Association mapping reveals loci associated with multiple traits that affect grain yield and adaptation in soft winter wheat

Genome-wide association studies (GWAS) are useful to facilitate crop improvement via enhanced knowledge of marker-trait associations (MTA). A GWAS for grain yield (GY), yield components, and agronomic traits was conducted using a diverse panel of 239 soft red winter wheat (Triticum aestivum) genotypes evaluated across two growing seasons and eight site-years. Analysis of variance showed significant environment, genotype, and genotype-by-environment effects for GY and yield components. Narrow sense heritability of GY (h ²  = 0.48) was moderate compared to other traits including plant height (h ²  = 0.81) and kernel weight (h ²  = 0.77). There were 112 significant MTA (p < 0.0005) detected for eight measured traits using compressed mixed linear models and 5715 single nucleotide polymorphism markers. MTA for GY and agronomic traits coincided with previously reported QTL for winter and spring wheat. Highly significant MTA for GY showed an overall negative allelic effect for the minor allele, indicating selection against these alleles by breeders. Markers associated with multiple traits observed on chromosomes 1A, 2D, 3B, and 4B with positive minor effects serve as potential targets for marker assisted breeding to select for improvement of GY and related traits. Following marker validation, these multi-trait loci have the potential to be utilized for MAS to improve GY and adaptation of soft red winter wheat.     

Spatial assessment of aesthetic services in a complex mountain region: combining visual landscape properties with crowdsourced geographic information

Context

Human and natural systems interact at multiple scales which are context specific in relation to ecosystem service supply. Scenic beauty is recognised as a cultural ecosystem service whose aesthetic value is perceived at a holistic landscape level.

Objectives

In this study we provide methodological advancements for assessing the relationship between landscape visual character and scenic beauty based on crowdsourced geographic information. The final aim is to demonstrate, through a case study application, an empirical method for mapping the scenic beauty of complex mountain landscapes from the perspective of observers which are realistically exposed to the environment being evaluated.

Methods

We propose a viewshed based approach which relies on visual indicators and the location of visitors retrieved by public image storage analysis. A cluster analysis was used to integrate visual characters of the landscape and visiting users’ preferences.

Results

Four different typologies of landscapes were finally characterized by distinct values of visual indicators. The spatial distribution of the landscape typologies presented a clustered pattern, allowing a regionalization of the landscape characters. The analysis of the visiting users’ provenance revealed that visual scale, naturalness and ephemera attract mainly foreign users, while imageability, complexity and historicity attract mostly domestic and local users.

Conclusions

The combination of crowdsourced images with visual indicators allows a systematic analysis of landscape scenic beauty properties. In all, by understanding how specific landscape characters contributes to aesthetic service provision we provide a tool for facilitating the visualization and interpretation of complex landscape characters.

     

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Context

Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.

Objectives

We compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.

Methods

We calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.

Results

Comparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.

Conclusions

This analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.

     

Participatory mapping of landscape values in a Pan-European perspective

Context

Human–nature interactions are reflected in the values people assign to landscapes. These values shape our understanding and actions as landscape co-creators, and need to be taken into account to achieve an integrated management of the landscape that involves civil society.

Objectives

The aim of this research was to increase the current knowledge on the most and least common landscape values perceived by local stakeholders, the patterns in the spatial distribution of values, and their connection to different socio-economic backgrounds and landscape characteristics across Europe.

Methods

The research consisted of a cross-site comparison study on how landscape values are perceived in six areas of Europe using Public Participation GIS surveys. Answers were analysed combining contingency tables, spatial autocorrelation and bivariate correlation methods, kernel densities, land cover ratios, and viewshed analyses. Results were discussed in the light of findings derived from other European participatory mapping studies.

Results

We identified shared patterns in the perception of landscape values across Europe. Recreation, aesthetics, and social fulfilment were the most common values. Landscape values showed common spatial patterns mainly related to accessibility and the presence of water, settlements, and cultural heritage. However, respondents in each study site had their own preferences connected to the intrinsic characteristics of the local landscape and culture.

Conclusions

The results encourage land planners and researchers to approach landscape values in relation to socio-cultural and bio-physical land characteristics comprehensibly, acknowledging the complexity in the relationship between people’s perception and the landscape, to foster more effective and inclusive landscape management strategies.

     

Conservation planning with spatially explicit models: a case for horseshoe bats in complex mountain landscapes

Context

Context Bats are considered as an ecological indicator of habitat quality due to their sensitivity to human-induced ecosystem changes. Hence, we will focus the study on two indicator species of bats as a proxy to evaluate structure and composition of the landscape to analyze anthropic pressures driving changes in patterns.

Objectives

This study develops a spatially-explicit model to highlight key habitat nodes and corridors which are integral for maintaining functional landscape connectivity for bat movement. We focus on a complex mountain landscape and two bat species: greater (Rhinolophus ferrumequinum) and lesser (Rhinolophus hipposideros) horseshoe bats which are known to be sensitive to landscape composition and configuration.

Methods

Species distribution models are used to delineate high-quality foraging habitat for each species using opportunistic ultrasonic bat data. We then performed connectivity analysis combining (modelled) suitable foraging habitat and (known) roost sites. We use graph-theory and the deviation in the probability of connectivity to quantify resilience of the landscape connectivity to perturbations.

Results

Both species were confined to lowlands (<1000 m elevation) and avoided areas with high road densities. Greater horseshoe bats were more generalist than lesser horseshoe bats which tended to be associated with broadleaved and mixed forests.

Conclusions

The spatially-explicit models obtained were proven crucial for prioritizing foraging habitats, roost sites and key corridors for conservation. Hence, our results are being used by key stakeholders to help integrate conservation measures into forest management and conservation planning at the regional level. The approach used can be integrated into conservation initiatives elsewhere.