Structural Traits Research Articles

The regeneration of natural stibnite with introduced oxide-based catalyst towards enhanced Li-storage properties

Owing to its excellent theoretical specific capacity, Sb2S3 captures widespread attention in the energy-storage field. However, it still suffers from volume expansion and sluggish electrochemical kinetics. Meanwhile, considering serious pollution and complex chemical preparation processes, stibnite is regarded as “first-hand” materials, displaying enormous energy-storage application potential; however, it is still limited by low-purity and high crystallinity. Herein, stibnite is purified and regenerated through physical chemical and vacuum gas-phase melting strategy to form high-properties stibnite-based electrode materials. Assisted by the introduction of lithium nitrate as an active medium, abundant sites and effective structural traits are formed, effectively promoting the reversibility of electrochemical kinetic processes. Utilized as lithium-ion battery anodes, the as optimized samples have a capacity of approximately 656.8 mAh g−1 with a capacity retention rate of 89.9 % at 0.5 A g−1. Even at 5.0 A g−1, the capacity of 483.3 mAh g−1 could be remained after 100 cycles. Supported by a detailed kinetic analysis, the enhancement of the surface-controlling behavior and the reduction of capacitive resistance are confirmed. Herein, the as-regenerated phase and the introduced oxide-based catalyst are beneficial to alleviate polysulfide shuttling and volume expansion, further accelerating ion/electron transfer behaviors. This work is expected to shed light on strategies to design promising mineral-based anodes for lithium-ion batteries.

Face-degree-based topological descriptors of germanium phosphide

In graph theory, topological indices are numerical metrics that give information about a graph’s structural traits. The face index is one such topological index that describes planar networks. Since the discovery of graphene, the genealogy of two-dimensional 2D crystals has expanded and currently contains a large variety that has all logical electrical properties required for nano electronics. Nanotechnology benefits from the use of materials that resemble Dirac, such as silicon, graphite, semiconductors, and germanene, as well as TMDC (phosporene), a transition metal dichalcogenide. In contrast with standard topological descriptors, which are numerical values utilised to characterise molecular structures, the face index presents a potentially more comprehensive method for obtaining structural details. In investigations involving quantitative structure-property relationships (QSPR), this may result in more precise predictions. We calculated the recently created face index of Germanium Phosphide (GeP) and its many shapes, including triangle, rhombus, hourglass, and concentric circles.

Silicon weakens the outer apoplastic barrier in roots of rice and delays its formation, resulting in increased Na+ and Cl− fluxes to the shoot

In rice, silicon can mitigate abiotic and biotic stresses. We therefore investigated the effect of Si on key root traits related to soil flooding and salinity tolerance with emphasis on the outer apoplastic barrier and cortical aerenchyma. We tested the hypothesis that Si application alters the phenotypic response of these root traits by growing rice in nutrient solutions without or with Si, designed to mimic drained or flooded soils. We measured the barrier strength through resistance to O2 and water of the outer parts of adventitious roots along with cortical aerenchyma and other root structural traits. We found that Si delayed the barrier formation and caused lower amounts of inducible cortical aerenchyma. The delay in barrier formation resulted in higher xylem loading of Na+ and Cl-, i.e., the sap flux of both ions was significantly higher for plants with access to Si. The increased ion fluxes correlated with lower lignin and suberin deposition in the outer part of the root. Consequently, we do not recommend using Si application to alleviate combined stress of salinity and soil flooding in rice, since the barrier was more permeable to O2, and the aerenchyma formation was less pronounced in roots with Si.

Exploring the heart-brain and brain-heart axes: Insights from a bidirectional Mendelian randomization study on brain cortical structure and cardiovascular disease

IntroductionThe bidirectional relationship between the brain cortex and cardiovascular diseases (CVDs) remains inadequately explored. MethodsThis study used bidirectional Mendelian randomization (MR) analysis to explore the interactions between nine phenotypes associated with hypertension, heart failure, atrial fibrillation (AF), and coronary heart disease (CHD), and brain cortex measurements. These measurements included total surface area (SA), average thickness (TH), and the SA and TH of 34 regions defined by the Desikan-Killiany atlas. The nine traits were obtained from sources such as the UK Biobank and FinnGen, etc., while MRI-derived traits of cortical structure were sourced from the ENIGMA Consortium. The primary estimate was obtained using the inverse-variance weighted approach. A false discovery rate adjustment was applied to the p-values (resulting in q-values) in the analyses of regional cortical structures. ResultsA total of 1,260 two-sample MR analyses were conducted. Existing CHD demonstrated an influence on the SA of the banks of the superior temporal sulcus (bankssts) (q=0.018) and the superior frontal lobe (q=0.018), while hypertension was associated with changes in the TH of the lateral occipital region (q=0.02). Regarding the effects of the brain cortex on CVD incidence, total SA was significantly associated with the risk of CHD. Additionally, 16 and 3 regions exhibited significant effects on blood pressure and AF risk, respectively (q<0.05). These regions were primarily located in the frontal, temporal, and cingulate areas, which are associated with cognitive function and mood regulation. ConclusionThe detection of cortical changes through MRI could aid in screening for potential neuropsychiatric disorders in individuals with established CVD. Moreover, abnormalities in cortical structure may predict future CVD risk, offering new insights for prevention and treatment strategies.

Particle shape analysis of calcareous sand based on digital images

Particle geometric is a key parameter that defines the eometric attributes of calcareous sand particles and is intricately related to their mechanical traits, such as compression and shear. The scanning electron microscopy and digital imaging were applied to capture the microscopic properties and geometric projections of calcareous sand. The qualitative analysis, conventional statistical methods and fractal theory were employed to describe the geometric morphology of sand particles. Additionally, we analyzed the structural and physical traits of calcareous sand based on its unique biological genesis. We developed a hypothetical structural-physical model for calcareous sand. Our findings revealed the interwoven reticulation on the surface of calcareous gravel particles, along with an uneven distribution of pores on the external surface. As the particle size increased, the global profile factor decreased and the angularity increased. The critical threshold for the variations in flatness, surface roughness, and circularity was observed at a particle size of 5 mm, with the particle size having a relatively minor effect on these characteristics for particles smaller than 5 mm. The shape of the calcareous sand particles exhibited fractal characteristics, with fractal dimension serving as a measure of surface smoothness, particle breakage, and strength. These experimental results could significantly enhance our understanding of the mechanical behavior of calcareous sand.

High-throughput digital imaging and detection of morpho-physiological traits in tomato plants under drought

Abstract Advances in informatics, robotics, and imaging techniques make it possible to use state-of-the-art digital reconstruction technologies for high-throughput plant phenotyping (HTPP) affected by stress factors, as well as for the ontology of their structural and functional traits. Digital imaging of structural and functional features of the aboveground part of plants is non-destructive and plants can be monitored throughout their entire life cycle. In the experiment with tomato plants (Solanum lycopersicum L.; cv. Gruzanski zlatni) grown in controlled environmental conditions and affected by gradual soil dehydration, we evaluated phenotypic traits and phenotypic plasticity by the PlantScreenTM platform using digital imaging of plant optical signals. In this study, 25 different morpho-physiological traits of the plant were evaluated during the precise control and monitoring of the water content in the soil. Different levels of plant water supply induced statistically significant differences in the formation of individual phenotypic traits. Several plant traits have been identified that are characterized by low variability in both well-hydrated and water-stressed conditions, as well as traits with high phenotypic plasticity. Geometric traits (especially Isotop, Round-2top, and Compside) showed a relatively low level of drought-induced phenotypic plasticity. However, functional and chemometric characteristics (ΔF/F′m, Rfd, Water-1, and ARI-1) showed the potential to exhibit rapid plasticity in water-stressed conditions. Our results confirmed that a high-throughput phenotyping methodology coupled with advanced statistical analysis tools can be successfully applied to characterize crop stress responses and identify traits associated with crop stress tolerance.

Unfolding the leaf economics spectrum for wheat: Trait analysis and genomic associations across cultivars

The leaf economics spectrum (LES) is an ecophysiological concept that describes the trade-offs between leaf structural and physiological traits. It has been extensively studied across various scales. However, the coordination hypothesis has rarely been tested at the intraspecific scale, especially in crops, for understanding yield increases or predicting evolutionary trajectories. Here, we first tested the relationships among leaf traits and examined the genetic coordination among 209 wheat genotypes. Compared to non-crop grass species, wheat is a fast-growing species, and tends to have a higher value of photosynthetic rate, leaf nitrogen concentration and leaf respiration rate at a given leaf mass per area, although it does align with the predicted direction of the “fast-slow” spectrum. We conducted a principal component analysis (PCA) to compare different traits within wheat. The first axis from PCA (ranging from slow to fast of plant economic investment) is significantly positively associated with the agronomic traits, especially grain yield (R2=0.11, P<0.001). Partially independent changes in leaf nitrogen content and leaf mass per area may allow crops to maximize photosynthetic rates without sacrificing leaf lifespan. The results reveal that some loci are simultaneously associated with different traits, which may be the genetic basis for the formation of trait-trait relationships. The current study deepens the understanding of LES traits in wheat at the intraspecific and genetic levels, supporting the trait-based adaptation strategies to improve wheat productivity and resource-use efficiency.

Simulation of early season herbivory via mechanical damage affects flower production in pumpkin (Cucurbita pepo ssp. pepo).

Damage from insect herbivores can elicit a wide range of plant responses, including reduced or compensatory growth, altered volatile profiles, or increased production of defence compounds. Specifically, herbivory can alter floral development as plants reallocate resources towards defence and regrowth functions. For pollinator-dependent species, floral quantity and quality are critical for attracting floral visitors; thus, herbivore-induced developmental effects that alter either floral abundance or attractiveness may have critical implications for plant reproductive success. Based on past work on resource trade-offs, we hypothesize that herbivore damage-induced effects are stronger in structural floral traits that require significant resource investment (e.g., flower quantity), as plants reallocate resources towards defence and regrowth, and weaker in secondary floral traits that require less structural investment (e.g., nectar rewards). In this study, we simulated early-season herbivore mechanical damage in the domesticated jack-o-lantern pumpkin Cucurbita pepo ssp. pepo and measured a diverse suite of floral traits over a 60-day greenhouse experiment. We found that mechanical damage delayed the onset of male anthesis and reduced the total quantity of flowers produced. Additionally, permutational multivariate analysis of variance (PERMANOVA) indicated that mechanical damage significantly impacts overall floral volatile profile, though not output of sesquiterpenoids, a class of compounds known to recruit specialized cucumber beetle herbivores and squash bee pollinators. In summary, we show that C. pepo spp. pepo reduces investment in male flower production following mechanical damage, and that floral volatiles do exhibit shifts in production, indicative of damage-induced trait plasticity. Such reductions in male flower production could reduce the relative attractiveness of damaged plants to foraging pollinators in this globally relevant cultivated species.

Effects of drought and moisture stress on the growth and ecophysiological traits of Schima superba seedlings.

Changes in rainfall patterns are important environmental factors affecting plant growth, especially when larger precipitation events and prolonged drought periods occur in subtropical regions. There are many studies on how drought reduces plant biomass through drought-sensitive functional traits, but how excess water affects plant growth and ecophysiology is still poorly understood. Therefore, a greenhouse experiment was conducted on Schima superba (Theaceae), a dominant tree species in subtropical forests and commonly used in forestry, in a closed chamber under control (25% soil water content (SWC) as in local forests), drought stress (D, 15% SWC) and moisture stress (W, 35% SWC). Plant growth and ecophysiological traits related to morphology, leaf gas exchange, water potential and structural traits were measured. Compared to control, S. suberba under dry conditions significantly decreased its aboveground biomass, photosynthetic rate (A), leaf water potential and nitrogen use efficiency, but increased intrinsic water use efficiency, root to shoot ratio and specific root length. S. superba under wet conditions also significantly decreased its total biomass, aboveground biomass and specific root length, while W had no effect on A and leaf water potential. Our results indicate that S. superba shows a decrease in carbon gain under drought stress, but less response under wet conditions. This emphasizes the need to consider the strength and frequency of rainfall pattern changes in future studies because rainfall may either alleviate or intensify the effects of drought stress depending on the moisture level, thus suitable water conditions is important for better management of this tree species in subtropical China.

Leaf Trait Variations and Ecological Adaptation Mechanisms of Populus euphratica at Different Developmental Stages and Canopy Heights

The ability of plants to alter specific combinations of leaf traits during development and in response to abiotic stress is crucial for their success and survival. While there are numerous studies on the variation of leaf traits within the canopies of Populus species, the application of network analysis to understand the variation and combinations of these traits across different growth stages is rare. The leaves of Populus euphratica, a dominant species in arid regions, exhibit notable morphological variations at different developmental stages and canopy heights in response to water scarcity and climate change. In this study, 34 leaf traits (morphological, chemical, photosynthetic, and hydraulic) and their roles in drought adaptation were investigated in 60 Populus euphratica plants at five developmental stages and five canopy heights using leaf trait network (LTN) analysis. The aim was to analyze adaptive strategies to arid environments at different developmental stages and canopy heights through the interdependence of leaf traits. The results showed that the internal coordination capacity of leaf trait networks decreased and then increased with each developmental stage, while the functional modules of leaf trait networks were loosely connected and aggregated with the increase in tree diameter at breast height. With increasing canopy height, the coordination linkage’s ability between leaf traits showed an increasing then decreasing trend, and the traits of the leaves in the canopy at 6 m were more closely connected, less modular, and simpler in topology compared with those in the other layers. Leaves form functional modules by coordinating specific traits that promote growth and resist drought. Leaf photosynthesis, water transport, and nutrient traits were central to different developmental stages, whereas leaf morphology, nutrient metabolism, and drought-resistance-related traits were central to the canopy height. Leaf morphology and osmoregulatory traits play key roles in leaf trait network regulation, including leaf length and width, leaf shape index, soluble sugars, and soluble proteins, which are important “intermediary traits” in the Populus euphratica leaf network. Further analysis revealed that structural traits were important at different developmental stages and canopy heights. When resources are limited, the leaf preferentially maintains a stable connection between structural traits to enhance photosynthesis, and these traits and their combinations might confer drought resistance. During the rapid development stage, the connection between chemical traits becomes important, and the leaf grows by rapidly accumulating nutrients. In summary, this study provides new perspectives and insights into the drought adaptation strategies of P. euphratica at different developmental stages and canopy heights by analyzing leaf trait networks.

Linkage between leaf anatomical structure and key leaf economic traits across co-existing species in temperate forests

Linkage between leaf anatomical structure and key leaf economic traits across co-existing species in temperate forests

Modulating Heavy Atom Effect in Germylene for Persistent Room Temperature Phosphorescence.

It is worth but still challenging to develop the low-valent main group compounds with persistent room temperature phosphorescence (pRTP). Herein, we presented germylene-based persistent phosphors by introduction of low-valent Ge center into chromophore. A novel phosphors CzGe and its series of derivatives, namely CzGeS, CzGeSe, CzGeAu, and CzGeCu, were synthesized. Experiments and theoretical calculations reveal that the pRTP behavior were "turn on" due to the heavy atom effect of germylene. More importantly, the low-valent of oxidation state and structural traits propelled GeCz had a balance between the intersystem crossing and the shortening of lifetime caused by the heavy atoms, resulting the ultralong lifetime of 309 ms and phosphorescent quantum efficiency of 15.84 %, which is remarkable among heavy main group phosphors. This research provides valuable insights to the design of heavy atoms in phosphors and expand the applications of germylene chemistry.

Agricultural Landscapes: A Pattern-Process-Design Approach to Enhance Their Ecological Quality and Ecosystem Services through Agroforestry

Agricultural landscapes are currently suffering and generating severe ecological issues. This is especially true in intensively managed alluvial contexts, where biodiversity is declining and ecosystem services (ES) delivery capacity is being depleted. The aim of our study is to set up and test a synthetic analytical methodology that allows us to: understand current agricultural landscape ecological quality drivers (structural and functional traits); identify context-specific strategies to correct current negative trends (landscape ecology design approach); and assess the changes in the landscape ecological behavior provided by design scenarios. The applied methodology is low-cost and low-time-demanding and is based on multi-scale landscape ecology and land-use-based ES assessment; it implements a pattern-process-design approach. Analyses are applied to four northern Italian alluvial agricultural landscape systems. We specifically address landscape biodiversity support functions (landscape ecology indicators) and landscape multifunctionality (ES spatial assessment). We test the agroforestry approach (landscape feature insertions and crop diversification) as a key strategy to enhance ecological quality and ES, and we account for its contributions to context-specific design scenarios. This analytical toolkit might serve for future applications on similar case studies.

Exploring the genetic architecture of brain structure and ADHD using polygenic neuroimaging-derived scores.

Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of neuropsychiatric disorders and highlighted their complexity. Careful consideration of the polygenicity and complex genetic architecture could aid in the understanding of the underlying brain mechanisms. We introduce an innovative approach to polygenic scoring, utilizing imaging-derived phenotypes (IDPs) to predict a clinical phenotype. We leveraged IDP GWAS data from the UK Biobank, to create polygenic imaging-derived scores (PIDSs). As a proof-of-concept, we assessed genetic variations in brain structure between individuals with ADHD and unaffected controls across three NeuroIMAGE waves (n = 954). Out of the 94 PIDS, 72 exhibited significant associations with their corresponding IDPs in an independent sample. Notably, several global measures, including cerebellum white matter, cerebellum cortex, and cerebral white matter, displayed substantial variance explained for their respective IDPs, ranging from 3% to 5.7%. Conversely, the associations between each IDP and the clinical ADHD phenotype were relatively weak. These findings highlight the growing power of GWAS in structural neuroimaging traits, enabling the construction of polygenic scores that accurately reflect the underlying polygenic architecture. However, to establish robust connections between PIDS and behavioral or clinical traits such as ADHD, larger samples are needed. Our novel approach to polygenic risk scoring offers a valuable tool for researchers in the field of psychiatric genetics.

Leaf functional traits of Daphniphyllum macropodum across different altitudes in Mao’er Mountain in Southern China

Investigating functional traits among mountain species with differing altitude requirements is integral to effective conservation practices. Our study aims to investigate the structural and chemical characteristics of Daphniphyllum macropodum leaves at three altitudes (1100 m, 1300 m, and 1500 m) across southern China to provide insight into changes in leaf functional traits (LFT) as well as plant adaptations in response to changing environmental conditions. Leaf structural characteristics include leaf thickness (LT), leaf area (LA), specific leaf area (SLA), and leaf tissue density (LD), respectively, while chemical properties include carbon-nitrogen-phosphorus (C:N:P) contents and ratios, such as C/N, C/P, and N/P. Our findings demonstrated the significant effect of altitude on both structural (LT, SLA, LD) and chemical aspects (N, C/N, N/P) of LFT. In particular, leaves at 1100 and 1300 m differed greatly, with 1300 m having lower SLA values than 1100 m. Observable trends included an initial increase followed by a decline as the altitude rose. Notable among them were the LT, LD, N, and N/P values at both locations. Traits at 1300 m were significantly higher than at 1100 m; SLA and C/N values displayed an inverse trend, with their lowest values occurring at 1300 m. Furthermore, this research demonstrated various degrees of variation among LFT, with structural traits exhibiting greater fluctuation than chemical traits. Robust correlations were observed among certain traits, such as LT, LD, and SLA. Furthermore, the interdependency relationships between N and C/N, as well as P and C/P, demonstrated interconnectedness. Redundancy analysis indicated that soil factors, specifically P content, exerted the strongest impact on LFT. At 1100 m, D. macropodum employed acquisition strategies; however, at 1300 m, conservation strategies emerged, showing a shift from acquisition strategies at lower altitudes to conservative strategies at higher ones.

Polyploidy and the evolution of phenotypic integration: Network analysis reveals relationships among anatomy, morphology, and physiology.

Most traits are polygenic and most genes are pleiotropic, resulting in complex, integrated phenotypes. Polyploidy presents an excellent opportunity to explore the evolution of phenotypic integration as entire genomes are duplicated, allowing for new associations among traits and potentially leading to enhanced or reduced phenotypic integration. Despite the multivariate nature of phenotypic evolution, studies often rely on simplistic bivariate correlations that cannot accurately represent complex phenotypes or data reduction techniques that can obscure specific trait relationships. We apply network modeling, a common gene co-expression analysis, to the study of phenotypic integration to identify multivariate patterns of phenotypic evolution, including anatomy and morphology (structural) and physiology (functional) traits in response to whole genome duplication in the genus Brassica. We identify four key structural traits that are overrepresented in the evolution of phenotypic integration. Seeding networks with key traits allowed us to identify structure-function relationships not apparent from bivariate analyses. In general, allopolyploids exhibited larger, more robust networks indicative of increased phenotypic integration compared to diploids. Phenotypic network analysis may provide important insights into the effects of selection on non-target traits, even when they lack direct correlations with the target traits. Network analysis may allow for more nuanced predictions of both natural and artificial selection.

Structure Characteristics, Variation of Main Quantitative Traits, and Probability Grading of Chinese Olive (Canarium album) Seeds

In order to comprehensively describe and evaluate Chinese olive seeds, this study examined 33 varieties (strains) of Chinese olive seeds to address the limitations of previous research on quantitative trait variation and grading among Chinese olive seed varieties (strains). The research specifically focused on evaluating the morphological characteristics, seed locule structure, embryo composition, and phenotypic quantitative traits of Chinese olive seeds. The results indicated that Chinese olive seeds consisted of a core, seed coat, and embryo. Typically, the core contained two to four locules, with each locule containing zero to one embryos. Eight distinct structural variations were identified, with the number of locules per seed ranging from two to four and the number of embryos ranging from one to four. The most common structural types were ‘3-locule 1-embryo’ and ‘3-locule 2-embryo’, each occurring in 100% of the varieties (strains) studied. These two structural types also had a high average proportion within each variety (line), accounting for 50.17% and 42.06%, respectively. The average dimensions of a seed were 31.20 mm in length and 10.89 mm in width, with a shape index of 2.89 and weighing 1.55 g. These quantitative traits displayed significant variation, with the coefficient of variation being highest for single seed weight (19.35%) and lowest for seed length (9.39%). Normality tests revealed that seed width, seed length, and single seed weight followed a normal distribution. These traits were categorized into five levels based on specific points, with probabilities of occurrence approximately 10%, 20%, 40%, 20%, and 10%, respectively. The findings of this study are crucial for understanding and utilizing Chinese olive seed traits and provide valuable insights for the establishment of seed trait standards and data normalization.

Assessing Structural Traits in Triticum aestivum and Zea mays for C3 and C4 Photosynthetic Differentiation Using Free-hand and Semi-thin Sections.

The enhanced efficiency of C4 photosynthesis, compared to the C3 mechanism, arises from its ability to concentrate CO2 in bundle sheath cells. The effectiveness of C4 photosynthesis and intrinsic water use efficiency are directly linked to the share of mesophyll and bundle leaf cells,size and density of bundle sheaths, and size, density, and cell wall thickness of bundle sheath cells. Rapid microscopical analysis of these traits can be performed on free-hand and semi-thin sections using conventional light microscopy, providing valuable information about photosynthetic efficiency in C4 crops by means of identifying and examining specific cell types. Additionally, errors in freehand and semi-thin section preparation that affect anatomical measurements and cell type diagnoses are shown, as well as how to avoid these errors. This microscopical approach offers an efficient means of gathering insights into photosynthetic acclimation to environmental variation and aids in the rapid screening of crops for future climates.

Genomic variation of 363 diverse tea accessions unveils the genetic diversity, domestication, and structural variations associated with tea adaptation.

Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full-length protein-encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large-scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits.

The role of agroforestry in solving the agricultural landscapes vulnerabilities in the Po Plain district

AbstractThe current trend of biodiversity deterioration in rural systems is a complex issue that operates across multiple spatial scales. Agroforestry practices have the potential to positively contribute towards addressing these trends by shaping the structure of agricultural landscapes and their underlying ecological functions. This study aims to test a multi-scale analytical approach to understand and account for these processes. Specifically, the study seeks to assess the contributions that agroforestry practices at the farm scale can make towards supporting biodiversity, in response to the wider-scale landscape eco-mosaic structural and functional challenges and requirements (both at the local and extra-local landscape systems). To achieve this, a series of landscape ecology analyses are conducted on an agroforestry-based rice farm located in the western Po Plain region of Northern Italy. These analyses examine various landscape structural traits (such as matrix composition, patch size, shape complexity, and diversity indices) and functional traits (including connectivity and bionomic indices), with different levels of detail for each scale of analysis. This allows for the evaluation of the current ecological status of both the extra-local and local scale landscape systems (including drivers of vulnerability and resilience) and the assessment of the farm's current contributions to biodiversity support. Based on these findings, strategic agroforestry interventions are identified at the farm scale to enhance its capacity to address the wider-scale ecological gaps. Two design scenarios are assessed, wherein functional ecological traits such as landscape diversity, connectivity, and ecological stability are improved. The results confirm the role of farm scale agroforestry management as a buffering tool, demonstrating how it contributes to the restoration of broader-scale landscape vulnerabilities. The applied approach provides cost-effective assessments of biodiversity-related ecological processes, with the accuracy of the findings dependent on the comprehensive multi-scale analysis conducted.