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Biology subjects

Zu, P.

Publications and source records attributed to Zu, P..

6 recordsLinked to original sources

Nectar chemistry reflects pollination strategies in alpine plant communities

Nectar is a primary floral reward, which can also deter non-specialist pollinators; yet, the role of complex nectar composition in plant-pollinator interactions and its relationship to other floral traits remain understudied, particularly in natural communities. We profiled the nectar metabolome of 43 co-occurring species in an alpine grassland to evaluate relationships among nectar chemistry, phylogeny, floral display traits and pollinator visitation. Field observations revealed a dominant bee vs fly visitation gradient. Several aggregated nectar traits tracked this gradient independently of plant phylogeny, indicating functional convergence: specifically, bee visitation was associated with higher nectar sucrose proportion, greater compound richness, and more divergent profiles of uncommon sugars. Nectar traits exhibited variable relationships to floral display traits, suggesting partial inter-trait phenotypic integration. Together, these findings indicate that detailed features of nectar composition, including phytochemical diversity, play a functional role in floral phenotypes, with previously unappreciated implications for plant-pollinator community ecology.

ecology↗

Causal discovery in biodiversity-mediated social-ecological systems

Global biodiversity loss and climate change exacerbate feedbacks within social-ecological systems, i.e., between ecosystems, their services and well-being of human societies. Our ability to mediate these feedbacks is hampered by incomplete understanding of the underlying causal links, which could benefit from interdisciplinary approaches to discover theoretical or empirical links from heterogeneous data characteristic of social-ecological studies. We propose a novel framework connecting literature-based causal knowledge with data-driven inference of causality. We test this framework for the highly biodiverse island of Borneo by conducting a systematic literature review of 7473 studies over 170 years, and a causal inference analysis for three conceptual causal diagrams connecting global change, socio-economics, ecosystem services, and biodiversity-ecosystem function using a set of 227 spatially explicit variables. We find that, while natural or social processes have been mostly studied independently, a set of studies already documents causal links across social-ecological domains for processes related to deforestation, food or energy. Causal discovery unveiled consistent negative causal links between global change, social-economic landscape, and biodiversity-ecosystem function, and positive causal links between global change and socio-economics, and these links were robust to indicator selection and addition. We detected few and weak links between social-economic landscape, global change, and ecosystem services. When comparing the data-driven inferred causal links to those documented by the literature, we find that links between biodiversity and ecosystem function with global change, and links between social-economic landscape and ecosystem services were also consistent, and causal analysis uncovered new (potential) causal links not yet described in the literature. Significance StatementAddressing climate change and biodiversity loss in the Anthropocene requires us to recognize that human societies and ecological systems are inherently interconnected in complex adaptive systems. Causal understanding in social-ecological systems enables understanding system dynamics and response to pressures and shocks. While promising, few studies have studied these systems using a combination of big literature which provides the state-of-the-knowledge and big data that provides the underlying information for causal discovery. With this framework, we can specify and rigorously test, causal links in biodiversity-mediated social-ecological processes under global change and examine potential interventions that lead to much needed sustainable outcomes.

ecology↗

Plant-insect chemical communication in ecological communities: an information theory perspective

Cross-species communication, where signals are sent by one species and perceived by others, is one of the most intriguing types of communication that functionally links different species to form complex ecological networks. Yet, global changes and human activities can affect communication by increasing the fluctuations of species composition and phenology, altering signal profiles and intensity, and introducing noises. So far, most studies on cross-species communication have focused on a few specific species isolated from ecological communities. Scaling up investigations of cross-species communication to the community level is currently hampered by a lack of conceptual and practical methodologies. Here, we propose an interdisciplinary framework based on information theory to investigate mechanisms shaping cross-species communication at the community level. We use plants and insects, the cornerstones of most ecosystems, as a showcase; and focus on chemical communication as the key communication channel. We first introduce some basic concepts of information theory, then we illustrate information patterns in plant-insect chemical communication, followed by a further exploration of how to integrate information theory into ecological and evolutionary processes to form testable mechanistic hypotheses. We conclude by highlighting the importance of community-level information as a vehicle to better understand the maintenance of ecological systems, especially when facing rapid global changes.

ecology↗

Towards a system-level causative knowledge of pollinator communities

Pollination plays a central role both in the maintenance of biodiversity and in crop production. However, habitat loss, pesticides, invasive species, and larger environmental fluctuations are contributing to a dramatic decline of numerous pollinators world-wide. This has increased the need for interventions to protect the composition, functioning, and dynamics of pollinator communities. Yet, how to make these interventions successful at the system level remains extremely challenging due to the complex nature of species interactions and the various unknown or unmeasured confounding ecological factors. Here, we propose that this knowledge can be derived by following a probabilistic causal analysis of pollinator communities. This analysis implies the inference of interventional expectations from the integration of observational and synthetic data. We propose that such synthetic data can be generated using theoretical models that can enable the tractability and scalability of unseen confounding ecological factors affecting the behavior of pollinator communities. We discuss a road map for how this probabilistic causal analysis can be accomplished to increase our system-level causative knowledge of natural communities.

ecology↗

Pollen sterols are associated with phylogenetics and environment but not with pollinators

O_LIPhytosterols are primary plant metabolites that have fundamental structural and regulatory functions. They are also essential nutrients for phytophagous insects, including pollinators, that cannot synthesize sterols. Despite the well-described composition and diversity in vegetative plant tissues, few studies have examined phytosterol diversity in pollen. C_LIO_LIWe quantified 25 pollen phytosterols in 122 plant species (105 genera, 51 families) to determine their composition and diversity across plant taxa. We searched literature and databases for plant phylogeny, environmental conditions, and pollinator guilds of the species to examine the relationships with pollen sterols. C_LIO_LI24-methylenecholesterol, sitosterol and isofucosterol were the most common and abundant pollen sterols. We found phylogenetic clustering of twelve individual sterols, total sterol content and sterol diversity, and of sterol groupings that reflect their underlying biosynthesis pathway (24 carbon alkylation, ring B desaturation). Plants originating in tropical-like climates (higher mean annual temperature, lower temperature seasonality, higher precipitation in wettest quarter) were more likely to record higher pollen sterol content. However, pollen sterol composition and content showed no clear relationship with pollinator guilds. C_LIO_LIOur study is the first to show that pollen sterol diversity is phylogenetically clustered and that pollen sterol content may adapt to environmental conditions. C_LI

biochemistry↗

Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa using a G-matrix

BackgroundAngiosperms employ an astonishing variety of visual and olfactory floral signals that are generally thought to evolve under natural selection. Those morphological and chemical traits can form highly correlated sets of traits. It is not always clear which of these are used by pollinators as primary targets of selection and which would be indirectly selected by being linked to those primary targets. Quantitative genetics tools for predicting multiple traits response to selection have been developed since long and have advanced our understanding of evolution of genetically correlated traits in various biological systems. We use these tools to predict the evolutionary trajectories of floral traits and understand the selection pressures acting on them. ResultsWe used data from an artificial and a pollinator (bumblebee, hoverfly) selection experiment with fast cycling Brassica rapa plants to predict evolutionary changes of 12 floral volatiles and 4 morphological floral traits in response to selection. Using the observed selection gradients and the genetic variance-covariance matrix (G-matrix) of the traits, we showed that the responses of most floral traits including volatiles were predicted in the right direction in artificial- and bumblebee-selection experiment, revealing direct and indirect targets of bumblebee selection. Genetic covariance had a mix of constraining and facilitating effects on evolutionary responses. We further revealed how G-matrices evolved in the selection processes. ConclusionsOverall, our integrative study shows that floral signals, and especially volatiles, evolve under selection in a mostly predictable way, at least during short term evolution. Evolutionary constraints stemming from genetic covariance affected traits evolutionary trajectories and thus it is important to include genetic covariance for predicting the evolutionary changes of a comprehensive suite of traits. Other processes such as resource limitation and selfing also needs to be considered for a better understanding of floral trait evolution.

evolutionary biology↗