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Michelle Y. Wong

Publications and source records attributed to Michelle Y. Wong.

2 recordsLinked to original sources

Blind spots in our understanding of the tropical nitrogen cycle

Understanding environmental controls on tropical nitrogen (N) cycling is critical for projecting flux rates and modeling ecosystem responses to rising CO 2 . Here, we ask whether geographic bias in field sampling may shape our understanding of N cycling by failing to capture the breadth of environmental heterogeneity within the tropics. We mapped empirical sampling locations of two major ecosystem N inputs and outputs—biological nitrogen fixation and denitrification—paired with a wide range of variables thought to influence N cycling. Both single and multi-variate analyses revealed that sampling density is greater in productive, wet, fertile, warmer tropical ecosystems with low seasonality—areas expected to have higher process rates—but biased away from spatially extensive biomes which may have high process rate variability and thus higher uncertainty. Even within tropical broadleaf forests, sampling is biased toward sites with unusually high soil fertility (N and phosphorus), potentially skewing biome-wide averages. Although some geographically undersampled regions share environmental characteristics with well-studied sites, others are unique, compromising inference from existing data. Finally, we find that while sampled field locations capture the range of N cycle process means/variances predicted by an ensemble of terrestrial biosphere models, this may be the result of circularity in model parameters and driving data rather than true coverage, including overrepresentation of forest plant functional types that may be parameterized from a small subset of sites. Data coverage expansion into areas with novel environmental conditions and higher uncertainty could be used to assess and improve model parameterization, as well as test general hypotheses.

Global Biogeochemical Cycles↗

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

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 (Hengl et al ., 2017 ), contain c . 30% of terrestrial C stocks (Jobbagy & Jackson, 2000 ), and have some of the largest stores of fine-root biomass globally (Jackson et al ., 1996 ), as well as higher fine-root production and turnover rates compared with other biomes (Cusack et al ., 2021 ). Tropical forest responses to projected warming, altered rainfall regimes, and elevated CO 2 concentrations (IPCC, 2021 ) 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 108 th 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 ).

New Phytologist↗