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Assessing the body condition of wild animals is necessary to monitor the health of the population and is critical to defining a framework for conservation actions. Body condition indices (BCIs) are a non-invasive and relatively simple means to assess the health of individual animals, useful for addressing a wide variety of ecological, behavioral, and management questions. The Antillean manatee (Trichechus manatus manatus) is an endangered subspecies of the West Indian manatee, facing a wide variety of threats from mostly human-related origins. Our objective was to define specific BCIs for the subspecies that, coupled with additional health, genetic and demographic information, can be valuable to guide management decisions. Biometric measurements of 380 wild Antillean manatees captured in seven different locations within their range of distribution were obtained. From this information, we developed three BCIs (BCI 1  = UG/SL, BCI 2  = W/SL 3 , BCI 3  = W/(SL*UG 2 )). Linear models and two-way ANCOVA tests showed significant differences of the BCIs among sexes and locations. Although our three BCIs are suitable for Antillean manatees, BCI 1 is more practical as it does not require information about weight, which can be a metric logistically difficult to collect under particular circumstances. BCI 1 was significantly different among environments, revealing that the phenotypic plasticity of the subspecies have originated at least two ecotypes-coastal marine and riverine-of Antillean manatees., (© 2021. The Author(s).)

Cellulosic ethanol derived from fast growing C4 grasses could become an alternative to finite fossil fuels. With the potential to generate a major source of lignocellulosic biomass, maize has gained importance as an outstanding model plant for studying the complex cell wall network and also to optimize crop breeding strategies in bioenergy grasses. A genome-wide association study (GWAS) was conducted using a subset of 408 Recombinant Inbred Lines (RILs) from a Multi-Parent Advanced Generation Intercross (MAGIC) Population in order to identify single nucleotide polymorphisms (SNPs) associated with yield and saccharification efficiency of maize stover. We identified 13 SNPs significantly associated with increased stover yield that corresponded to 13 QTL, and 2 SNPs significantly associated with improved saccharification efficiency, that could be clustered into 2 QTL. We have pointed out the most interesting SNPs to be implemented in breeding programs based on results from analyses of averaged and yearly data. Association mapping in this MAGIC population highlight genomic regions directly linked to traits that influence the final use of maize. Markers linked to these QTL could be used in genomic or marker-assisted selection programs to improve biomass quality for ethanol production. This study opens a possible optimisation path for improving the viability of second-generation biofuels.