Biology subjects

Boyer, D.

Publications and source records attributed to Boyer, D..

9 recordsLinked to original sources

bioRxiv2023

Harvesting trajectories in large-scale coffee plantations: ecological and management drivers and implications

CONTEXTCoffee is produced under different management systems and scales of production categorized as Syndromes of Production. The "Capitalist Syndrome" is characterized by the high use of capital and labor inputs to increase agricultural outputs. This syndrome results in practices like high planting densities that may promote the development and dispersal of plant pathogens like coffee leaf rust. The spatial arrangement of coffee trees drives the spatial movement of the harvesters, who can bear and disperse pathogens across and within plantations. In most capitalist coffee plantations, harvesters work multiple hours to maximize the daily harvest, which might increase their dispersal potential. However, their spatial movement has not yet been described, nor its relationship with the scale or management of the plantation, and even less its ecological implications for pathogens dispersal. OBJECTIVEWe describe and analyze the daily spatial movement of coffee harvesters in two large-scale capitalist plantations: an organic and a conventional plantation. METHODSUsing state-space models, we recorded and analyzed the spatial movements of harvesters. We then constructed a driver tree for harvest dynamics, which incorporated qualitative variables related to climate, coffee plants, and management aspects reported by the harvesters. RESULTS AND CONCLUSIONSOur model differentiated two kinds of movements: 1) when trees have berries, harvesters remain in the coffee rows or areas nearby (Collect state; 94-98% of the steps); 2) when not, harvesters make longer steps within the harvesting location or move to another area (Search state; 2-6% of the steps). In the organic plantation, the Search state had a longer-tailed step-length distribution than in the conventional plantation, resulting in a significantly higher visited area per worker (p<0.05). This might be related to a) a lower fruit load or percentage of trees with ripe fruits when we took the data or b) smaller harvesting locations ("pantes") per number of harvesters. Harvesting movements that explore a wider area, either by visiting more plants or by changing locations on the same day, could create more foci of CLR infection across the plantation. SIGNIFICANCEOur results highlight practices that can reduce the possible impact of human dispersal of pathogens like shorter harvesting trajectories by working fewer hours a day or avoiding harvesting at the end of the maturation season when few trees have berries and harvesters have to travel longer distances. This calls for organic coffee management that could prevent diseases, increase diversity, and guarantee just and safe conditions for workers.

ecology↗

bioRxiv2023

Levy movements and a slowly decaying memory allow efficient collective learning in groups of interacting foragers

Many animal species benefit from spatial learning to adapt their foraging movements to the distribution of resources. Learning involves the collection, storage and retrieval of information, and depends on both the random search strategies employed and the memory capacities of the individual. For animals living in social groups, spatial learning can be further enhanced by information transfer among group members. However, how individual behavior affects the emergence of collective states of learning is still poorly understood. Here, with the help of a spatially explicit agent-based model where individuals transfer information to their peers, we analyze the effects on the use of resources of varying memory capacities in combination with different exploration strategies, such as ordinary random walks and Levy flights. We find that individual Levy displacements associated with a slow memory decay lead to a very rapid collective response, a high group cohesion and to an optimal exploitation of the best resource patches in static but complex environments, even when the interaction rate among individuals is low. Author SummaryHow groups of social animals collectively learn to find and exploit resources in complex environments is not well-understood. By means of a computational model where individuals are initially spread out across a landscape, we study the effects of individual exploratory behaviors and memory capacities on the emergence of spatial learning. Collective learning emerges spontaneously only if group members transfer information between each other at a sufficiently high rate, so that individual experiences can be used by others. In static but heterogeneous environments with many resource sites of varying attractiveness, we find that random displacements over many spatial scales combined with a slow memory decay lead to a rapid collective response and highly cohesive groups. Collective learning is noticeable through an optimal exploitation of the best resource sites, which far exceeds what individuals would achieve on their own. Our study sheds light on important mechanisms responsible for collective learning in ecology, with potential applications in other areas of science.

animal behavior and cognition↗

bioRxiv2022

Structural polymorphism of amyloid fibrils in cardiac ATTR amyloidosis revealed by cryo-electron microscopy

The deposition of amyloidogenic transthyretin (ATTR) in ATTR amyloidosis leads to an unexplained variety of clinical phenotypes, including cardiomyopathy. In brain amyloid conditions, there is an apparent association between the clinical phenotype and the amyloid fibril structure. Here, we question this phenotype-structure association in cardiac amyloidoses by determining the cryo-electron microscopy structures of fibrils extracted from the hearts of seven ATTR amyloidosis patients. We found that, in contrast to brain fibrils, cardiac ATTR fibrils display a structural polymorphism that is not genotype-specific, can co-exist within the same individual, and is independent of the cardiac phenotype. This polymorphism challenges the current paradigm of "one disease equals one fibril fold" proposed in tauopathies and synucleinopathies, and questions whether a similar structural heterogeneity occurs in other amyloidoses. One-Sentence SummaryUnlike brain amyloid fibrils, cardiac ATTR fibrils are polymorphic independent of genotype and even within the same patient.

molecular biology↗

bioRxiv2022

Dispersion and Plant Arrangement Condition the Timing and Magnitude of Coffee Rust Infection

One central issue in coffee-leaf rust (Hemileia vastatrix) epidemiology is to understand what determines the intensity and the timing of yearly infections in coffee plantations. However, most experimental and theoretical studies report infection as an average at the plot level, obscuring the role of potentially key factors like rust dispersal or the planting pattern. Here, we first review the rust epidemic patterns of different sites, which reveal large variability in the duration and magnitude of the different epidemiologic phases. We then present a spatially explicit and parametrised model, where the host population is subdivided into discrete patches linked through spore dispersal, modelled as simple diffusion. With this model, we study the role of the planting arrangement, the dispersal intensity and plant-level variables on the maximum average tree infection (MATI) and its timing. Our results suggest that the epidemic timeline can be divided into two phases: a time lag and a growth phase per se. The model shows that the combination of the dispersal magnitude and plant aggregation modifies the MATI and the time to MATI, mainly by preventing some plants from reaching their maximum peak during the epidemic. It also affects the epidemic curves, which can have a stepped, or a rather smooth pattern in plots with otherwise similar conditions. The initial rust infection modulates the time lag before the epidemic and the infected leaf-fall rate drastically changes the MATI. These findings highlight the importance of explicitly considering the spatial aspects of coffee agroecosystems when measuring and managing rust infection, and help us to further understand the spatio-temporal dynamics of ecological systems in general.

systems biology↗

bioRxiv2021

Hierarchical, Memory-based Movement Models for Translocated Elk (Cervus canadensis)

The use of spatial memory is well documented in many animal species and has been shown to be critical for the emergence of spatial learning. Adaptive behaviors based on learning can emerge thanks to an interdependence between the acquisition of information over time and movement decisions. The study of how spatio-ecological knowledge is constructed throughout the life of an individual has not been carried out in a quantitative and comprehensive way, hindered by the lack of knowledge of the information an animal already has of its environment at the time monitoring begins. Identifying how animals use memory to make beneficial decisions is fundamental to developing a general theory of animal movement and space use. Here we propose several mobility models based on memory and perform hierarchical Bayesian inference on 11-month trajectories of 21 elk after they were released in a completely new environment. Almost all the observed animals exhibited preferential returns to previously visited patches, such that memory and random exploration phases occurred. Memory decay was mild or negligible over the study period. The fact that individual elk rapidly become used to a relatively small number of patches was consistent with the hypothesis that they seek places with predictable resources and reduced mortality risks such as predation.

animal behavior and cognition↗

bioRxiv2021

Inhibition of amyloid formation of the Nucleoprotein of SARS-CoV-2

The SARS-CoV-2 Nucleoprotein (NCAP) functions in RNA packaging during viral replication and assembly. Computational analysis of its amino acid sequence reveals a central low-complexity domain (LCD) having sequence features akin to LCDs in other proteins known to function in liquid-liquid phase separation. Here we show that in the presence of viral RNA, NCAP, and also its LCD segment alone, form amyloid-like fibrils when undergoing liquid-liquid phase separation. Within the LCD we identified three 6-residue segments that drive amyloid fibril formation. We determined atomic structures for fibrils formed by each of the three identified segments. These structures informed our design of peptide inhibitors of NCAP fibril formation and liquid-liquid phase separation, suggesting a therapeutic route for Covid-19. One Sentence SummaryAtomic structures of amyloid-driving peptide segments from SARS-CoV-2 Nucleoprotein inform the development of Covid-19 therapeutics.

biochemistry↗

bioRxiv2021

High-order interactions maintain or enhance structural robustness of a coffee agroecosystem network

The capacity of highly diverse systems to prevail has proven difficult to explain. In addition to methodological issues, the inherent complexity of ecosystems and issues like multicausality, non-linearity and context-specificity make it hard to establish general and unidirectional explanations. Nevertheless, in recent years, high order interactions have been increasingly discussed as a mechanism that benefits the functioning of highly diverse ecosystems and may add to the mechanisms that explain their persistence. Until now, this idea has been explored by means of hypothetical simulated networks. Here, we test this idea using an updated and empirically documented network for a coffee agroecosystem. We identify potentially key nodes and measure network robustness in the face of node removal with and without incorporation of high order interactions. We find that the systems robustness is either increased or unaffected by the addition of high order interactions, in contrast with randomized counterparts with similar structural characteristics. We also propose a method for representing networks with high order interactions as ordinary graphs and a method for measuring their robustness. HighlightsO_LIThe robustness of a coffee-associated ecological network is either increased or unaffected by the incorporation of high order interactions. C_LIO_LIA method is proposed for representing high order interactions in ordinary networks. C_LIO_LIA method is proposed to measure the robustness of networks with high order interactions. C_LIO_LIHigh order interactions may promote the persistence of diverse ecosystems. C_LI

ecology↗

bioRxiv2020

SlicerMorph: An open and extensible platform to retrieve, visualize and analyze 3D morphology

Large scale digitization projects such as #ScanAllFishes and oVert are generating high-resolution microCT scans of vertebrates by the thousands. Data from these projects are shared with the community using aggregate 3D specimen repositories like MorphoSource through various open licenses. MorphoSource currently hosts tens of thousands of 3D scans of eukaryotes. Along with the data from similarly scoped projects such as 10kPhenomes, DigiMorph and many others, soon hundreds of thousands of specimens that represent biodiversity of extinct and extant organisms will be conveniently available to researchers. We anticipate an explosion of quantitative research in organismal biology with the convergence of available data and the methodologies to analyze them. Though the data are available, the road from a series of images to analysis is fraught with challenges for most biologists. It involves tedious tasks of data format conversions, preserving spatial scale of the data accurately, 3D visualization and segmentations, acquiring measurements and annotations. When scientists use commercial software with proprietary formats, a roadblock for data exchange, collaboration, and reproducibility is erected that hurts the efforts of the scientific community to broaden participation in research. Another relevant concern is that ultimate derivative data from individual research projects (e.g., 3D models of segmentation) are shared in formats that do not preserve the correct spatial scale of the data. In this paper, we present our effort to tackle challenges biologists face when conducting 3D specimen-based research. We developed SlicerMorph as an extension of 3D Slicer, a biomedical visualization and analysis ecosystem with extensive visualization and segmentation capabilities built on proven python-scriptable open-source libraries such as Visualization Toolkit and Insight Toolkit. In addition to the core functionalities of Slicer, SlicerMorph provides users with modules to conveniently retrieve open-access 3D models or import users own 3D volumes, to annotate 3D curve and patch-based landmarks, generate canonical templates, conduct geometric morphometric analyses of 3D organismal form using both landmark-driven and landmark-free approaches, and create 3D animations from their results. We highlight how these individual modules can be tied together to establish complete workflow(s) from image sequence to morphospace. Our software development efforts were supplemented with short courses and workshops that cover the fundamentals of 3D imaging and morphometric analyses as it applies to study of organismal form and shape in evolutionary biology, and extensive links to the existing tutorials are provided as supplemental material. Our goal is to establish a community of organismal biologists centered around Slicer and SlicerMorph to facilitate easy exchange of data and results and collaborations using 3D specimens. Our proposition to our colleagues is that using a common open platform supported by a large user and developer community ensures the longevity and sustainability of the tools beyond the initial development effort.

evolutionary biology↗

bioRxiv2018

A structure-based model for the electrostatic interaction of the N-terminus of protein tau with the fibril core of Alzheimer’s Disease filaments

Although portions of tau protein within the microtubule binding region have been shown to form the ordered core of tau filaments, the structural details of how other regions of tau participate in filament formation are so far unknown. In an attempt to understand how the N-terminus of tau may interact with fibril core, we crystallized and determined the structure of the N-terminal segment 5RQEFEV10 of tau. Several lines of evidence have shown the importance of this segment for fibril formation. The crystal structure reveals an out-of-register Class 5 steric zipper with a wet and a dry interface. To examine the possible interaction of 5RQEFEV10 with the tau fibril core, we modeled the binding of the wet interface of the 5RQEFEV10 structure with the 313VDLSKVTSKC322 region of the Alzheimers Disease tau filament structures. This model is consistent with, and helps to explain previous findings on the possible interaction of these two segments, distant in sequence. In addition, we discuss the possible conservation of this interaction across multiple polymorphs of tau.

biochemistry↗