‐specific nutrient requirements of 550 local tree species. Here, we ask whether nutrients limit reproduction at the species and community levels. We also ask whether species‐specific reproductive responses to nutrient addition are stronger among species associated with naturally fertile soils, which could contribute to a shift in species composition. We quantified species‐level reproductive responses for 38 focal species in the 21st year of the experiment and community‐level reproductive litter production for the first 20 yr. Species‐level reproductive responses to nitrogen and potassium addition were weak, inconsistent across species, and insignificant across the 38 focal species. In contrast, species‐level responses to phosphorus addition were consistently and significantly positive across the 38 focal species but were unrelated to species‐specific phosphorus requirements documented independently for the same species. Community‐level reproductive litter production was unaffected by nutrient addition, possibly because spatial and temporal variation is large. We conclude that phosphorus limits reproduction by trees in our experiment but find no evidence that reproductive responses to phosphorus addition favor species associated with naturally phosphorus‐rich soils. [ABSTRACT FROM AUTHOR]

Detection of flowering and quantification of flowering phenology are key to monitoring the reproduction of tropical trees and their response to global change. However, effective monitoring of flowering over various scales from individuals to forest ecosystem levels is lacking due to the relatively small sizes of flowers, diverse flowering strategies across species, and the short duration of flowering, making accurate flower detection difficult. Drone-based surveys require less time and human resources than traditional ground-based flower surveys and thus may be able to help address this in a cost-effective manner but remain underexplored in species-rich tropical forest ecosystems. Here, we developed a method that integrated the Residual Networks 50 (ResNet50) deep learning algorithm with high resolution imagery (c. 0.05 m) from monthly drone surveys done in a 50-ha tropical forest plot on Barro Colorado Island (BCI), Panamá, over 2018–2020 to detect a diversity of flowering species in this tree community and to track the timing of flowering throughout the year. We built a comprehensive training library of canopy components (flower, leaf, branch, and shade) from this forest plot throughout the study period, trained a single deep learning model across all drone imagery, and validated it using five-fold cross validation at the pixel scale. We further generated image- and tree-crown-specific supervised classifications to evaluate the deep learning model at the tree-crown scale. Our deep learning method accurately classified flowers (User's accuracy = 95.3 %, Producer's accuracy = 85.8 %) while maintaining high predictive power for the other three classes (Overall accuracy = 98.4 %). Our results also demonstrated high consistency against tree-crown-specific supervised classifications for flower (r2 = 0.85), leaf (r2 = 0.84), and branch (r2 = 0.92) components, with lower agreement observed for the shade component (r2 = 0.59). These results demonstrate the effectiveness of our method in advancing fine-scale flower monitoring in the tropics, with potential to be extended to other regions or other remote sensing platforms with frequent high-resolution monitoring. The method will allow us to better monitor flowering in tropical forests and improve our understanding of how phenology and reproductive success may be affected by climate change. [ABSTRACT FROM AUTHOR]