Toward a coordinated understanding of hydro-biogeochemical root functions in tropical forests for application in vegetation models.

Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest-climate feedbacks for these carbon-rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine-root strategies for soil resource exploration, (2) coupling and trade-offs in fine-root water vs nutrient acquisition, and (3) aboveground-belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground-belowground hydro-nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO2. The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.

Las características de las raíces de los bosques tropicales y las estrategias de adquisición de recursos están subrepresentadas en modelos de vegetación, lo que dificulta la predicción del efecto de cambio de clima para estos ecosistemas ricos en carbono. Los bosques tropicales a menudo tienen combinaciones únicas a nivel mundial de alta biodiversidad taxonómica y funcional, estacionalidad de precipitación, y suelos infértiles, dando lugar a patrones distintos en los rasgos y funciones de las raíces en comparación con los ecosistemas de latitudes más altas. Integramos los avances recientes en nuestra comprensión de la función subterránea de los bosques tropicales en modelos de vegetación, centrándonos en la adquisición de agua y nutrientes. Ofrecemos comparaciones de avances recientes en la comprensión empírica y de modelos de las características de las raíces que representan procesos funcionales importantes en los bosques tropicales. Nos centramos en: (1) estrategias de raíces finas para adquisición de recursos del suelo, (2) acoplamiento y compensaciones entre adquisición del agua y de nutrientes, y (3) vínculos entre funciones sobre tierra y debajo del superficie en bosques tropicales. Sugerimos vías para representar estas comunidades de plantas extremadamente diversas en grupos computacionalmente manejables y ecológicamente significativos en modelos. Los bosques tropicales se están calentando, tienen cambios en los regímenes de lluvias, y tienen una exacerbación de la escasez de nutrientes del suelo causada por el elevado CO2 atmosférico. La representación precisa de las funciones de los bosques tropicales en modelos es crucial para comprender las interacciones de este bioma con el clima.

Tropical root responses to global changes: A synthesis.

Tropical ecosystems face escalating global change. These shifts can disrupt tropical forests' carbon (C) balance and impact root dynamics. Since roots perform essential functions such as resource acquisition and tissue protection, root responses can inform about the strategies and vulnerabilities of ecosystems facing present and future global changes. However, root trait dynamics are poorly understood, especially in tropical ecosystems. We analyzed existing research on tropical root responses to key global change drivers: warming, drought, flooding, cyclones, nitrogen (N) deposition, elevated (e) CO2, and fires. Based on tree species- and community-level literature, we obtained 266 root trait observations from 93 studies across 24 tropical countries. We found differences in the proportion of root responsiveness to global change among different global change drivers but not among root categories. In particular, we observed that tropical root systems responded to warming and eCO2 by increasing root biomass in species-scale studies. Drought increased the root: shoot ratio with no change in root biomass, indicating a decline in aboveground biomass. Despite N deposition being the most studied global change driver, it had some of the most variable effects on root characteristics, with few predictable responses. Episodic disturbances such as cyclones, fires, and flooding consistently resulted in a change in root trait expressions, with cyclones and fires increasing root production, potentially due to shifts in plant community and nutrient inputs, while flooding changed plant regulatory metabolisms due to low oxygen conditions. The data available to date clearly show that tropical forest root characteristics and dynamics are responding to global change, although in ways that are not always predictable. This synthesis indicates the need for replicated studies across root characteristics at species and community scales under different global change factors.

Experimental warming and its legacy effects on root dynamics following two hurricane disturbances in a wet tropical forest.

Tropical forests are expected to experience unprecedented warming and increases in hurricane disturbances in the coming decades; yet, our understanding of how these productive systems, especially their belowground component, will respond to the combined effects of varied environmental changes remains empirically limited. Here we evaluated the responses of root dynamics (production, mortality, and biomass) to soil and understory warming (+4°C) and after two consecutive tropical hurricanes in our in situ warming experiment in a tropical forest of Puerto Rico: Tropical Responses to Altered Climate Experiment (TRACE). We collected minirhizotron images from three warmed plots and three control plots of 12 m2 . Following Hurricanes Irma and María in September 2017, the infrared heater warming treatment was suspended for repairs, which allowed us to explore potential legacy effects of prior warming on forest recovery. We found that warming significantly reduced root production and root biomass over time. Following hurricane disturbance, both root biomass and production increased substantially across all plots; the root biomass increased 2.8-fold in controls but only 1.6-fold in previously warmed plots. This pattern held true for both herbaceous and woody roots, suggesting that the consistent antecedent warming conditions reduced root capacity to recover following hurricane disturbance. Root production and mortality were both related to soil ammonium nitrogen and microbial biomass nitrogen before and after the hurricanes. This experiment has provided an unprecedented look at the complex interactive effects of disturbance and climate change on the root component of a tropical forested ecosystem. A decrease in root production in a warmer world and slower root recovery after a major hurricane disturbance, as observed here, are likely to have longer-term consequences for tropical forest responses to future global change.

Variation in forest root image annotation by experts, novices, and AI.

BACKGROUND: The manual study of root dynamics using images requires huge investments of time and resources and is prone to previously poorly quantified annotator bias. Artificial intelligence (AI) image-processing tools have been successful in overcoming limitations of manual annotation in homogeneous soils, but their efficiency and accuracy is yet to be widely tested on less homogenous, non-agricultural soil profiles, e.g., that of forests, from which data on root dynamics are key to understanding the carbon cycle. Here, we quantify variance in root length measured by human annotators with varying experience levels. We evaluate the application of a convolutional neural network (CNN) model, trained on a software accessible to researchers without a machine learning background, on a heterogeneous minirhizotron image dataset taken in a multispecies, mature, deciduous temperate forest. RESULTS: Less experienced annotators consistently identified more root length than experienced annotators. Root length annotation also varied between experienced annotators. The CNN root length results were neither precise nor accurate, taking ~ 10% of the time but significantly overestimating root length compared to expert manual annotation (p = 0.01). The CNN net root length change results were closer to manual (p = 0.08) but there remained substantial variation. CONCLUSIONS: Manual root length annotation is contingent on the individual annotator. The only accessible CNN model cannot yet produce root data of sufficient accuracy and precision for ecological applications when applied to a complex, heterogeneous forest image dataset. A continuing evaluation and development of accessible CNNs for natural ecosystems is required.

Bringing function to structure: Root-soil interactions shaping phosphatase activity throughout a soil profile in Puerto Rico.

Large areas of highly productive tropical forests occur on weathered soils with low concentrations of available phosphorus (P). In such forests, root and microbial production of acid phosphatase enzymes capable of mineralizing organic phosphorus is considered vital to increasing available P for plant uptake.We measured both root and soil phosphatase throughout depth and alongside a variety of root and soil factors to better understand the potential of roots and soil biota to increase P availability and to constrain estimates of the biochemical mineralization within ecosystem models.We measured soil phosphatase down to 1 m, root phosphatase to 30 cm, and collected data on fine-root mass density, specific root length, soil P, bulk density, and soil texture using soil cores in four tropical forests within the Luquillo Experimental Forest in Puerto Rico.We found that soil phosphatase decreased with soil depth, but not root phosphatase. Furthermore, when both soil and root phosphatase were expressed per soil volume, soil phosphatase was 100-fold higher that root phosphatase.Both root and soil factors influenced soil and root phosphatase. Soil phosphatase increased with fine-root mass density and organic P, which together explained over 50% of the variation in soil phosphatase. Over 80% of the variation in root phosphatase per unit root mass was attributed to specific root length (positive correlation) and available (resin) P (negative correlation). Synthesis: Fine-root traits and soil P data are necessary to understand and represent soil and root phosphatase activity throughout the soil column and across sites with different soil conditions and tree species. These findings can be used to parameterize or benchmark estimates of biochemical mineralization in ecosystem models that contain fine-root biomass and soil P distributions throughout depth.