Feedbacks among plant traits, animals and plant decomposition across species

Plant litter, created by mortality of plants and their senesced parts, is an important component of Earth’s ecosystems. The presence of plant litter influences numerous ecosystem functions such as those related to biogeochemical cycles, habitat formation, energy flow, hydrological processes, modification of geomorphological features. Despite having been explored for decades, there is still much to be learned about its versatile role in ecosystem functioning. As the fears over the ever-rising atmospheric CO2 concentration and alarming biodiversity decline have permeated through Academia and have eventually become matters of public concern in recent years, plant litter has become relevant to policies aimed at carbon control and biodiversity conservation. Plant litter preserves a sizeable portion of plant carbon and nutrients, most of which is released to the environment gradually via decomposition. Dead plant organic matter also provides vital resources (i.e., shelter, food and reproductive sites) for a myriad of organisms throughout the entirety of its decomposition trajectory, making it pivotal for detrital food webs, hence a biodiversity hotspot. These two functions, carbon control and biodiversity support, are closely connected as part of the organisms hosted by plant litter are themselves involved in its decomposition . There is therefore great interest in advancing our mechanistic understanding of plant decomposition, needed for improving global carbon cycle modeling and conservation strategies. Main research gaps addressed in this thesis While seminal studies have identified climate, substrate quality, and decomposer organisms as primary drivers of decomposition, the relative dominance of these factors remains debated. In addition, significant gaps persist in our understanding of the contributions of vertebrates to plant decomposition, with limited research addressing how these animals influence the decomposition process. The impact of plant litter on biodiversity, particularly the deadwood-dependent diversity as result of the interspecific interactions within decomposer communities, is also inadequately documented. Interspecific interactions among decomposers can significantly influence biodiversity by creating or modifying deadwood heterogeneity. However, the mechanisms through which these interactions shape biodiversity are poorly understood. In this thesis, I delve into the knowledge gaps on some of the important but overlooked ecological components crucial to plant decomposition and the concomitant (invertebrate) biodiversity. I dedicate three chapters of my doctoral thesis to rarely reported drivers of plant decomposition rates. I explore whether and how vertebrates control plant decomposition at the global scale in Chapter 2 by synthesizing existing literature. Additionally, Chapter 3 experimentally assesses the substantial role that a specific group of vertebrates, i.e. woodpeckers, play in deadwood decomposition. In Chapter 4, I look into how bark traits influence deadwood decomposition by modulating termite activity. Lastly, Chapter 5 explores the mechanisms shaping invertebrate biodiversity in deadwood, emphasizing how deadwood biodiversity is influenced by heterogeneity within deadwood and interspecific interactions. Chapter 6 will summarize and synthesize these four chapters and indicate remaining or emerging research gaps for further study

Dynamic feedbacks among tree functional traits, termite populations and deadwood turnover

Changes in the composition of plant functional traits may affect ecosystem processes through influencing trophic interactions. Bottom-up control by plant species through food availability to animals may vary with time. However, such dynamics and their consequences for deadwood turnover are poorly known for detrital food webs. We introduce a dynamic conceptual model of the feedback of tree functional traits, (deadwood-feeding) termite populations and deadwood decomposition. We hypothesized that tree functional diversity (in terms of a wood resource economic spectrum [WES]) supports the sustenance of termite populations via complementary food supplied through time, as deadwood varies in traits both initially across species and because of different decomposition rates. Simultaneously, driven by this temporal dynamics of food quality, the consumption of deadwood by termites should hypothetically sustain deadwood turnover in a functionally diverse forest over time. We tested our hypothesis through an 18-month termite-exclusion decomposition experiment by incubating coarse (i.e. 5 cm diameter) deadwood of 34 woody species in two subtropical forests in East China. One site still sustained a healthy population of pangolins as the keystone termite predator, whereas another had lost its pangolins due to hunting and illegal wildlife trade. The results supported our hypothesis: in the first 12 months, termites amplified the positive linear relationship between % wood mass loss and initial wood quality (WES). In contrast, between 12 and 18 months, termite-mediated consumption, and associated wood mass loss, showed a humpback relation with the initial WES. This shift in termite preference of deadwood species along the WES reflects complementary food availability to termites through time. Synthesis. Our findings imply that tree functional composition, with variation in deadwood quality through decomposition time, can help to sustain termite populations and thereby forest carbon turnover. Future studies need to test whether and how our conceptual model may apply to other detrital systems and food webs. In general, food web research would benefit from a stronger focus on temporal patterns for better understanding the interactions of basal resource functional traits and consumers on ecosystem functions

Influences of the bark economics spectrum and positive termite feedback on bark and xylem decomposition

The plant economics spectrum integrates trade-offs and covariation in resource economic traits of different plant organs and their consequences for pivotal ecosystem processes, such as decomposition. However, in this concept stems are often considered as one unit ignoring the important functional differences between wood (xylem) and bark. These differences may not only affect the performance of woody plants during their lifetime, but may also have important “afterlife effects.” Specifically, bark quality may strongly affect deadwood decomposition of different woody species. We hypothesized that (1) bark quality strongly influences bark decomposability to microbial decomposers, and possibly amplifies the interspecific variation in decomposition by invertebrate consumption, especially termites; and (2) bark decomposition has secondary effects on xylem mass loss by providing access to decomposers including invertebrates such as termites. We tested these hypotheses across 34 subtropical woody species representing five common plant functional types, by conducting an in situ deadwood decomposition experiment over 12-month in two sites in subtropical evergreen broad-leaved forest in China. We employed visual examination and surface density measurement to quantify termite consumption to both bark and the underlying xylem, respectively. Using principal component analysis, we synthesized seven bark traits to provide the first empirical evidence for a bark economics spectrum (BES), with high BES values (i.e., bark thickness, nitrogen, phosphorus, and cellulose contents) indicating a resource acquisitive strategy and low BES values (i.e., carbon, lignin, and dry matter contents) indicating a resource conservative strategy. The BES affected interspecific variation in bark mass loss and this relationship was strongly amplified by termites. The BES also explained nearly half of the interspecific variation in termite consumption to xylem, making it an important contributor to deadwood decomposition overall. Moreover, the above across-species relationships manifested also within plant functional types, highlighting the value of using continuous variation in bark traits rather than categorical plant functional types in carbon cycle modeling. Our findings demonstrate the potent role of the BES in influencing deadwood decomposition including positive invertebrate feedback thereon in warm-climate forests, with implications for the role of bark quality in carbon cycling in other woody biomes

In-silico prediction of disorder content using hybrid sequence representation

<p>Abstract</p> <p>Background</p> <p>Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge of the content of the intrinsic disorder in proteins is useful for a variety of studies including estimation of the abundance of disorder in protein families, classes, and complete proteomes, and for the analysis of disorder-related protein functions. The above investigations currently utilize the disorder content derived from the per-residue disorder predictions. We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based prediction of the disorder content.</p> <p>Results</p> <p>We hypothesize that sequence-level aggregation of input information may provide more accurate content prediction when compared with the content extracted from the local window-based residue-level disorder predictors. We propose a novel predictor, DisCon, that takes advantage of a small set of 29 custom-designed descriptors that aggregate and hybridize information concerning sequence, evolutionary profiles, and predicted secondary structure, solvent accessibility, flexibility, and annotation of globular domains. Using these descriptors and a ridge regression model, DisCon predicts the content with low, 0.05, mean squared error and high, 0.68, Pearson correlation. This is a statistically significant improvement over the content computed from outputs of ten modern disorder predictors on a test dataset with proteins that share low sequence identity with the training sequences. The proposed predictive model is analyzed to discuss factors related to the prediction of the disorder content.</p> <p>Conclusions</p> <p>DisCon is a high-quality alternative for high-throughput annotation of the disorder content. We also empirically demonstrate that the DisCon's predictions can be used to improve binary annotations of the disordered residues from the real-value disorder propensities generated by current residue-level disorder predictors. The web server that implements the DisCon is available at <url>http://biomine.ece.ualberta.ca/DisCon/</url>.</p

A Spin-dependent Machine Learning Framework for Transition Metal Oxide Battery Cathode Materials

Owing to the trade-off between the accuracy and efficiency, machine-learning-potentials (MLPs) have been widely applied in the battery materials science, enabling atomic-level dynamics description for various critical processes. However, the challenge arises when dealing with complex transition metal (TM) oxide cathode materials, as multiple possibilities of d-orbital electrons localization often lead to convergence to different spin states (or equivalently local minimums with respect to the spin configurations) after ab initio self-consistent-field calculations, which causes a significant obstacle for training MLPs of cathode materials. In this work, we introduce a solution by incorporating an additional feature - atomic spins - into the descriptor, based on the pristine deep potential (DP) model, to address the above issue by distinguishing different spin states of TM ions. We demonstrate that our proposed scheme provides accurate descriptions for the potential energies of a variety of representative cathode materials, including the traditional Li$_x$TMO$_2$ (TM=Ni, Co, Mn, $x$=0.5 and 1.0), Li-Ni anti-sites in Li$_x$NiO$_2$ ($x$=0.5 and 1.0), cobalt-free high-nickel Li$_x$Ni$_{1.5}$Mn$_{0.5}$O$_4$ ($x$=1.5 and 0.5), and even a ternary cathode material Li$_x$Ni$_{1/3}$Co$_{1/3}$Mn$_{1/3}$O$_2$ ($x$=1.0 and 0.67). We highlight that our approach allows the utilization of all ab initio results as a training dataset, regardless of the system being in a spin ground state or not. Overall, our proposed approach paves the way for efficiently training MLPs for complex TM oxide cathode materials

The Impact Of Road Pavement On Urban Heat Island (UHI) Phenomenon

An urban heat island (UHI) is a climatic phenomenon caused by modifications to the climate due to changes in the form and composition of the land surface and atmosphere. The aim of this study is to investigate the impact of road pavement types for mitigating or intensifying UHI. This study was conducted in the Kota Samarahan area. Since Kota Samarahan is classified as a suburban area, it is still a developing district. Hence, there is still an opportunity for proper planning, such as choosing the most suitable type of pavement, before this area becomes a UHI. Data was collected by studying four types of pavements (asphalt, concrete, permeable, and industrialised building system (IBS) StormPav) in terms of their characteristics, performance, and maintenance costs. Additionally, their surface temperatures were investigated using ThermaCam and then plotted against the surrounding air temperature. Interview sessions were also conducted with the personnel of Jabatan Kerja Raya to obtain valuable information for this research. As a result, this study found that the construction of asphalt pavement can produce numerous potential impacts on the environment, which further contribute to air pollution and the UHI effect. Concrete, permeable, and IBS StormPav pavements retained less heat compared to asphalt, and can be implement to mitigate the UHI phenomenon. Furthermore, the implementation of green walls, cool roofs, vegetation and trees, and altering the properties and construction of asphalt pavement can help in mitigating this phenomenon

Facilitation: Isotopic evidence that wood-boring beetles drive the trophic diversity of secondary decomposers

Deadwood heterogeneity is regarded as a primary causal driver of deadwood-associated soil biodiversity, but the underlying mechanisms remain elusive. This is partly due to the technical difficulties in disentangling and quantifying different components (e.g., deadwood is both habitat and food) of heterogeneity to which soil organisms may have context-dependent responses. Furthermore, non-trophic interactions, e.g., facilitation, also add complexity to deadwood heterogeneity-biodiversity relationships, yet their influences are unaccounted for in most deadwood biodiversity studies. To address these research gaps, we sampled isopod communities from 40 logs of two isotopically distinct tree species, which had been cut and incubated reciprocally for eight years in each of two environmentally contrasting sites (e.g., differences in background isotopic signatures and litter turnover rates). We then assessed the extent to which the variation in the biodiversity of isopod communities is explained by deadwood heterogeneity induced by wood-boring beetles. Stable isotope ratios (i.e., δ13C and δ15N) were employed to examine the response of trophic diversity of isopod communities to the rarely tested food facet of deadwood heterogeneity. We hypothesized the deadwood heterogeneity is boosted by wood-boring beetles and thereby positively affects the abundance, taxonomic diversity and trophic diversity of isopod communities. Our results supported this hypothesis: the abundance and Shannon and Simpson diversity as well as trophic diversity of isopods were positively correlated to wood-boring beetle tunnel densities in both sites and across the two tree species. We observed significant tree species and reciprocal treatment effects on the δ15N values of isopods in one of the two sites. This result suggested that the use of deadwood as food sources versus habitats by isopods is environmentally dependent. This study demonstrates that there is substantial heterogeneity within deadwood that promotes the diversity and trophic diversity of macroinvertebrates. This relationship is mediated by saproxylic beetle facilitation, with implications for the roles of saproxylic beetles and within-deadwood heterogeneity in determining microbial wood decomposition in temperate forests

What you don't know... can't hurt you? A natural field experiment on relative performance feedback in higher education

This paper studies the effect of providing feedback to college students on their position in the grade distribution by using a natural field experiment. This information was updated every six months during a three-year period. We find that greater grades transparency decreases educational performance, as measured by the number of examinations passed and grade point average (GPA). However, self-reported satisfaction, as measured by surveys conducted after feedback is provided but before students take their examinations, increases. We provide a theoretical framework to understand these results, focusing on the role of prior beliefs and using out-of-trial surveys to test the model. In the absence of treatment, a majority of students underestimate their position in the grade distribution, suggesting that the updated information is “good news” for many students. Moreover, the negative effect on performance is driven by those students who underestimate their position in the absence of feedback. Students who overestimate initially their position, if anything, respond positively. The performance effects are short lived—by the time students graduate, they have similar accumulated GPA and graduation rates

The Classification of the Persistent Infection Risk for Human Papillomavirus among HIV-Negative Men Who Have Sex with Men: Trajectory Model Analysis

Objective. To classify the infection risk of human papillomavirus (HPV) among human immunodeficiency virus- (HIV-) negative men who have sex with men (MSM) using group-based trajectory modeling (GBTM). Methods. This study collected data on demographic and sexual behavior characteristics by questionnaires at semiannual visits from March 1st, 2016 to December 31th, 2017. Researchers collected anal exfoliated cells to finish HPV testing and blood samples to finish HIV testing at baseline and follow-up visits. Accumulative infection numbers of different types of HPV as the primary outcome and the follow-up visits as the independent predicator to build a GBTM model. Results. There were 500 potentially eligible HIV-negative participants at baseline, 361 (72.2%) of whom were included in this study after screening. Three trajectory groups were identified as the best-fitted GBTM model. Trajectory 1, defined as decreased group (DG) accounted for 44.6% (161/361) of the sample, showed a declining pattern with visits. Trajectory 2, defined as flat group (FG) accounted for 49.6% (179/361) of the sample, showed a flat pattern with visits. Trajectory 3, regarded as the increased group (IG) accounted for 5.8% (21/361) of the sample, showed an uptrend. Compared to the DG, risk factors for the FG included receptive anal intercourse (AOR, 2.24; 95% CI, 1.36-3.71), occasional condom use in anal sex during the past six months (AOR, 1.90; 95% CI, 1.16-3.14), experience of transactional sex with males in the past year (AOR, 3.60; 95% CI, 1.12-11.54), and substance use (AOR, 1.81; 95% CI, 1.08-3.04). Risk factors for the IG included receptive anal intercourse (AOR, 2.81; 95% CI, 1.04-7.70), occasional condom use in anal sex during the past six months (AOR, 3.93; 95% CI, 1.40-11.01), and history of other STIs (AOR, 5.72; 95% CI, 1.40-23.46). Conclusion. The MSM data in this study showed three distinct developmental trajectories (DG, FG, and IG) of HPV infection among HIV-negative MSM, with receptive anal intercourse and occasional condom use in anal sex during the past six months being the risk factors associated with FG and IG