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Tropical forests and global change: biogeochemical responses and opportunities for cross-site comparisons, an organized INSPIRE session at the 108th Annual Meeting, Ecological Society of America, Portland, Oregon, USA, August 2023

In this study, tropical forests play a critical role in the global carbon (C) cycle. These ecosystems maintain the highest rates of net primary production (NPP) on Earth, contain c. 30% of terrestrial C stocks, and have some of the largest stores of fine-root biomass globally, as well as higher fine-root production and turnover rates compared with other biomes. Tropical forest responses to projected warming, altered rainfall regimes, and elevated CO 2 concentrations are likely to be different from other ecosystems because of their unique characteristics (Box 1), making targeted research and model development important for understanding tropical forest–climate feedbacks. There is now a critical mass of long-term global change field experiments and modeling efforts in tropical forests, yet thus far there has been little synthesis, cross-site comparison, or multi-site standardized experimentation among tropical forests to help us understand how these biomes are changing. An organized INSPIRE session at the 108th Annual Meeting of the Ecological Society of America set out to tackle just this. Speakers covered large-scale tropical forest field experiments and modeling efforts, with an emphasis on changes in ecosystem biogeochemistry under warming, drying, elevated atmospheric CO 2 , and changing nutrient status. In this Meeting report, we provide an overview of the large-scale global change experiments presented and highlight the main objectives and opportunities for tropical forest research that emerged, including cross-site comparisons and integration with ecosystem-scale models (Fig. 1).

54 ENVIRONMENTAL SCIENCES↗

Contributions of TRMM to Our Understanding of Precipitation Processes and Climate Variability

The Tropical Rainfall Measuring Mission (TRMM), a joint U.S./Japan effort, has completed seven and a half years in orbit. This successful research mission studying precipitation processes and climatology has also become a key element in the routine monitoring of global precipitation. The package of rain measuring instrumentation, including the first rain radar and microwave radiometer combination in space, continues to function perfectly, and the satellite has the capability to operate for a number of additional years, providing a unique, long-term record of global tropical precipitation characteristics. A summary of research highlights will be presented covering topics ranging over climate analysis, improving forecasts, and storm and precipitation processes. A focus of the talk will be the important role of TRMM data in multi-satellite precipitation analyses at fine time scales and in improving our understanding of the validity of climate-scale variations through comparison with, and eventual improvement of, the GEWEX Global Precipitation Climatology Project (GPCP) 25-year data set.

Adler, Robert F.↗

Changes in Land Use Enhance the Sensitivity of Tropical Ecosystems to Fire-Climate Extremes

The Pantanal, the largest contiguous wetland in the world with a high diversity of ecosystems and habitat for several endangered species, was impacted by record-breaking wildfires in 2020. In this study, we integrate satellite and modeling data that enable exploration of natural and human contributing factors to the unprecedented 2020 fires. We demonstrate that the fires were fueled by an exceptional multi-year drought, but dry conditions solely could not explain the spatial patterns of burning. Our analysis reveals how human-caused fires exacerbated drought effects on natural ecosystem within the Pantanal, with large burned fractions primarily over natural (52%), and low cattle density areas (44%) in 2020. The post-fire ecosystem and hydrology changes also had strong ecological effects, with vegetation productivity less than − 1.5 σ over more than 30% of the natural and conservation areas. In contrast to more managed areas, there was a clear decrease in evaporation (by ~ 9%) and an increase in runoff (by ~ 5%) over the natural areas, with long-term impacts on ecosystem recovery and fire risk. This study provides the first tropical evidence outside rainforests of the synergy between climate, land management and fires, and the associated impacts on the ecosystem and hydrology over the largest contiguous wetlands in the world.

Sujay Kumar↗

Sensitivity of Latent Heating Profiles to Environmental Conditions: Implications for TRMM and Climate Research

The Tropical Rainfall Measuring Mission (TRMM) as a part of NASA's Earth System Enterprise is the first mission dedicated to measuring tropical rainfall through microwave and visible sensors, and includes the first spaceborne rain radar. Tropical rainfall comprises two-thirds of global rainfall. It is also the primary distributor of heat through the atmosphere's circulation. It is this circulation that defines Earth's weather and climate. Understanding rainfall and its variability is crucial to understanding and predicting global climate change. Weather and climate models need an accurate assessment of the latent heating released as tropical rainfall occurs. Currently, cloud model-based algorithms are used to derive latent heating based on rainfall structure. Ultimately, these algorithms can be applied to actual data from TRMM. This study investigates key underlying assumptions used in developing the latent heating algorithms. For example, the standard algorithm is highly dependent on a system's rainfall amount and structure. It also depends on an a priori database of model-derived latent heating profiles based on the aforementioned rainfall characteristics. Unanswered questions remain concerning the sensitivity of latent heating profiles to environmental conditions (both thermodynamic and kinematic), regionality, and seasonality. This study investigates and quantifies such sensitivities and seeks to determine the optimal latent heating profile database based on the results. Ultimately, the study seeks to produce an optimized latent heating algorithm based not only on rainfall structure but also hydrometeor profiles.

Shepherd, J. Marshall↗

Climate Change Signal in Atlantic Tropical Cyclones Today and Near Future

This manuscript discusses the challenges in detecting and attributing recently observed trends in the Atlantic tropical cyclone (TC) and the epistemic uncertainty we face in assessing future risk. We use synthetic storms downscaled from five CMIP5 models by the Columbia HAZard model (CHAZ), and directly simulated storms from high-resolution climate models. We examine three aspects of recent TC activity: the upward trend and multi-decadal oscillation of the annual frequency, the increase in storm wind intensity, and the decrease in forward speed. Some data sets suggest that these trends and oscillation are forced while others suggest that they can be explained by natural variability. Projections under warming climate scenarios also show a wide range of possibilities, especially for the annual frequencies, which increase or decrease depending on the choice of moisture variable used in the CHAZ model and on the choice of climate model. The uncertainties in the annual frequency lead to epistemic uncertainties in TC risk assessment. Here, we investigate the potential for reduction of these epistemic uncertainties through a statistical practice, namely likelihood analysis. We find that historical observations are more consistent with the simulations with increasing frequency than those with decreasing frequency, but we are not able to rule out the latter. We argue that the most rational way to treat epistemic uncertainty is to consider all outcomes contained in the results. In the context of risk assessment, since the results contain possible outcomes in which TC risk is increasing, this view implies that the risk is increasing.

54 ENVIRONMENTAL SCIENCES↗

Forest Age Rivals Climate to Explain Reproductive Allocation Patterns in Forest Ecosystems Globally

ABSTRACT Forest allocation of net primary productivity (NPP) to reproduction (carbon required for flowers, fruits, and seeds) is poorly quantified globally, despite its critical role in forest regeneration and a well‐supported trade‐off with allocation to growth. Here, we present the first global synthesis of a biometric proxy for forest reproductive allocation (RA) across environmental and stand age gradients from a compiled dataset of 824 observations across 393 sites. We find that ecosystem‐scale RA increases ~60% from boreal to tropical forests. Climate shows important non‐linear relationships with RA, but is not the sole predictor. Forest age effects are comparable to climate in magnitude (MAT: ß = 0.24,p = 0.021; old growth forest: ß = 0.22,p < 0.001), while metrics of soil fertility show small but significant relationships with RA (soil pH: ß = 0.07,p = 0.001; soil N: ß = −0.07,p = 0.001). These results provide strong evidence that ecosystem‐scale RA is mediated by climate, forest age, and soil conditions, and is not a globally fixed fraction of positive NPP as assumed by most vegetation and ecosystem models. Our dataset and findings can be used by modellers to improve predictions of forest regeneration and carbon cycling.

Environmental Sciences & Ecology↗

Internal variability and forcing influence model–satellite differences in the rate of tropical tropospheric warming

Climate-model simulations exhibit approximately two times more tropical tropospheric warming than satellite observations since 1979. The causes of this difference are not fully understood and are poorly quantified. Here, we apply machine learning to relate the patterns of surface-temperature change to the forced and unforced components of tropical tropospheric warming. This approach allows us to disentangle the forced and unforced change in the model-simulated temperature of the midtroposphere (TMT). In applying the climate-model-trained machine-learning framework to observations, we estimate that external forcing has produced a tropical TMT trend of 0.25 ± 0.08 K⋅decade −1 between 1979 and 2014, but internal variability has offset this warming by 0.07 ± 0.07 K⋅decade −1 . Using the Community Earth System Model version 2 (CESM2) large ensemble, we also find that a discontinuity in the variability of prescribed biomass-burning aerosol emissions artificially enhances simulated tropical TMT change by 0.04 K⋅decade −1 . The magnitude of this aerosol-forcing bias will vary across climate models, but since the latest generation of climate models all use the same emissions dataset, the bias may systematically enhance climate-model trends over the satellite era. Our results indicate that internal variability and forcing uncertainties largely explain differences in satellite-versus-model warming and are important considerations when evaluating climate models.

54 ENVIRONMENTAL SCIENCES↗

Interannual Variability of Boreal Summer Rainfall in the Equatorial Atlantic

Tropical Atlantic rainfall patterns and variation during boreal summer [June-July-August (JJA)] are quantified by means of a 28-year (1979-2006) monthly precipitation dataset from the Global Precipitation Climatology Project (GPCP). Rainfall variability during boreal spring [March-April-May (MAM)] is also examined for comparison in that the most intense interannual variability is usually observed during this season. Comparable variabilities in the Intertropical Convergence Zone (ITCZ) strength and the basin-mean rainfall are found during both seasons. Interannual variations in the ITCZ's latitudinal location during JJA however are generally negligible, in contrasting to intense year-to-year fluctuations during MAM. Sea surface temperature (SST) oscillations along the equatorial region (usually called the Atlantic Nino events) and in the tropical north Atlantic (TNA) are shown to be the two major local factors modulating the tropical Atlantic climate during both seasons. During MAM, both SST modes tend to contribute to the formation of an evident interhemispheric SST gradient, thus inducing anomalous shifting of the ITCZ and then forcing a dipolar structure of rainfall anomalies across the equator primarily in the western basin. During JJA the impacts however are primarily on the ITCZ strength likely due to negligible changes in the ITCZ latitudinal location. The Atlantic Nino reaches its peak in JJA, while much weaker SST anomalies appear north of the equator in JJA than in MAM, showing decaying of the interhemispheric SST mode. SST anomalies in the tropical central-eastern Pacific (the El Nino events) have a strong impact on tropical Atlantic including both the tropical north Atlantic and the equatorial-southern Atlantic. However, anomalous warming in the tropical north Atlantic following positive SST anomalies in the tropical Pacific disappears during JJA because of seasonal changes in the large-scale circulation cutting off the ENSO influence passing through the mid-latitudes. Hence the anomalies associated with the tropical Pacific during JJA are forced through an anomalous Walker circulation primarily working on the western basin, and likely a lagged oceanic response in the equatorial region.

Gu, Guojun↗

The Unexpected Oceanic Peak in Energy Input to the Atmosphere and Its Consequences for Monsoon Rainfall

Abstract Monsoons have historically been understood to be caused by the low thermal inertia of land, allowing more energy from summer insolation to be transferred to the overlying atmosphere than over adjacent ocean. Here, we show that during boreal summer, the global maximum net energy input (NEI) to the atmosphere unexpectedly lies over the Indian Ocean, not over land. Observed radiative fluxes suggest that cloud‐radiative effects (CRE) almost double the NEI over ocean, shifting the NEI peak from land to ocean. Global climate model experiments with both land and interactive sea surface temperatures confirm that CRE create the oceanic NEI maximum. Interactions between CRE, NEI, circulation, and land‐sea contrast in surface heat capacity shift precipitation from Southeast to South Asia. CRE thus alter the global partitioning of precipitation between land and ocean and the spatial structure of Earth's strongest monsoon, in ways that can be understood through the NEI.

54 ENVIRONMENTAL SCIENCES↗

Quantifying cover crop effects on soil health and productivity

The dataset presented here supports the research paper entitled “A calculator to quantify cover crop effects on soil health and productivity”. Soil health (sometimes used synonymously with soil quality) is a concept that describes soil as a living system to sustain plants, animals, and human. Soil physical, chemical, and biological properties, along with their interactions, are required to quantify soil health. The use of cover crops in agricultural rotations may enhance soil health, yet there has been little progress in understanding how external factors such as climate, soil type, and agronomic practices affect soil and cash crop responses. In response, this dataset compiles measurements from 281 studies and provides an analysis of field-measured changes in 38 soil health indicators due to cover crop usage. Environmental and background indicators were also compiled to assess how climatic and management practices affect soil and cash crop responses to cover crops, with specific categories including climate type (tropical, arid, temperate, and continental), soil texture (coarse, medium, and fine), cover crop type (legume, grass, multi-species mixture, and other), and cash crop type (corn, soybean, wheat, vegetable, corn-soybean rotation, corn-soybean-wheat rotation, and other). An unbalanced analysis of variation was used to determine the hierarchy of most to least important factors that affected responsiveness of each soil health indicator. Based on the hierarchy structure, a soil health calculator was then developed to quantify the response of 13 parameters – erosion, runoff, weed suppression, soil aggregate stability, leaching, infiltration, microbial biomass carbon, soil bulk density, soil organic carbon, soil nitrogen, microbial biomass nitrogen, cash crop yield, and saturated hydraulic conductivity – to cover crops. The presented data in the calculator report the mean change in parameter values based on all combinations of climate, soil texture, cover crop type, and cash crop type.

54 ENVIRONMENTAL SCIENCES↗

Data for Photosynthetic responses to temperature across the tropics: a meta-analytic approach

This data package contains raw data, data output, and code of photosynthetic temperature response curves from tropical forests. Data are used in "Photosynthetic responses to temperature across the tropics: a meta-analytic approach". The research investigates how photosynthetic optimum temperatures and shapes of photosynthetic temperature response curves varies across tropical forest climates and growth conditions. Growth climate variables include mean annual temperature, max and max temperature, diurnal temperature range, and aridity index. Meta-analysis combines 18 datasets with representation from Africa, Oceana, North American, and South America. Growth conditions analyzed considers deciduousness, successional status, light conditions, and whether plants are grown in situ or ex situ. All files, except for the raw datafile (Tropical_MetaAnalysis_Master_3.8.22_Edit.csv), have been processed using R code, which is provided.

54 ENVIRONMENTAL SCIENCES↗

Understanding the Recent Increase in Landfalling Tropical Cyclones Over Florida's Gulf Coast

Unlike Florida's Atlantic Coast, the Gulf Coast of Florida has seen heightened tropical cyclone (TC) activity in recent decades with several destructive landfalls. Here, we attempt to understand this regional contrast using a suite of observations for the period 1979–2024. First, we demonstrate that while the El Niño Southern Oscillation (ENSO), the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) can explain ~23% of the interannual variability in landfalls over the Gulf Coast, the variance explained by them for the Atlantic Coast is statistically insignificant. Next, we show that this striking difference may be attributed to the regional patterns of wind shear, steering flow and air-sea thermodynamic state excited by those modes of variability. The differential control exerted by ENSO, AMO, and NAO on landfalling Florida TCs, in combination with decadal trends in those modes, is likely responsible for the observed increases in landfalls over Florida's Gulf Coast.

Florida↗

Soybean fallow and nitrification inhibitors: Strategies to reduce N 2 O emission intensities and N losses in Australian sugarcane cropping systems

The Australian sugar industry is facing mounting pressure to reduce the nitrogen (N) losses and nitrous oxide (N 2 O) emissions associated with N fertiliser use. Research has shown that N 2 O emissions from sugarcane (Saccharum officinarum L.) cropping systems can be reduced with the use of fertilisers coated with nitrification inhibitors, or by sowing legume crops in the fallows between sugarcane crop cycles. However, the efficacy of these two N management strategies across different climatic zones is still unclear, as results from field studies have been contradictory. The objectives of this study were therefore to use the DayCent model to assess the long-term effects of the two strategies (separately or in combination) on N 2 O emissions, N losses and yields. The model was parameterised using data from eight field experiments (39 treatments) conducted across four of the five main districts of the Australian sugarcane industry. A series of long-term scenarios embracing a range of N fertiliser rates (0- 160 kg N ha -1 applied as urea), climatic regions (Tropics and Subtropics), soil textures (fine- and coarse-textured soils) and N-loss risk scenarios (crop fertilised well before or close to the on-set of the wet season) were tested for both N management strategies. Simulations identified that the combined use of soybean (Glycine max L.) fallows and N fertiliser coated with the 3,4-dimethylpyrazole phosphate (DMPP) nitrification inhibitor was the most effective strategy to maintain or even increase current yields while significantly reducing N 2 O and cumulative N (mainly due to nitrate) losses. When used alone, the soybean fallow strategy on average reduced N losses over the entire crop cycle by 29 % compared with current industry best practice. However, this strategy showed a limited capacity to reduce N 2 O emissions over the entire cane crop cycle (median: -3% compared with current industry best practice), or even increased them in scenarios at high-risk of N losses in the Tropics. The use of urea coated with DMPP alone allowed current fertiliser N rates to be reduced by 30 % without any substantial yield penalty. In environments prone to high N losses, DMPP urea abated overall N losses and N 2 O emissions by 41 % and 30 %, respectively. This was the first study to use such an extensive dataset to parameterise a biogeochemical model for yields, N 2 O emissions and N losses in sugarcane cropping systems. Finally, the findings will be instrumental in guiding future research and policies designed to improve the profitability and environmental sustainability of this industry.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of the Shallow‐To‐Deep Convective Transition to Moisture and Wind Shear in the Amazon

Deep convection is the primary influence on weather and climate in tropical regions. However, understanding and simulating the shallow‐to‐deep (STD) convective transition has long been challenging. Here, we conduct high‐resolution numerical simulations to assess the environmental controls on the evolution of isolated convection in the Amazon during the wet season. The large‐scale forcing derived through a constrained variational analysis approach for the GoAmazon2014/5 Experiment is used in the simulations. Through sensitivity experiments, we examine the relative importance of moisture and wind shear in controlling the shallow‐to‐deep convective transition for isolated convective events. Convection exhibits the greatest sensitivity to humidity within the lowest 1.5 km, where a 4 mm reduction in column water vapor nearly suppresses ice water formation on deep convective days. In contrast, a reduction in column water vapor in the free troposphere by a factor of two or more is necessary to produce a comparable impact on convection. Increasing low‐level wind speed from 6 to 9 m s -1 enhances afternoon deep convection, raising the cloud ice mixing ratio by approximately 25%. Conversely, upper‐level wind shear reveals the weakest correlation with daytime convection in our simulations. Our results help characterize the role of moisture and wind shear on the STD transition and our understanding of the underlying mechanisms.

environmental controls↗

Litterfall and Branchfall Mass Flux in Malaysia Lambir Hills GEM plots (2008-2010)

This data package includes two folders: Litterfall and Branchfall. The Litterfall folder includes three files: "GEM_Lambir_Hills_Litterfall_Mass_Flux_Data_2008_to_2010.csv" includes the litterfall data, the "GEM_Lambir_Hills_Litterfall_Metadata.xlx" includes the descripion of the columns in the data file, and the PDF file "GEM_Lambir_Hills_Litterfall_Methods_Description" includes a brief description of the litterfall sampling methods. The Branchfall Folder includes four files: the "GEM_Lambir_Hills_Branchfall_Data_2009_to_2010.csv" file includes the branchfall data, the "GEM_Lambir_Hills_Branchfall_Metadata_2009_to_2010.xlsx" includes the description of the columns in the csv data file, the "GEM_Lambir_Hills_Branchfall_Methods_Description.pdf" includes a brief description of the branchfall collection methods, and the "GEM_Lambir_Hills_Branchfall_Data_Metadata_Methods_TransectSums.xlx" includes data, metadata, methods description, and a 'TransectsSums' tab where the reader can find the sum of the branchfall data in each transect Litterfall and Branchfall data were collected to quantify canopy productivity and net primary productivity allocated to branch turnover, which are components of the total net primary productivity and ecosystem carbon budget. The methods follow the Global Ecosystems Monitoring (GEM) protocols (see gem.tropicalforests.ox.ac.uk). The data collection took place from 2008 to 2010 in two 1-ha GEM plots in Lambir Hills National Park, Sarawak, Malaysia, within the Lambir 52-ha ForestGEO plots. One of the plots was located on clay soil and the other on sandy loam. The site is an old-growth moist tropical forest dominated by Dipterocarpacea. The climate is moist tropical and aseasonal. Litterfall was collected biweekly from 25 litter traps per plot. Branchfall was estimated using four 100-m transects, which were surveyed every two months.

54 ENVIRONMENTAL SCIENCES↗

A Numerical Study of Tropical Sea-Air Interactions Using a Cloud Resolving Model Coupled with an Ocean Mixed-Layer Model

Coupling a cloud resolving model (CRM) with an ocean mixed layer (OML) model can provide a powerful tool for better understanding impacts of atmospheric precipitation on sea surface temperature (SST) and salinity. The objective of this study is twofold. First, by using the three dimensional (3-D) CRM-simulated (the Goddard Cumulus Ensemble model, GCE) diabatic source terms, radiation (longwave and shortwave), surface fluxes (sensible and latent heat, and wind stress), and precipitation as input for the OML model, the respective impact of individual component on upper ocean heat and salt budgets are investigated. Secondly, a two-way air-sea interaction between tropical atmospheric climates (involving atmospheric radiative-convective processes) and upper ocean boundary layer is also examined using a coupled two dimensional (2-D) GCE and OML model. Results presented here, however, only involve the first aspect. Complete results will be presented at the conference.

Shie, Chung-Lin↗