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The mission of the Smithsonian Tropical Research Institute (STRI) is to increase "...knowledge about the past, present and future of tropical biodiversity and its relevance to human welfare." Scientists pursue their own research interests within this broad mandate. This review concerns the history of STRI and recent ecological and applied research conducted at STRI, emphasizing research that extends across decades due to sustained efforts of single investigators or multiple investigators working across generations. STRI began as a rustic field station established in the forests of Barro Colorado Island (BCI), Panama in 1923 that prospered without outside funding setting the stage for the subsequent development of a major research center. Today, STRI employs 34 scientists, maintains nine field stations and six laboratories and hosts 1,200 visiting scientists and students each year. BCI provides examples of modern research being informed by results published up to 95 years earlier. Baselines recorded more systematically starting 50 years ago will be even more valuable in the future. The same will be true for each field station and research network described in this volume. As the natural world changes, data from these field stations and research networks will provide irreplaceable insights into how tropical forests and coral reefs once functioned and how function changed through time. [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]

Phosphorus (P) cycles rapidly in lowland tropical forest soils, but the process have been proven difficult to quantify. Recently it was demonstrated that valuable data on soil P transformations can be derived from the natural abundance of stable oxygen isotopes in phosphate (δ18OP). Here, we measured the δ18OP of soils that had received long-term nutrient additions (P, nitrogen, and potassium) or litter manipulations in lowland tropical forest in Panama and performed controlled incubations of fresh soils amended with a single pulse of P. To detect whether δ18OP values measured in the incubations apply also for soils in the field, we examined the δ18OP values after rewetting dry soils. In the incubations, resin-P δ18OP values converged to ∼3.5‰ above the expected isotopic equilibrium with soil water. This contrasts with extra-tropical soils in which the δ18OP of resin-P matches the expected equilibrium with soil water. Identical above-equilibrium resin-P δ18OP values were also found in field soils that did not receive P additions or extra litter. We suggest that the 3.5‰ above-equilibrium δ18OP values reflect a steady state between microbial uptake of phosphate (which enriches the remaining phosphate with the heavier isotopologues) and the release of isotopically equilibrated cell internal phosphate back to the soil. We also found that soil nutrient status affected the microbial turnover rate because in soils that had received chronic P addition, the original δ18OP signature of the fertilizer was preserved for at least eight weeks, indicating that the off-equilibrium δ18OP values produced during microbial phosphate turnover was not imprinted in these soils. Overall, our results demonstrate that ongoing microbial turnover of phosphate mediates its biological availability in lowland tropical soils. [ABSTRACT FROM AUTHOR]