Effects of Grazing Intensity on Belowground Carbon and Nitrogen Cycling

Livestock grazing activities substantially affect grassland ecosystem functions such as carbon (C) and nitrogen (N) cycles. Although numerous individual and synthesized studies had been conducted, how grazing, especially its intensity, affects belowground C and N cycling in grasslands remains poorly understood. In this chapter, our previous published studies were summarized to elucidate the 19 variables associated with belowground C and N cycling in response to livestock grazing across global grasslands. Overall, grazing significantly decreased belowground C and N pools in grassland ecosystems, with the largest decreases observed in microbial biomass C and N (21.62 and 24.40%, respectively). However, the response magnitude and directions of belowground C- and N-related variables largely depend on grazing intensities. Specifically, light grazing promoted soil C and N sequestration, whereas moderate and heavy grazing significantly accelerated C and N losses. This study highlights the importance of grazing intensity for belowground C and N cycling, which urges scientists to incorporate it into regional and global models for predicting human disturbance on global grasslands and assessing the climate-biosphere feedbacks accurately

Responses of soil respiration and ecosystem productivity to climate change in southern Great Plains.

The third is to investigate the role of precipitation on ecosystem carbon processes (i.e., biomass, litterfall, and soil respiration) along a natural precipitation gradient in southern Great Plains. Our results show that aboveground biomass (AGB), standing litter (ST), surface litter (SU), and soil respiration often linearly increased with an increase in precipitation along the gradient, although belowground biomass (BGB) and total biomass did not largely change. (Abstract shortened by UMI.)Terrestrial carbon processes, such as soil respiration and its components, net primary production (NPP), net ecosystem carbon exchange (NEE), and litterfall, are the important global change issues, which are related to carbon sequestration and ecosystem carbon-cycle feedback to climate change. This dissertation summarized four independent projects using experimental and modeling approaches. In the first study, I took advantage of two manipulative experiments---one long-term with a 2° C increase and yearly clipping (Experiment 1) and one short-term with a 4.4° C increase and doubled precipitation (Experiment 2)---to investigate main and interactive effects of warming, clipping, and doubled precipitation on soil respiration in a tallgrass prairie ecosystem. The transient responses to clipping were also studied in Experiment 2 (referred to as the transient study). On average, warming increased soil respiration by 13.0% ( p < 0.01) in Experiment 1, by 22.9% (p < 0.0001) in Experiment 2, and by 26.6% (p < 0.0001) in the transient study. Doubled precipitation resulted in an increase of 9.0% (p < 0.05) in soil respiration in Experiment 2. Yearly clipping did not significantly affect soil respiration (p = 0.66) in Experiment 1, while clipping decreased soil respiration by 16.1% (p < 0.05) in the transient study. No significant interactive effects among the experimental factors were statistically found on soil respiration or their temperature sensitivities except for the warmingxclipping interaction ( p < 0.05) in the transient study. The observed minor interactive effects relative to main ones suggest that results from single-factor experiments are useful in informing us of potential responses of soil respiration to multi-factor global change, at least in our ecosystem.In the second experiment, a long-term experiment was conducted to investigate effects of warming and yearly clipping on soil respiration and its components (autotrophic and heterotrophic respiration, RA and RH) in a tallgrass prairie ecosystem. Interannual variability of these fluxes was also examined. Using the deep-collar insertion to partition soil respiration, heterotrophic respiration accounted for approximately 66% of soil respiration over the six years. Warming treatment significantly stimulated soil respiration and its components (i.e., RA and RH) in most years. In contrast, yearly clipping significantly reduced soil respiration only in the last two years, although it decreased RH in every year of the study. Temperature sensitivity (i.e., apparent Q10 values) of soil respiration was slightly lower under warming (p>0.05) and reduced considerably by clipping (p< 0.05) compared to that in the control. However, warming did not change relative contributions of RA or RH to soil respiration. In addition, the apparent Q10 values for RA were higher than those for RH and soil respiration. Annual soil respiration did not vary substantially among years as precipitation did. The interannual variability of soil respiration may be mainly caused by precipitation distribution and summer severe drought. Our results suggest that the effects of warming and yearly clipping on soil respiration and its components did not result in significant changes in R H or RA contribution, and rainfall timing may be more important in determining interannual variability of soil respiration than the amount of annual precipitation

Don't Take This Out of Context! On the Need for Contextual Models and Evaluations for Stylistic Rewriting

Most existing stylistic text rewriting methods and evaluation metrics operate on a sentence level, but ignoring the broader context of the text can lead to preferring generic, ambiguous, and incoherent rewrites. In this paper, we investigate integrating the preceding textual context into both the $\textit{rewriting}$ and $\textit{evaluation}$ stages of stylistic text rewriting, and introduce a new composite contextual evaluation metric $\texttt{CtxSimFit}$ that combines similarity to the original sentence with contextual cohesiveness. We comparatively evaluate non-contextual and contextual rewrites in formality, toxicity, and sentiment transfer tasks. Our experiments show that humans significantly prefer contextual rewrites as more fitting and natural over non-contextual ones, yet existing sentence-level automatic metrics (e.g., ROUGE, SBERT) correlate poorly with human preferences ($\rho$=0--0.3). In contrast, human preferences are much better reflected by both our novel $\texttt{CtxSimFit}$ ($\rho$=0.7--0.9) as well as proposed context-infused versions of common metrics ($\rho$=0.4--0.7). Overall, our findings highlight the importance of integrating context into the generation and especially the evaluation stages of stylistic text rewriting.Comment: emnlp 2023 main camera read

Learning to translate by learning to communicate

We formulate and test a technique to use Emergent Communication (EC) with a pretrained multilingual model to improve on modern Unsupervised NMT systems, especially for low-resource languages. It has been argued that the currently dominant paradigm in NLP of pretraining on text-only corpora will not yield robust natural language understanding systems, and the need for grounded, goal-oriented, and interactive language learning has been highlighted. In our approach, we embed a modern multilingual model (mBART, Liu et. al. 2020) into an EC image-reference game, in which the model is incentivized to use multilingual generations to accomplish a vision-grounded task, with the hypothesis that this will align multiple languages to a shared task space. We present two variants of EC Fine-Tuning (Steinert-Threlkeld et. al. 2022), one of which outperforms a backtranslation-based baseline in 6/8 translation settings, and proves especially beneficial for the very low-resource languages of Nepali and Sinhala

Light effects on seedling growth in simulated forest canopy gaps vary across species from different successional stages

Tropical forests continue to suffer from various kinds of disturbances in the Anthropocene. An immediate impact of disturbances on forest ecosystems is the creation of numerous large and small canopy gaps, which dramatically affect forest structure and function. Yet, we know little about the effect of canopy gaps on forest successional trajectory. More specifically, the responses of seedlings from different successional stages to increased light intensity under large and small canopy gaps in understory remain unclear. In this study, dominant tree seedlings from early-, mid-, and late-successional stages were selected, respectively from a tropical montane forest in Hainan Island, China to study their growth rate, biomass and traits. Our results showed that the light condition under small canopy gaps (SG, 10–15% of full sunlight) and large canopy gaps (LG, 40–50% of full sunlight) induced greater increment of relative growth rates for seedlings from early- and mid-successional stages relative to that in late-successional stage. Both SG and LG also significantly increased photosynthesis rate, leaf area (LA), light saturation point (LSP), root mass ratio (RMR) and root: shoot ratio, but decreased specific leaf area (SLA) of seedlings across successional stages. Tree seedlings from the earlysuccessional stage displayed the greatest decrease in leaf mass ratio, increase in LA, LSP, and RMR, in comparison to those from mid- and late- successional stages. Light condition and SLA were the most important factors for seedlings’ relative growth rate across successional stages. SLA connected the interaction between the light condition and successional stage on seedlings’ growth, thereby jointly explaining the 93% variation of seedlings’ growth, combining with area-based light saturated rate of CO2 assimilation. Our study highlights the distinct effect of disturbance-induced canopy gaps on seedling regeneration in the understory in tropical forest due to the variation of light intensity. We suspect that the seedlings from late-successional stage will recover relatively slow after disturbances causing canopy losses, which can have detrimental impacts on structure feature an