Predicting potential winter wheat yield losses caused by multiple disease systems and climatic conditions

Despite the ongoing evolution of wheat pathogens due to the selection pressures of agro-ecological conditions, many studies have often overlooked the combined impact of both biotic and abiotic factors on disease occurrence. From 2016 to 2023, a comprehensive screening of obligate pathogens, including B. graminis f. sp. tritici, P. graminis f. sp. tritici, P. triticina, and P. striiformis f. sp. tritici, was carried out. This screening was conducted on a phenotyping platform encompassing 2715 winter wheat genotypes and their wild relatives, both with and without resistant genes (Lr, Yr, and Sr) for rust diseases. The data were analyzed using PCAmix, best subsets regression, and linear regression modeling. The findings from this study reveal that the plant reactions to leaf and yellow rust infections is far from straightforward. It is heavily influenced not only by prevalent rust races and climatic factors that impact pathogen life cycles but also by variations in the susceptibility reactions of wheat genotypes to the broader agro-ecological conditions. We also observed a tendency for leaf rust and yellow rust to coexist within the same host plant, even though yellow rust is typically considered more aggressive. We reported for the first time genes related to yellow rust resistance breakdown in Serbia in 2023. Lastly, we underscored the importance of investigating resistance responses to rust diseases not exclusively through the interrelation between resistance genes and pathogen virulence, but also by considering how plants respond to the combined stresses of abiotic and biotic factors. Consequently, our study sets the groundwork for further research into how plants respond to multiple stressors and contributes for further investigations related with effective integrated rust management.

Test the relative importance of biotic and abiotic factors on species distribution – A case study in the Yellow River Delta

Objective. To form a special collection of lines with marker genes of watermelon for use in hybrid breeding (heterosis) and for providing initial material to scientific and educational institutions. Object. 37 lines with marker genes of common watermelon (Citrullus lanatus (Thunb.) Matsum. et Nakai). Methods. General scientific, measurement and weight analysis, computational, statistical methods. Results. A screening of watermelon lines with marker genes (Citrullus lanatus (Thunb.) Matsum. et Nakai) was conducted based on phenological, morphological, economically valuable traits, and resistance to abiotic and biotic factors. Work was carried out to form a special watermelon collection, which includes 37 lines with marker genes, all developed at the Institute of Vegetable and Melon Growing of NAAS. The collection was created based on biological and morphological traits, resistance to biotic and abiotic factors, and the chemical composition of fruits – using 42 characteristics and 186 levels of expression, with standard reference samples identified for each trait. A working database of the collection was developed, containing information on 20 biological, morphological, economically valuable, and chemical traits, resistance to biotic and abiotic factors, and the presence of marker genes in each line of the collection. The samples in the collection are intended for use in breeding heterotic hybrids of watermelon as parental lines containing marker genes that determine specific signal traits. As a result of the analysis based on a complex of economically valuable traits, a number of lines were identified that can be recommended as parental components for heterosis breeding, serving as sources of individual or combined valuable traits. Most samples combine high yield, monoecy, earliness, a high content of biochemical compounds, adaptability to extreme climatic conditions, and resistance to diseases. Based on the evaluation of economically valuable traits, the most productive samples (approximately 35 t/ha) were identified for use as parental forms to increase yield in the development of competitive heterotic hybrids. Lines that serve as sources of earliness (vegetation period <70 days) were also identified. According to the assessment of resistance to biotic and abiotic factors, lines with significant value for use as parental forms were selected to enhance disease resistance, heat tolerance, and cold tolerance in the creation of competitive heterotic watermelon hybrids. Conclusions. A special collection of watermelon lines with marker traits has been formed. The collection comprises 37 samples with marker genes. It was developed based on biological and morphological traits, resistance to biotic and abiotic factors, and the chemical composition of fruits – covering 42 traits with 186 levels of expression. Reference samples have been identified for each trait. A working database of the collection was created, containing information on 20 biological, morphological, economically valuable, and chemical traits, as well as resistance to biotic and abiotic stress factors and the presence of marker genes in each line. The collection is intended for use as parental forms to enhance yield, earliness, disease resistance, heat tolerance, and cold tolerance in the development of competitive heterotic watermelon hybrids.

The interest in understanding ecosystem functioning has grown in recent years due to the effects of species loss on ecosystem processes. Even though biotic and abiotic factors control ecosystem processes, their relative influence may vary according to ecosystem dynamics. In flood and coastal plains, these dynamics are mainly represented by flood pulses and hydroregime, respectively. The objective of this study was to investigate the importance of abiotic and biotic factors for the ecosystem processes represented by zooplankton secondary production (SP), biomass (ZB), and resource use efficiency (RUE) in lentic waterbodies subjected to different hydrological regimes. We hypothesised that abiotic factors would more strongly determine the ecosystem processes in temporary waterbodies and floodplain lakes, given their greater susceptibility to environmental changes. Biotic factors would be more relevant in coastal lagoons due to their greater temporal stability. Sampling was undertaken quarterly over 1 year in eight coastal lagoons, 10 temporary ponds and five floodplain lakes. The environments were characterised in relation to limnological variables, and zooplankton functional divergence, functional dispersion (FDis), functional evenness, functional richness, and taxonomic richness were measured. Analysis of variance (ANOVA) was used to verify seasonal changes in SP, ZB, RUE, functional diversity, richness, and abiotic factors. Linear mixed models were used to determine which abiotic and biotic factors were the most important for ZB, SP, and RUE. In the coastal lagoons, RUE differed over time. In the temporary ponds and floodplain lakes, no seasonal significant differences were observed for any of the zooplankton production variables. The linear mixed model analyses showed that models composed mainly of biotic factors were better fitted to the production variables. For coastal lagoons, phytoplankton density affected ZB, SP, and RUE increasing them by 9.9 mg DW/m3, 12.4 mg DW/m3, and 1.23, respectively. For temporary ponds, FDis lowered ZB by 6.9 mg DW/m3 and taxonomic richness increased SP and RUE by 14.2 mg DW/m3 and 1.17, respectively. For floodplain lakes, FDis lowered ZB it by 9.9 mg DW/m3 and functional divergence lowered RUE by 0.81. The present study demonstrates that biotic factors are the main determinants of ecosystem processes in neotropical lentic waterbodies, irrespective of their annual hydrological regimes. Complementarity effects and high functional diversity are more important in more stable environments, whereas redundancy and low functional diversity prevail in environments subject to more frequent environmental changes. Biotic factors play a major role in ensuring the functioning of aquatic ecosystems and indicate the important role of biodiversity in enabling ecosystem states to be maintained after disturbances and to prevent changes in ecosystem processes.

Additional empirical evidence on the intrinsic trend to stationarity in the long run and the nested relationship between abiotic, biotic and anthropogenic factors starting from the organic biophysics of ecosystems (OBEC)

Disease dynamics are governed by variation of individuals, species, and environmental conditions across space and time. In some cases, an alternate reservoir host amplifies pathogen loads and drives disease transmission to less competent hosts in a process called pathogen spillover. Spillover is frequently associated with multi-host disease systems where a single species is more tolerant of infection and more competent in pathogen transmission compared to other hosts. Pathogen spillover must be driven by biotic factors, including host and community characteristics, yet biotic factors interact with the abiotic environment (e.g., temperature) to create disease. Despite its fundamental role in disease dynamics, the influence of the abiotic environment on pathogen spillover has seldom been examined. Improving our understanding of disease processes such as pathogen spillover hinges on disentangling the effects of interrelated biotic and abiotic factors over space and time. We applied 10yr of fine-scale microclimate, disease, and tree community data in a path analysis to investigate the relative influence of biotic and abiotic factors on pathogen spillover for the emerging infectious forest disease sudden oak death (SOD). Disease transmission in SOD is primarily driven by the reservoir host California bay laurel, which supports high foliar pathogen loads that spillover onto neighboring oak trees and create lethal canker infections. The foliar pathogen load and susceptibility of oaks is expected to be sensitive to forest microclimate conditions. We found that biotic factors of pathogen load and tree diversity had relatively stronger effects on pathogen spillover compared to abiotic microclimate factors, with pathogen load increasing oak infection and tree diversity reducing oak infection. Abiotic factors still had significant effects, with greater heat exposure during summer months reducing pathogen loads and optimal pathogen conditions during the wet season increasing oak infection. Our results offer clues to possible disease dynamics under future climate change where hotter and drier or warmer and wetter conditions could have opposing effects on pathogen spillover in the SOD system. Disentangling direct and indirect effects of biotic and abiotic factors affecting disease processes can provide key insights into disease dynamics including potential avenues for reducing disease spread and predicting future epidemics.

Contributions of biotic and abiotic factors to soil aggregation under different thinning intensities

Modelling the influence of biotic factors on species distribution patterns

Adaptation to different environments in geographically separated populations is key for allopatric speciation. Most research has focused on the effects of geographical isolation and abiotic factors, but disjunct populations frequently co-occur with different pools of species, favouring divergent adaptation and speciation. We show the importance of plant neighbourhood, compared to geographic and environmental factors, in the allopatric speciation of two closely related plants, Carex elata and Carex reuteriana. Both species share similar ecological requirements and inhabit river shores at medium to low altitudes across the Iberian Peninsula. We employed a multidisciplinary approach integrating abiotic, biotic and geographical factors, and genomic data (genotyping-by-sequencing) to infer the relative role of different evolutionary drivers. Abiotic factors were assessed based on 38 bioclimatic variables, biotic factors using the community of co-occurring plant species (1536 vegetation inventories), and geographical factors with a distance matrix based on geographic coordinates. Using regularised generalised linear models, we identified the key variables explaining distribution patterns. We also examined the relationships between inter-population genetic distances, and biotic, abiotic and geographic factors to understand the drivers of lineage splitting, revealing varying degrees of influence. Plant neighbourhood emerged as a stronger predictor of allopatric distributions than abiotic or geographic factors, with the largest effect observed in Carex elata, which exhibited the greatest population differentiation. These findings suggest that the biotic and microenvironmental factors influencing divergent plant neighbourhoods have significantly contributed to the differentiation of these taxa, providing new insights into the evolutionary processes shaping the origin and distribution of species.

Our understanding of the long-lasting effects of human land use on soil fungal communities in tropical forests is limited. Yet, over 70% of all remaining tropical forests are growing in former agricultural or logged areas. We investigated the relationship among land use history, biotic and abiotic factors, and soil fungal community composition and diversity in a second-growth tropical forest in Puerto Rico. We coupled high-throughput DNA sequencing with tree community and environmental data to determine whether land use history had an effect on soil fungal community descriptors. We also investigated the biotic and abiotic factors that underlie such differences and asked whether the relative importance of biotic (tree diversity, basal tree area, and litterfall biomass) and abiotic (soil type, pH, iron, and total carbon, water flow, and canopy openness) factors in structuring soil fungal communities differed according to land use history. We demonstrated long-lasting effects of land use history on soil fungal communities. At our research site, most of the explained variation in soil fungal composition (R2 =18.6%), richness (R2 =11.4%), and evenness (R2 =10%) was associated with edaphic factors. Areas previously subject to both logging and farming had a soil fungal community with lower beta diversity and greater evenness of fungal operational taxonomic units (OTUs) than areas subject to light logging. Yet, fungal richness was similar between the two areas of historical land use. Together, these results suggest that fungal communities in disturbed areas are more homogeneous and diverse than in areas subject to light logging. Edaphic factors were the most strongly correlated with soil fungal composition, especially in areas subject to light logging, where soils are more heterogenous. High functional tree diversity in areas subject to both logging and farming led to stronger correlations between biotic factors and fungal composition than in areas subject to light logging. In contrast, fungal richness and evenness were more strongly correlated with biotic factors in areas of light logging, suggesting that these metrics might reflect long-term associations in old-growth forests. The large amount of unexplained variance in fungal composition suggests that these communities are structured by both stochastic and niche assemblage processes.

White oak mortality in the eastern United States presents significant challenges for forest conservation efforts. Understanding the spatial patterns and underlying processes, impacts of biotic and abiotic factors, and climate change is crucial for effective management of white oak forest in the eastern United States. White oak mortality (WOM) can have clustered patterns at local scale due to stand development and soil conditions. While there might be a random WOM pattern due to drought events and uniform pattern from soil conditions and moisture availability at broad scale. White oak mortality is also greatly impacted by biotic factors such as basal area, stand density, and abiotic factors such as spring precipitation and winter temperature. Chapter I laid out the overall objectives and justifications for chapter II, III, and IV. It stated ecological importance of white oaks in the eastern US and its conservation for maintaining regional biodiversity. This chapter addressed spatial pattern distribution, role of biotic and abiotic factors, and climate change impacts on WOM rate. In this chapter, there was a specific description on data processing, result analyses, major findings, and summaries from chapters. Chapter II investigated the spatial patterns in southern, central, and northern region of WOM rate across the eastern US. I compiled multicycle Forest Inventory and Analysis data from 1998 to 2019 to capture WOM rate. Results of this chapter found clustered pattern mostly at local scale across the southern and northern regions of WOM rate. However, the central region indicated random patterns at mid scales and uniform pattern at a broad scale across all regions. The observed various spatial pattern of WOM rate explored the underlying factors associated WOM. This study provides an important basis for depicting the broad, general pattern of WOM and understanding the possible factors impacting WOM rate at varying scales. Chapter III identified the most important variables affecting WOM rate by integrating biotic, abiotic factor and forest inventory data. I ranked biotic and abiotic variables in response to WOM rate by integrating forest inventory data and Classification and Regression Tree. I also identified that basal area was first in the hierarchical ranking denoting major impacting variable to WOM rate. I demonstrated that biotic factors were significantly more important than abiotic factors, in which basal area was very important followed by stand density, summer temperature, summer and spring precipitation, and elevation. This research contributes valuable insights into the biotic and abiotic factors impacting white oak forest and highlight the importance of holistic approach in addressing complex environmental challenges. Chapter IV investigated the situation of WOM rate under climate change in the intermediate scenario i.e., SSP2-4.5. I projected WOM rate to the year 2025 to 2099 with break off at three averaged time intervals i.e., early (2025-2049), mid (2050-2074), and late (2075-2099). I analyzed five different climate models by integrating remote sensing and Coupled Model Intercomparison Project Phase 6 climate variables. I focused on four seasonal variables mainly summer and winter temperature and spring and summer precipitation. Results of this chapter showed that WOM rate will increase mostly in the southern region of our study area whereas northern region mostly witness a decrease in WOM rate. I also identified that there will be a increase in few areas as well as very less areas for decrease in WOM rate in the central region of our study area. Rising temperature and shifting precipitation pattern will increase WOM rate while ongoing management efforts will decrease WOM rate at northern region. This research points out important insights into highly impacted as well as less impacting areas of WOM rates under changing climate. Chapter V is the overall conclusions that summarizes major findings. Chapter II identified mainly clustered pattern at local scale associated with stand-level competition and soil characteristics. Random pattern at local and broad scale was associated with stochastic events such as droughts and other climate stressors. The uniform pattern at broad scale was associated with land use practices and forest management efforts. Chapter III pointed out that basal area was the main biotic variable impacting white oaks due to massive competition of resources during natural thinning. Likewise, climate, terrain, and soil characteristics also found important in impacting white oaks in the second and third tier, respectively. Chapter IV demonstrated that WOM rate will increase mainly in the southern region due to rising temperature and shifting precipitation. The central and northern region will experience decrease as well as moderate increase due to possible forest management efforts. However, majority areas will also remain unchanged for WOM rate due to ongoing management efforts.

AimThe factors that set species range limits underlie many patterns in ecology, evolution, biogeography and conservation. These factors have been the subject of several reviews, but there has been no systematic review of the causes of warm‐edge limits (low elevations and latitudes). Understanding these causes is urgent, given that the factors that set these limits might also drive extinction at warm edges as global climate changes. Many authors have suggested that warm‐edge limits are set by biotic factors (particularly competition) whereas others have stressed abiotic factors (particularly temperature). We synthesize the known causes of species' warm‐edge range limits, with emphasis on the underlying mechanisms (proximate causes).LocationGlobal.MethodsWe systematically searched the literature for studies testing the causes of warm‐edge range limits.ResultsWe found 125 studies that address the causes of warm‐edge limits, from a search including > 4000 studies. Among the species in these studies, abiotic factors are supported more often than biotic factors in setting species range limits at warm edges, in contrast to the widely held view that biotic factors are more important. Studies that test both types of factors support abiotic factors significantly more frequently. In addition, only 23 studies (61 species) identified proximate causes of these limits, and these overwhelmingly support physiological tolerances to abiotic factors (primarily temperature). Only eight species with identified proximate causes were tested for both biotic and abiotic factors, but the majority support abiotic factors.Main conclusionsAlthough it is often assumed that warm‐edge limits are set by biotic factors, our review shows that abiotic factors are supported more often among the species in these 125 studies. However, few studies both identify proximate causes and test alternative mechanisms, or examine the interaction between biotic and abiotic factors. Filling these gaps should be a high priority as warm‐edge populations are increasingly driven to extinction by climate change.

Comparing ensemble and cascaded neural networks that combine biotic and abiotic variables to predict insect species distribution

Effects of biotic and abiotic factors on soil organic matter mineralization: Experiments and structural modeling analysis

Both biotic and abiotic factors are expected to drive species diversification, yet demonstrating their synergistic effects within a single framework is challenging and has rarely been studied. The recent and rapid radiation of the genus Aspidistra (cast-iron plant) provides an ideal system for examining these processes. Here, we generated restriction site-associated DNA sequencing data for 123 Aspidistra taxa and reconstructed well-resolved phylogenies using both concatenation- and coalescent-based approaches. Using a comprehensive suite of diversification models, we quantified the contributions of multiple biotic and abiotic factors and applied phylogenetic path analysis to detect their synergistic effects. Our phylogenetic analyses recovered two main clades that differ in stem habits. We found that the diversification of Aspidistra has been driven by both abiotic factors (paleotemperature and the East Asian monsoon) and biotic factors (interspecific competition and pollination mutualism). Notably, these drivers operated both independently and synergistically to facilitate the rapid radiation of Aspidistra. Beyond providing a robust phylogeny useful for classifying Aspidistra, we present a statistical framework for better understanding the macroevolutionary processes underlying rapid plant radiations. Our findings underscore the critical importance of integrating multiple biotic and abiotic drivers into a unified analytical framework to comprehensively understand diversification history.