Biology subjects

McHale, M.

Publications and source records attributed to McHale, M..

4 recordsLinked to original sources

bioRxiv2025

Tracking savanna vegetation structure in South Africa by extension of GEDI canopy metrics with Landsat, Sentinel-2, and PALSAR

1Adaptive management of savanna ecosystems requires frequent monitoring of woody vegetation structure, and although vegetation structure and changes may be captured with repeat airborne lidar, it is spatially and temporally limited across African savannas. As an alternative, this study evaluates the extension of spaceborne waveform lidar canopy metrics (RH98, Cover, Foliage Height Diversity) from the Global Ecosystem Dynamics Investigation (GEDI) across the Greater Kruger region in South Africa using moderate resolution optical sensors (Landsat and Harmonized Landsat Sentinel-2 [HLS]), L-band Synthetic Aperture Radar (PALSAR-1 and -2), and topographic and soil covariates. We compared the performance of 14 predictor sets incorporating different sensor combinations and temporal processing methods (LandTrendr and CCDC) in random forest models using temporal cross-validation to assess extrapolation accuracy. The most parsimonious fusion model (LandTrendr + SAR + topography/soils) achieved RMSEs of 3.04 m for RH98, 13.38% for Cover and 0.34 for FHD, which was comparable to more complex models using HLS and CCDC. All models demonstrated good temporal transferability with minimal bias but tended to overestimate low values and underestimate high values, which muted the estimated magnitude of change. Annual canopy structure maps derived from the best model captured expected spatial patterns and were used in model-based estimators to quantify changes in areas impacted by elephants, timber harvesting, fuelwood extraction, and woody encroachment. Extending GEDI metrics with moderate-resolution sensors thus offers a viable approach for large-scale savanna monitoring and detecting change in high impact areas.

ecology↗

bioRxiv2024

Draft genome of Palmaria palmata and intraspecific genetic variations in the North-East Atlantic

The rhodophyte Palmaria palmata (L.) Weber & Mohr is one of the target species of a growing European seaweed industry due to its high content of protein and essential amino acids which makes it suitable for human food, dietary supplements, and as salmon feed. However, the lack of a published nuclear genome limits phylogenetics analyses and gene function investigations which could help the development of a breeding programme. We present the first draft genome of P. palmata that was obtained with PacBio HiFi long read sequencing with average coverage of 10x, consisting of an assembly of 1.05 Gb, N50=2.75Mb and BUSCO completeness of 72.1%. Additionally, a population study on the whole genome of 33 P. palmata individuals from across the Northern East Atlantic area found three main clusters consistent with their geographic distribution: (1) Denmark and Norway, (2) France and western Ireland, (3) Faroe Islands. All individuals from Northern Ireland share ancestry with western Ireland and Denmark, and some individuals from the Faroe Islands show admixture from Faroe, western Ireland and Northern Ireland. These results represent a fundamental step towards breeding and genetic studies to further explore the vastly unexploited economic potential of Palmaria palmata. Highlights- We report the first draft genome of Palmaria palmata, from PacBio HiFi long reads. - The size of the genome, 1.05 Gb, is among the largest so far among the Rhodophyta. - Busco completeness of 72.1% and contig N50 of 2.75 Mb indicate good quality. - The genomes of 33 more individuals from North Atlantic Europe have been sequenced. - Phylogenetic analysis found three clusters consistent with geographic distribution.

genomics↗

bioRxiv2024

AlGrow: a graphical interface for easy, fast and accurate area and growth analysis of heterogeneously colored targets.

Image analysis is widely used in plant biology to determine growth rates and other phenotypic characters, with segmentation into foreground and background being a primary challenge. Statistical clustering and learning approaches can reduce the need for user input into this process, though these are computationally demanding, can generalise poorly and are not intuitive to end users. As such, simple strategies that rely on the definition of a range of target colors are still frequently adopted. These are limited by the geometries in color space that are implicit to their definition; i.e. thresholds define cuboid volumes and selected colors with a radius define spheroid volumes. A more comprehensive specification of target color is a hull, in color space, enclosing the set of colors in the image foreground. We developed AlGrow, a software tool that allows users to easily define hulls by clicking on the source image or a three-dimensional projection of its colors. We implemented convex hulls and then alpha-hulls, i.e. a limit applied to hull edge length, to support concave surfaces and disjoint color volumes. AlGrow also provides automated annotation by detecting internal circular markers, such as pot margins, and applies relative indexes to support movement. Analysis of publicly available Arabidopsis image series and metadata demonstrated effective automated annotation and mean Dice coefficients of >0.95 following training on only the first and last images in each series. AlGrow provides both graphical and command line interfaces and is released free and open-source with compiled binaries for the major operating systems.

bioinformatics↗

bioRxiv2020

A Solanum lycopersicoides reference genome facilitates biological discovery in tomato

Wild relatives of tomato are a valuable source of natural variation in tomato breeding, as many can be hybridized to the cultivated species (Solanum lycopersicum). Several, including Solanum lycopersicoides, have been crossed to S. lycopersicum for the development of ordered introgression lines (ILs). Despite the utility of these wild relatives and their associated ILs, limited finished genomes have been produced to aid genetic and genomic studies. We have generated a chromosome-scale genome assembly for Solanum lycopersicoides LA2951 using PacBio sequencing, Illumina, and Hi-C. We identified 37,938 genes based on Illumina and Isoseq and compared gene function to the available cultivated tomato genome resources, in addition to mapping the boundaries of the S. lycopersicoides introgressions in a set of cv. VF36 x LA2951 introgression lines (IL). The genome sequence and IL map will support the development of S. lycopersicoides as a model for studying fruit nutrient/quality, pathogen resistance, and environmental stress tolerance traits that we have identified in the IL population and are known to exist in S. lycopersicoides.

genomics↗