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Biology subjects

Strand, O.

Publications and source records attributed to Strand, O..

4 recordsLinked to original sources

Chromosome-level genome assembly of Norwegian wild alpine reindeer (Rangifer tarandus tarandus)

We describe a chromosome-level genome assembly from a wild alpine reindeer individual (Rangifer tarandus tarandus) from the Rondane area in Southern Norway. The assembly is resolved into two pseudo-haplotypes: hap 1 spanning 3,081 megabases and hap 2 spanning 2,633 megabases. Contig N50 and scaffold N50 lengths are in the range of 31-41 Mb and 66-69 Mb, respectively. A large part of these two haplotypes (83.8% and 90.4%, respectively) are scaffolded into 34 autosomal chromosomal pseudomolecules, and in sex chromosomes X and Y for hap 1. The BUSCO completeness scores are 98.0% and 95.2%, respectively, and gene annotations of the assemblies identified 37,998 and 36,977 protein-coding genes. We also present an updated and improved genome assembly for Svalbard reindeer (Rangifer tarandus platyrhynchus) and a comparison with previously published genome assemblies of reindeer.

genomics↗

Rapid loss of genetic variation and increased inbreeding in small and isolated populations of Norwegian wild reindeer

Wildlife responses to habitat loss and fragmentation are a central concern in the management and conservation of biodiversity. Small and isolated populations are vulnerable, both due to demographic and genetic mechanisms, which are often linked. Thus, understanding how (changes in) genetic diversity, effective population sizes, and levels of inbreeding relate to population size and degree of isolation is key for developing effective conservation strategies. High-density Single Nucleotide Polymorphism (SNP) arrays represent an increasingly cost-efficient tool to achieve the data needed for such analysis. Here, we present the development of a novel 625k SNP array for reindeer Rangifer tarandus and apply this array to assess conservation genetic issues across thirteen Norwegian wild reindeer populations of varying size, isolation, and genetic origin (i.e., semi-domesticated reindeer origin or a mix of wild reindeer and semi-domesticated reindeer origins). Many of these populations are currently completely isolated, with no gene flow from other populations. We genotyped n = 510 individuals sampled by hunters and found that variation in population size across the populations largely predicted their (recent loss of) genetic variation (observed heterozygosity, Ho), as well as effective population size (Ne) and (change in) level of recent inbreeding. For the smallest and most isolated populations, with total population sizes of <50-100 individuals and a high and increasing level of recent inbreeding, estimated loss of genetic variation was as high as 3-10% over the time span of a generation or less, and estimated Ne was as low as six individuals. With the current level of isolation and associated lack of gene flow, and considering their already low genetic diversity, these populations are hardly viable - neither demographically nor genetically - in the long term. These results have direct relevance for the management of Norwegian wild reindeer, recently red-listed as Near Threatened. Yet, these genetic challenges, characterizing many of the small wild reindeer populations in Norway, have been largely ignored by management thus far. Mitigation efforts such as reducing barriers would introduce substantial conservation dilemma due to the aim of avoiding further spread of chronic wasting disease (CWD), as well as potential further domestic introgression into populations with genetically wild reindeer (or mixed) origin. Nevertheless, our cost-efficient and high-density SNP array especially designed for reindeer and caribou offers a powerful genetic tool to include in future monitoring, providing important contributions to management and conservation decisions.

genetics↗

Impacts of ocean acidification and warming on post-larval growth and metabolism in two populations of the great scallop (Pecten maximus L.)

Ocean acidification and warming are key stressors for many marine organisms. Some organisms display physiological acclimatisation or plasticity, but this may vary across species ranges, especially if populations are adapted to local climatic conditions. Understanding how acclimatisation potential varies among populations is therefore important in predicting species responses to climate change. We carried out a common garden experiment to investigate how different populations of the economically important great scallop (Pecten maximus) from France and Norway responded to variation in temperature and pCO2 concentration. After acclimation, post-larval scallops (spat) were reared for 31 days at one of two temperatures (13{degrees}C and 19{degrees}C) under either ambient or elevated pCO2 (pH 8.0 and pH 7.7). We combined measures of proteomic, metabolic, and phenotypic traits to produce an integrative picture of how physiological plasticity varies between the populations. The proteome of French spat showed significant sensitivity to environmental variation, with 12 metabolic, structural and stress-response proteins responding to temperature and/or pCO2. Principal component analysis revealed seven energy metabolism proteins in French spat that were consistent with countering ROS stress under elevated temperature. Oxygen uptake in French spat did not change under elevated temperature, but increased under elevated pCO2. In contrast, Norwegian spat reduced oxygen uptake under both elevated temperature and pCO2. Metabolic plasticity seemingly allowed French scallops to maintain greater energy availability for growth than Norwegian spat. However, increased physiological plasticity and growth in French spat may come at a cost, as French (but not Norwegian) spat showed reduced survival under elevated temperature. Summary StatementJuvenile scallops from France and Norway differ in their response to warming and acidification. French scallops show more physiological plasticity, adjusting their proteome and metabolism in order to maintain growth.

evolutionary biology↗

Estimating the cumulative impact and zone of influence of anthropogenic infrastructure on biodiversity

O_LIThe concept of cumulative impacts is widespread in policy documents, regulations, and ecological studies, but quantification methods are still evolving. Infrastructure development usually takes place in landscapes with preexisting anthropogenic features. Typically, their impact is determined by computing the distance to the nearest feature only, thus ignoring the potential cumulative impacts of multiple features. We propose the cumulative ZOI approach to assess whether and to what extent anthropogenic features lead to cumulative impacts. C_LIO_LIThe approach estimates both effect size and zone of influence (ZOI) of anthropogenic features and allows for estimation of cumulative effects of multiple features distributed in the landscape. First, we use simulations and an empirical study to understand under which circumstances cumulative impacts arise. Second, we demonstrate the approach by estimating the cumulative impacts of tourist infrastructure in Norway on the habitat of wild reindeer (Rangifer t. tarandus), a nearly-threatened species highly sensitive to anthropogenic disturbance. C_LIO_LISimulations show that analyses based on the nearest feature and our cumulative approach are indistinguishable in two extreme cases: when features are few and scattered and their ZOI is small, and when features are clustered and their ZOI is large. Empirical analyses revealed cumulative impacts of private cabins and tourist resorts on reindeer, extending up to 10 and 20 km, with different decaying functions. Although the impact of an isolated private cabin was negligible, the cumulative impact of cabin villages could be much larger than that of a single large tourist resort. Focusing on the nearest feature only underestimates the impact of cabin villages on reindeer. C_LIO_LIThe suggested approach allows us to quantify the magnitude and spatial extent of cumulative impacts of point, linear, and polygon features in a computationally efficient and flexible way and is implemented in the oneimpact R package. The formal framework offers the possibility to avoid widespread underestimations of anthropogenic impacts in ecological and impact assessment studies and can be applied to a wide range of spatial response variables, including habitat selection, population abundance, species richness and diversity, community dynamics, and other ecological processes. C_LI

ecology↗