Biology subjects

Blasco, A.

Publications and source records attributed to Blasco, A..

5 recordsLinked to original sources

bioRxiv2024

Last-century vegetation dynamics in a highland Pyrenean national park and implications for conservation

Ecological records from before and after the creation of natural parks are valuable for informing conservation and restoration actions. Such records are often unavailable, but high-resolution paleoecological studies may provide useful information. This paper presents a sub-decadal paleoecological reconstruction of vegetation and landscape in a national park in the Pyrenean highlands, established in the 1950s. The park lands were traditionally been used for small-scale cultivation, extensive grazing, forest exploitation and, since 1910, hydroelectricity generation following the damming of numerous glacial lakes. A significant finding is that present-like forests, with negligible changes in composition, have dominated the landscape during the study period. Major vegetation changes involved shifts in forest cover, influenced by both climatic and anthropic factors. Interestingly, the creation of the park in 1955 and the initial restrictions on forest exploitation in 1975 did not significantly affect vegetation cover or composition. Forest expansion did not occur significantly until the 1980s when the park was enlarged, and forest exploitation was further restricted. This expansion peaked in the mid-1990s coinciding with a warming trend and a decrease in fire incidence, before declining due to warmer and drier climates. This decline in forest cover occurred concurrently with the ongoing global forest dieback phenomenon and may be exacerbated by the predicted global warming in this century, which could also increase fire incidence due to the accumulation of dead wood. Under current conservation measures, the main threats are global warming, fire and, on a more local scale, the massification of tourism. Expanding the park and implementing forest restoration actions on degraded terrains surrounding the park could only be beneficial.

ecology↗

bioRxiv2023

A continuous centennial Lateglacial-Early Holocene (15-10 cal kyr BP) palynological record from the Iberian Pyrenees and regional comparisons

This paper presents the first continuous (gap-free) Lateglacial-Early Holocene (LGEH) pollen record for the Iberian Pyrenees resolved at centennial resolution. The main aims are (i) to provide a standard chronostratigraphic correlation framework, (ii) to unravel the relationships between vegetation shifts, climatic changes and fire, and (iii) to obtain a regional picture of LGEH vegetation for the Pyrenees and the surrounding lowlands. Seven pollen assemblage zones were obtained and correlated with the stadial/interstadial phases of the Greenland ice cores that serve as a global reference. Several well-dated datums were also derived for keystone individual taxa that are useful for correlation purposes. Four vegetation types were identified, two of them corresponding to conifer and deciduous forests (Cf, Df) and two representing open vegetation types (O1, O2) with no modern analogs, dominated by Artemisia-Poaceae and Saxifraga-Cichiroideae, respectively. Forests dominated during interstadial phases (Bolling/Allerod and Early Holocene), whereas O1 dominated during stadials (Oldest Dryas and Younger Dryas), with O2 being important only in the first half of the Younger Dryas stadial. The use of pollen-independent proxies for temperature and moisture allowed the reconstruction of paleoclimatic trends and the responses of the four vegetation types defined. The most relevant observation in this sense was the finding of wet climates during the Younger Dryas, which challenges the traditional view of arid conditions for this phase on the basis of former pollen records. Fire incidence was low until the early Holocene, when regional fires were exacerbated, probably due to the combination of higher temperatures and forest biomass accumulation. These results are compared with the pollen records available for the whole Pyrenean range and the surrounding lowlands within the framework of elevational, climatic and biogeographical gradients. Some potential future developments are suggested on the basis of the obtained results, with an emphasis on the reconsideration of the LGEH spatiotemporal moisture patterns and the comparison of the Pyrenees with other European ranges from different climatic and biogeographical regions.

paleontology↗

bioRxiv2021

Compositional data analysis of microbiome and any-omics datasets: a revalidation of the additive logratio transformation

BackgroundMicrobiome and omics datasets are, by their intrinsic biological nature, of high dimensionality, characterized by counts of large numbers of components (microbial genes, operational taxonomic units, RNA transcripts, etc...). These data are generally regarded as compositional since the total number of counts identified within a sample are irrelevant. The central concept in compositional data analysis is the logratio transformation, the simplest being the additive logratios with respect to a fixed reference component. A full set of additive logratios is not isometric in the sense of reproducing the geometry of all pairwise logratios exactly, but their lack of isometry can be measured by the Procrustes correlation. The reference component can be chosen to maximize the Procrustes correlation between the additive logratio geometry and the exact logratio geometry, and for high-dimensional data there are many potential references. As a secondary criterion, minimizing the variance of the reference components log-transformed relative abundance values makes the subsequent interpretation of the logratios even easier. Finally, it is preferable that the reference component not be a rare component but well populated, and substantive biological reasons might also guide the choice if several reference candidates are identified. Results: On each of three high-dimensional datasets the additive logratio transformation was performed, using references that were identified according to the abovementioned criteria. For each dataset the compositional data structure was successfully reproduced, that is the additive logratios were very close to being isometric. The Procrustes correlations achieved for these datasets were 0.9991, 0.9977 and 0.9997, respectively. In the third case, where the objective was to distinguish between three groups of samples, the approximation was made to the restricted logratio space of the between-group variance. Conclusions: We show that for high-dimensional compositional data additive logratios can provide a valid choice as transformed variables that are (1) subcompositionally coherent, (2) explaining 100% of the total logratio variance and (3) coming measurably very close to being isometric, that is approximating almost perfectly the exact logratio geometry. The interpretation of additive logratios is simple and, when the variance of the log-transformed reference is very low, it is made even simpler since each additive logratio can be identified with a corresponding compositional component.

bioinformatics↗

bioRxiv2020

Improving Deconvolution Methods in Biology through Open Innovation Competitions: An Application to the Connectivity Map

Do machine learning methods improve standard deconvolution techniques for gene expression data? This paper uses a unique new dataset combined with an open innovation competition to evaluate a wide range of gene-expression deconvolution approaches developed by 294 competitors from 20 countries. The objective of the competition was to separate the expression of individual genes from composite measures of gene pairs. Outcomes were evaluated using direct measurements of single genes from the same samples. Results indicate that the winning algorithm based on random forest regression outperformed the other methods in terms of accuracy and reproducibility. More traditional gaussian-mixture methods performed well and tended to be faster. The best deep learning approach yielded outcomes slightly inferior to the above methods. We anticipate researchers in the field will find the dataset and algorithms developed in this study to be a powerful research tool for benchmarking their deconvolution methods and a useful resource for multiple applications.

genomics↗

bioRxiv2019

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant performance gains over established algorithms. These include algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research.

bioinformatics↗