Biology subjects

McMahon, B. J.

Publications and source records attributed to McMahon, B. J..

4 recordsLinked to original sources

bioRxiv2026

Genomic status of the Eurasian curlew Numenius arquata : estimating Essential Biodiversity Variables and selection signals for a declining migratory bird

Understanding how contemporary population declines affect the genomic diversity and structure of threatened species is important for effective conservation. The Eurasian curlew (Numenius arquata) is experiencing severe population declines across Europe, with Ireland among the most extreme, showing declines exceeding 90% over 40 years. Genomic data are increasingly incorporated into policy and used to assess conservation status by estimating genetic diversity, differentiation, inbreeding, effective population size, and adaptive divergence. Such data for curlew is scarce, and the population structure among northern and north-western European breeding populations remains unclear. To address this, we generated whole-genome resequencing data for 56 curlews across Ireland, Britain and Sweden. Irish and British populations showed minimal interpopulation differentiation, but both were substantially differentiated from Sweden. This was apparent from principal component analysis, and admixture and FST analyses. Measures of genetic diversity (nucleotide diversity, heterozygosity, Watterson's{theta} ) were similar across populations. A slightly elevated Tajima's D in Ireland, along with elevated FROH in Ireland and Britain relative to Sweden, may be the early genomic signs of recent population declines. We identified locally selected candidate genes. These had putative roles in metabolic processes, the immune response, and were potentially associated with distinct migratory behaviours and environmental conditions. We find a potential lag in genomic effects of decline being detectable following population contraction. We also show highly migratory species can exhibit differentiation in ecologically relevant traits, potentially driven by high site fidelity. These findings warrant consideration in translocation planning and broader conservation strategies.

genomics↗

bioRxiv2025

Influence of mowing timing on the breeding success of an endangered ground-nesting migratory bird, Whinchat (Saxicola rubetra)

Ground-nesting birds in Europe are declining due to anthropogenic pressures that reducebreeding productivity. Agricultural intensification under the Common Agricultural Policy in Europe is a major driver of this for farmland species, including Whinchat (Saxicola rubetra), in Ireland. We collected data over five breeding seasons in the Shannon Callows, a stronghold for this species where seasonal flooding limits agricultural intensification. We recorded habitat characteristics, breeding activity, and phenological events to determine population growth rates and assess mowing impacts on breeding success. Mean fledging date was July 4th ({+/-} 9.28 days). We calculate that for the population to remain stable, with 80.6% brood survival, mowing should be delayed until July 14th (+ 9.28 SD days to allow for natural variation). It is well documented in the literature that early mowing significantly impacts Whinchat productivity. However, when modelling mowing date against Whinchat breeding success weak significance was found that disappeared when increasing sample size through simulations, suggesting that mowing timing alone is not a strong determinant of reproductive success. Other factors including habitat structure, prey availability, predation risk, and weather conditions likely interact to influence breeding outcomes and warrant further study. We present a valuable framework with five years of breeding data that can inform Whinchat conservation and highlight the need for longer-term studies considering additional factors including how weather conditions affect mowing and prey availability.

ecology↗

bioRxiv2023

Inbreeding or outbreeding depression? How to manage an endangered and locally adapted population of red grouse Lagopus scotica

The balance between the inbreeding and outbreeding continuum is a fundamental debate within conservation genomics. To inform this debate we use genome wide data to show that inbreeding is higher in Irish red grouse (Lagopus scotica) and that this smaller and isolated population exhibits divergence from the British. Outlier analysis identified divergence in several genomic regions linked to genes coding for ecologically important traits such as phenotypic differences in plumage colour and sequence divergence among coding regions in the melanin pathway. We also find differences among immune genes and loci involved in food intake and energy control. The two populations thus appear locally adapted. Divergence between the source and the target population when used for conservation aided restocking may have negative consequences if locally adapted alleles are swamped and/or maladapted genotypes are introduced, leading to outbreeding depression. While avoiding inbreeding by maintaining large populations is important, our study illustrates that conservationists and managers should also consider population divergence and local adaptation. We argue against translocations among Ireland and Britain as a conservation strategy. The results of our study demonstrate the value of focusing on local populations and habitat management when aiming to enhance the conservation status of specific species.

genomics↗

bioRxiv2022

Bayesian species distribution models integrate presence-only and presence-absence data to predict deer distribution and relative abundance.

The use of georeferenced information on the presence of a species to predict its distribution across a geographic area is one of the most common tools in management and conservation. The collection of high-quality presence-absence data through structured surveys is, however, expensive, and managers usually have more abundant low-quality presence-only data collected by citizen scientists, opportunistic observations, and culling returns for game species. Integrated Species Distribution Models (ISDMs) have been developed to make the most of the data available by combining the higher-quality, but usually less abundant and more spatially restricted presence-absence data, with the lower quality, unstructured, but usually more extensive and abundant presence-only data. Joint-likelihood ISDMs can be run in a Bayesian context using INLA (Integrated Nested Laplace Approximation) methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. These models, however, have only been applied to simulated data so far. Here, for the first time, we apply this approach to empirical data, using presence-absence and presence-only data for the three main deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km2 resolution across the island. Models predictions were associated to spatial estimate of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we validated the three species-specific models using independent deer hunting returns. Our work clearly demonstrates the applicability of spatially-explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unused and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies.

ecology↗