Spatial Distribution Of Plants Research Articles

Across a phylogeographic break in the Qinling Mountains-Huaihe River Line: Quaternary evolutionary history of a medicinal and edible homologous plant (Allium macrostemon) in China

Biogeographic barriers to gene flow are central to studies of plant phylogeography. There are many physical and geographic barriers in China, but few studies have used molecular ecological evidence to investigate the natural geographic isolation barrier of the Qinling Mountains-Huaihe River Line (QHL). Allium macrostemon is a precious Chinese perennial herb belonging to the Amaryllidaceae family. It is used as a food and medicine, with a variety of health and healing properties. Five SSR markers, three chloroplast DNA (cpDNA) markers (psbA-trnH, rps16 and trnL-F), one nuclear ribosomal DNA (nrDNA) marker (ITS), and simplified genome GBS sequencing were used to analyse the genetic diversity and structure of A. macrostemon. Combining SSR, cpDNA, nrDNA ITS data and GBS analysis results, we divided A. macrostemon populations into northern and southern groups, with the southern group further divided into southwestern and central-southeastern groups. Niche simulation results reveal that the distribution area of A. macrostemon will reach its maximum in the future. These data indicate that the regional separation of A. macrostemon has been maintained by the combined influence of a geographical barrier and Quaternary climate, and that the back-and-forth fluctuations of QHL and Quaternary climate have played an important role in this process. QHL acts as a north-south dividing line in phylogeography and population genetic structure, promoting physical geographic isolation. This study provides a theoretical basis for the conservation, development, and utilization of A. macrostemon resources. It further provides a reference for understanding the systematic geographical pattern of the large-scale spatial distribution of plants in China and enriches our understanding of Quaternary plant evolution in areas with complex terrain.

Identifying the Authenticity of Plantscapes through Classics: A Case Study of Beijing Suburbs in the Qing Dynasty

The plantscapes surrounding historical gardens hold significant value, reflecting the natural pristine state as well as demonstrating the cultural attributes of the landscape. This study aims to develop a method for identifying the characteristics of historic plantscapes and to recognize the authenticity of historic landscapes from the perspective of plant elements. Our method combines textual and geospatial data analysis to examine the plant species, their relationships and combinations, and spatial distribution. The case study focuses on the Beijing suburbs during the Qing Dynasty, as documented in A Collection of Past Events in Beijing. We identified 658 plants recorded, encompassing 44 families and 58 genera. These plants were categorized into 7 groups based on the growth type and morphological characteristics, leading to 54 plant relationship outcomes, 107 plant combination scenarios, 5 plant combination categories, and 7 representative plant combinations. Additionally, we mapped the spatial distribution of plants, forming 16 plantscape groups and depicting the spatial kernel density distribution of important plants. We also determined the characteristics of plantscapes in different directions in the suburb. Our findings advocate for respecting the historical development of the plantscape and understanding its evolution, particularly emphasizing the use of high-quality native plants and plant combinations.

Central American Red BrocketDieta de Mazama temama (Kerr 1792, Artiodactyla: Cervidae) en Parque Nacional Cañón del Río Blanco

Determining the diet of herbivores through the epidermal structures present in their excreta makes it possible to identify the plants consumed and estimate the variations at different times of the year. The objective of the study was to determine the botanical composition of the diet of the deer Central American Red Brocket (Mazama temama), in the Parque Nacional Cañón del Río Blanco (PNCRB), Veracruz, Mexico. The vegetation where the study was carried out is an evergreen tropical forest with the presence of induced vegetation. Sampling was carried out during the dry and rainy season of 2021. The plant species consumed were identified with the microhistological analysis of epidermal residues in fecal samples. The diet consisted of 18 species of plants belonging to 14 botanical families. The highest percentage of consumption was for the Solanaceae family (16.6%), followed by Arecaceae, Asteraceae, Cucurbitacea and Malvaceae (11.1% each). 66% of the plants were consumed in the dry season, and consumption increased by 34% during the rainy season, showing 100% of the plant species in the rainy season, showing 100% consumption in the rainy season.. The plants consumed were 10 herbaceous plants (55.5%), six arboreal plants (33.5%), one shrub and one grass (5.5% each); forest edge plants (BB = 44%), forest interior plants (IB = 33%) and cultured plants (CP = 23%), constituted the diet. M. temama adapted its diet to the availability and temporal and spatial distribution of plants in the habitat and based on climatic conditions (dry vs. rainy).

Mixed particle swarm optimization algorithm-based approach to optimize spatial distribution of virtual maize

Increasing crop yields is one potential way to solve the problem of food shortage and limited field resources. Optimization of crop spatial distribution is an efficient method to increase yield. However, extensive field experiments are costly and time consuming, which renders conventional optimization studies difficult if not prohibitive. In this study, a new optimization strategy was proposed, integrating a Functional-Structural Plant Model (FSPM) of maize with a workflow based on a Mixed Particle Swarm Optimization (MPSO) algorithm. The maize FSPM applies a dynamic interactive feedback method between plant morphology and plant growth dynamics on the one hand, and simultaneously between plant spatial distribution and plant growth, and furthermore can respond to different environmental factors. MPSO is a new mixed particle swarm optimization algorithm with multistage disturbance, which enhances the ability of traversing the solution space and jumping out of local extrema. This study performs a plant spatial distribution optimization of monocropping maize to maximize light interception. Simulation results indicate that the optimized row spacing can increase maize light interception comparing to the random row spacing within the spacing range (with maximum of 36.44% increment), and that the optimization results satisfy the optimal interval provided by previous field experiments.

Geographic range of plants drives long-term climate change

Long computation times in vegetation and climate models hamper our ability to evaluate the potentially powerful role of plants on weathering and carbon sequestration over the Phanerozoic Eon. Simulated vegetation over deep time is often homogenous, and disregards the spatial distribution of plants and the impact of local climatic variables on plant function. Here we couple a fast vegetation model (FLORA) to a spatially-resolved long-term climate-biogeochemical model (SCION), to assess links between plant geographical range, the long-term carbon cycle and climate. Model results show lower rates of carbon fixation and up to double the previously predicted atmospheric CO2 concentration due to a limited plant geographical range over the arid Pangea supercontinent. The Mesozoic dispersion of the continents increases modelled plant geographical range from 65% to > 90%, amplifying global CO2 removal, consistent with geological data. We demonstrate that plant geographical range likely exerted a major, under-explored control on long-term climate change.

Distribution Patterns of Gymnosperm Species along Elevations on the Qinghai–Tibet Plateau: Effects of Climatic Seasonality, Energy–Water, and Physical Tolerance Variables

Climate change is one of the most prominent factors influencing the spatial distribution of plants in China, including gymnosperms. Climatic factors influence gymnosperm distribution along elevational gradients on the Qinghai–Xizang (Tibet) Plateau (QTP), and understanding how species adapt to these factors is important for identifying the impacts of global climate change. For the first time, we examined the county-level distribution of gymnosperm species on QTP using data from field surveys, published works, monographs, and internet sources. We used simulated distribution data of gymnosperms (N = 79) along the elevational gradients to investigate the overall impact of environmental variables in explaining the richness pattern of gymnosperms. Eighteen environmental variables were classified into three key variable sets (climatic seasonality, energy–water, and physical tolerance). We employed principal component analysis and generalized linear models to assess the impact of climatic variables on the gymnosperm’s richness pattern. Gymnosperm species are unevenly distributed across the plateau and decline gradually from the southeast to the northwest. The altitudinal gradients have a unimodal relationship with the richness of gymnosperms, with the maximum species richness at an elevation of 3200 m. The joint effects of physical tolerance and energy–water predictors have explained the highest diversity of gymnosperms at mid-elevation. Because the richness peak correlates significantly with the wettest month’s precipitation and moisture index, this confirms the significance of moisture on gymnosperm distributions due to increased precipitation during the wet season. Furthermore, our results provide evidence that climatic seasonality factors are involved in the decline of gymnosperm richness at high elevations. A total of 37% of gymnosperm species on QTP are listed as vulnerable, nearly threatened, or endangered, with elevations ranging from 600 m to 5300 m. As a result, we conclude that gymnosperms are at high risk of extinction because of the current climate fluctuations caused by global climate change. Our research offers fundamental data for the study and protection of gymnosperm species along the steepest elevation gradients.

Spatial aggregation patterns in four mistletoe species: ecological and environmental determinants.

Plant spatial distribution is an important topic in ecology as it determines species coexistence and biodiversity dynamics. Usually, plants show clustered distributions in nature. Mistletoes are a good example of aggregated distributions, as they form dense aggregations due to several factors (availability of competent hosts, seed dispersal vectors, microclimate conditions). We analysed four native mistletoe species with divergent life histories and host ranges: Desmaria mutabilis and Tristerix corymbosus from the temperate rainforests of southern Chile; and Tristerix aphyllus and Tristerix verticillatus from the northern semi-desert zone. While T. corymbosus and T. verticillatus have a wide host range, T. aphyllus and D. mutabilis are specialists that can parasitize only a few plant species. We hypothesized that specialized species would be more aggregated due to ecological and environmental restrictions. We used heterogeneous Poisson models to quantify spatial aggregation. Three of the four mistletoe species were spatially clustered at both environments, with aggregation being stronger in the temperate rainforest of southern Chile and particularly in the host-specialist species. Our results suggest that environmental constraints are more important than ecological constraints (host range) in shaping mistletoe spatial structure. Mistletoe aggregated spatial distribution depends primarily on the environment that they inhabit, which conditions host spatial availability, and arrangement.

Early-stage development of an artificial dune with varying plant density and distribution

For the optimal design of artificial dunes, a fundamental understanding of morphological changes throughout the early phases of dune growth is required. This study examines the effect of different vegetation densities and patterns on the subsequent dune development during the first three months following construction. Marram grass (0.40 m in height) was planted in six zones (20 × 20 m2) with three different densities (6, 9 and 15 plants/m2) and four different patterns (gridded, random, clustered, and staggered). Monthly drone surveys were combined with daily to weekly topographic RTK-GNSS surveys along 12 cross-shore profiles (two per zone). Beach wind conditions were continuously monitored with a meteorological station. Additionally, four aeolian sand transport measurements were conducted with Modified Wilson And Cook sand traps. Results demonstrate the importance of using a specific plant density as well as the use of spatial plant distribution. The use of a staggered or random plant distribution leads to the formation of narrower bedforms, while higher vegetation densities also result in narrower bedforms. Bedform height is greater in zones with high vegetation density. Regardless of plant density and distribution, each plantation zone experienced dune development with a volume of 6 m3/m, primarily influenced by the supply of aeolian sand from the adjacent beach. Aeolian sand transport rapidly decreases within a downwind distance of 20 m from the vegetation edge. The ability to trap sand varies between size of the plants, with wider plants being able to trap sand over shorter distances. By the end of the study period, nearly all vegetation zones were completely buried, causing sand to bypass the dune. The future progression of dune development will be determined by the interaction between vegetation growth and sand burial.

Rhizobium nodule diversity and composition are influenced by clover host selection and local growth conditions.

While shaping of plant microbiome composition through 'host filtering' is well documented in legume-rhizobium symbioses, it is less clear to what extent different varieties and genotypes of the same plant species differentially influence symbiont community diversity and composition. Here, we compared how clover host varieties and genotypes affect the structure of Rhizobium populations in root nodules under conventional field and controlled greenhouse conditions. We first grew four Trifolium repens (white clover) F2 crosses and one variety in a conventional field trial and compared differences in root nodule Rhizobium leguminosarum symbiovar trifolii (Rlt) genotype diversity using high-throughput amplicon sequencing of chromosomal housekeeping (rpoB and recA) genes and auxiliary plasmid-borne symbiosis genes (nodA and nodD). We found that Rlt nodule diversities significantly differed between clover crosses, potentially due to host filtering. However, variance in Rlt diversity largely overlapped between crosses and was also explained by the spatial distribution of plants in the field, indicative of the role of local environmental conditions for nodule diversity. To test the effect of host filtering, we conducted a controlled greenhouse trial with a diverse Rlt inoculum and several host genotypes. We found that different clover varieties and genotypes of the same variety selected for significantly different Rlt nodule communities and that the strength of host filtering (deviation from the initial Rhizobium inoculant composition) was positively correlated with the efficiency of symbiosis (rate of plant greenness colouration). Together, our results suggest that selection by host genotype and local growth conditions jointly influence white clover Rlt nodule diversity and community composition.

Functional traits explain both seedling and adult plant spatial patterns in gypsum annual species

Abstract Ecological processes such as seed dispersal or plant–plant interactions and environmental constraints such as climate or soil heterogeneity are known to influence establishment, and thus the spatial patterns of plant communities and populations. In this study, we hypothesized that key functional traits such as the specific leaf area (SLA), reproductive ratio (reproductive/vegetative biomass), seed mass and maximum plant height would influence the spatial patterns of individual species in annual, gypsophilous plant communities, and that these effects would be modulated by both the soil surface structure (biocrust) and climate (precipitation) conditions. We mapped the spatial patterns of all plants found in six 1 × 1 m plots (more than 1000 individuals per plot) in both the seedling (autumn) and adult stages (spring) under two biocrust experimental conditions (intact vs. disturbed biocrust) during two consecutive years which were contrasted in term of precipitation (dry year and wet year). To assess the spatial patterns of seedlings and adults, we fitted four different spatial point pattern models (i.e. Poisson, inhomogeneous Poisson, Poisson cluster and inhomogeneous Poisson cluster processes) to each of the 242 populations of the 26 most abundant species that had more than 15 individuals per plot. Most seedling populations exhibited clustered spatial patterns that persisted in the adult stage, which suggests that short‐distance dispersal is an adaptive trait for soil specialists such as gypsophilous plants. One‐third of the populations fitted an inhomogeneous model best but the physical structure of the biocrust was not related to them. More importantly, we found a connection between the functional strategies of species and the spatial distribution of plants. In particular, during the dry year, irrespective of the biocrust conditions, species with a high SLA and high Rep/Veg mainly exhibited clustered spatial patterns, whereas low SLA and low Rep/Veg were associated with random distributions. Species with heavy and light seed masses had random and clustered patterns, respectively. In both the dry and wet years, species with lower maximum heights had clustered patterns, whereas taller species exhibited random patterns. In addition, species with heavier seeds and greater maximum heights had the largest cluster sizes. Our results confirm that the spatial patterns of seedlings and adult plants are significantly determined by the functional strategy of each species. Read the free Plain Language Summary for this article on the Journal blog.

Wave Propagation in Vegetation Field by Combining Fast Multiple Scattering Theory and Numerical Electromagnetics in a Hybrid Method

To calculate scattering of a vegetation field consisting of a large number of plants, an improved fast version of the hybrid method (FHM) combining fast multiple scattering theory (FMST) and a numerical electromagnetic approach has been developed. In the HM, we use a library of T-matrices and the Foldy–Lax (FL) equation to calculate the electromagnetic field interactions outside of the cylinders enclosing the individual plants. To improve CPU time and memory requirements, the FL equation is solved by a triplet of fast Fourier transforms (FFTs) consisting of two FFTs solving 2-D FFTs of spatial distribution of plants and one 1-D FFT for solving the transformation of the order of cylindrical waves in the translation addition theorem. The triple FFTs minimize the CPU time and the memory requirement for computing translation addition matrix, which has been the bottleneck of large-scale simulations in the HM. To account for nonperiodic distribution of scatterers in a corn field, the premultiplication and the postmultiplication processes were applied to the FHM. The proposed method is validated at L-band (1.4 GHz) for 100 corn plants of height 1.25 m occupying an area of 9.54 by 9.54 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}^{2}$ </tex-math></inline-formula> . On a standard laptop, the CPU time is less than 6 min and the memory consumption is less than 710 Mbytes. The CPU time and the memory requirements are orders of magnitude more efficient than those required for solving the problem with a commercial software or using the previous version of the HM.

Measurement of foliar H2O2 concentration can be an indicator of riparian vegetation management

Riparian vegetation is frequently exposed to abiotic stress, which generates reactive oxygen species (ROS) caused by strong differences in a river’s hydrological conditions. Among different ROS, hydrogen peroxide (H2O2) is relatively steady and can be measured appropriately. Thus, the quantification of plant H2O2 can be used as a stress indicator for riparian vegetation management. The current study examines the spatial distribution of plants by riparian vegetation communities across the elevation gradient of riparian zones through quantification of environmental stress using foliar H2O2 concentration. The trees Salix spp., Robinia pseudoacacia, Ailanthus altissima with Juglans mandshurica, and the herbs Phragmites australis, Phragmites japonica, and Miscanthus sacchariflorus were selected for this study. Leaf tissues were collected to analyze H2O2 concentration, meanwhile riparian soil was sampled to measure total nitrogen (TN), total phosphorus (TP), and moisture content. The H2O2 concentration of tree species increased with higher soil moisture content, which was negatively correlated for Salix and herb spp., in which H2O2 concentration always decreased with high soil moisture. In this study, we found a unique significant interaction between soil moisture content and H2O2 concentration, both positively or negatively correlated relationships, when compared with other parameters, such as TN or TP concentrations or TN: TP in riparian soil. The species-specific distribution zones can be explained by the H2O2 concentration in the plant for gravelly and sandy channels on a theoretical range of soil moisture. Each species’ H2O2 concentration was estimated through derived equations and is directly related to an elevation above the channel. The comparison with the observed distribution of plant elevations in the field indicated that all species showed a spatial distribution that acts as species-specific elevations where H2O2 concentrations stayed below 40 μmol/gFW. Hence, the present study suggests that foliar H2O2 concentration can be a useful benchmark for the distribution potentiality of riparian vegetation.

Arbuscular mycorrhizal root colonization depends on the spatial distribution of the host plants

Despite their ubiquity in terrestrial ecosystems, arbuscular mycorrhizal fungi (AMF) experience dispersion constraints and thus depend on the spatial distribution of the plant hosts. Our understanding of fungal-plant interactions with respect to their spatial distributions and implications for the functioning of the symbiosis remain limited. We here manipulated the location of habitat patches of Medicago lupulina in two experiments to explore the responses of AMF root colonization and extraradical hyphae. We tested the specific hypothesis that AMF-plant habitats high in connectance would stimulate root colonization and induce denser functional root colonization (colonization rate of arbuscules plus coils) because of higher propagule availability between nearby host plant patches (experiment 1). In experiment 2, we anticipated similar responses in mixed habitats of different soil fertility, namely phosphorus-fertilized or unfertilized soil, and anticipated a higher density of extraradical hyphae in the soil connecting the habitats with increased functional root colonization. In agreement with our hypothesis, we found the highest total and functional root colonization in unfragmented micro-landscapes, describing landscapes that occur within a spatial scale of a few centimeters with the AMF-plant habitats positioned adjacent to each other. In the second experiment, overdispersed micro-landscapes promoted functional root colonization. This study provides experimental evidence that the spatial distribution of habitats can determine AMF abundance at the microscale.

Trinexapac-ethyl application time in the crop corn agronomic performance grown under different plant arrangements

Reduced row spacing promotes more uniform spatial distribution of plants in the field. However, the adoption of reduced row spacing only is possible with smaller plants, which may be obtained with the use of plant growth regulator. This study aimed to evaluate the agronomic performance of the first corn crop with Trinexapac-ethyl applied at the different plant development stages and grown under different row spacing, with the same plant population. The experiments were arranged in a split-plot randomized block design with four replications, with row spacing for the plots (0.45 and 0.90 m) and Trinexapac-ethyl (TE) application time to subplots (control without application, at the V3, V6, V9 and V12 phenological stages). The Trinexapacethyl application time interacted with row spacings changing the growth and yield performance of the corn crop. For 0.45 m spacing Trinexapac-ethyl application at V12 and for 0.90 m spacing application at V9 and V12 reduced plant height and ear height. Trinexapac-ethyl application at V9 for both row spacings changed the plant architecture without changing the ear length and grain yield.

Estimating the spatial distribution of possible livestock production level using a mathematical model and the SMAP soil moisture data: The case of Botswana

In a traditional livestock farming, the livelihood of animals depends highly on existing plant biomass, which is affected by the level and intensity of temperature, rainfall, humidity and other meteorological variables. Understanding the interaction of such meteorological factors and agricultural production in general is an important aspect in planning at the macro and micro levels. Particularly livestock agriculture is heavily affected by the changing climate, and hence the variation in major meteorological variables. However, there is still limited research regarding the impacts of meteorological variables on livestock production in each particular region. Soil moisture is one of the main factors in agricultural production and hydrological cycles with better memory of previous weather conditions. It also involves complex structural characteristics and meteorological factors. In this study, a soil moisture dependent mathematical model for the interaction of plants and herbivores is developed and analysed. The Soil Moisture Active Passive level 4 satellite soil moisture data is used in the model to simulate the possible spatial distribution of plants and the corresponding potential livestock production level for Botswana. A global dynamic sensitivity analysis is employed to study the sensitivity of the solution of the model with a variation in the involved parameter values. The results of the simulations of the model show that estimated livestock harvest in wet regions is more than triple as compared to what is estimated for dry regions. If some important parameters are properly estimated and the soil moisture data is available for each region, it is possible to estimate the livestock production level for each spatial region with better accuracy using the proposed model.

FROST RESISTANCE OF THE COLUMNAR APPLE TREE THE METHOD OF DIRECT FREEZING

Frost stress strongly affects the spatial distribution of plants. Among various weather hazards, frost causes the greatest economic losses in agriculture. Among various environmental hazards, it is frost that causes the greatest economic losses in agriculture. Although frost severely limits life forms and creates enormous economic losses, it has not been studied as thoroughly as other biotic or abiotic stresses. Frost resistance can be affected by many factors, including microclimate, soil condition, plant height, but they must be studied in a complex. The purpose of the research was to select frost-resistant cultivars and hybrids of the columnar apple tree under the conditions of the Forest Steppe of Ukraine. The research was carried out during 2021–2022 at the V.L. Symyrenko Department of Horticulture of the National University of Life and Environmental Sciences of Ukraine. The experimental basis for conducting research was the columnar apple tree plantations of the Training Laboratory «Fruit and Vegetable Garden». Frost resistance was determined during the period of deep rest by the method of direct freezing of one-year increments. Freezing was performed in the laboratory of plant physiology and microbiology of the National Academy of Sciences of Ukraine. In the researched plantations, when the test samples were frozen at temperatures of -25 and -30 °C during deep rest, different resistance of varieties and shoot parts to low temperatures was found. In all cultivars and hybrids of columnar type apple trees, the apical bud and generative buds were the most vulnerable, and the tissues of the middle and upper part of the shoot were the most resistant to frost. The damage index during general freezing was the lowest in the cultivars Valuta’, Sparta’, Favoryt’, Bilosnizhka’, as well as in the hybrids 9/110 Mykhailivske’, 11/15(2)’ and 9/78 Viktoriia’; it was the largest in the Bolero’ cultivars. Freezing of experimental samples at temperatures of -25 and -30 °C did not result in frostbite, critical for plants. All studied cultivars and hybrids of columnar apple trees are recommended for further research and production. The obtained results will be interesting for both experienced gardeners and amateur gardeners who plan to grow columnar apple trees in their garden.

Why do traditional dispersion indices used for analysis of spatial distribution of plants tend to become obsolete?

AbstractIt is common to characterize the spatial distribution of plant patterns as random, aggregate, or uniform. In this context, a major challenge for the researcher is the choice of the method to identify the spatial pattern correctly as well as the factors related to it. The vast literature on the subject is not recent, especially regarding the dispersion indices. The aim of this review was to conduct a critical and temporal analysis of these dispersion indices and test their effectiveness in determining the spatial distribution of Paepalanthus chiquitensis Herzog (Eriocaulaceae). This species is a meaningful model due to its occurrence in specific sites. The Lexis, Charlier, dispersion, relative variance, aggregation, Green, inverse of k of the negative binomial, Morisita, and standardized Morisita indices were limited to indicating that the individuals of the species are aggregate and did not provide information on neither spatial dimension (scale) where the aggregation occurs, nor the factors related to this aggregation. Although they have distinct magnitudes, the algebraic expressions of dispersion, relative variance, aggregation, Green, inverse of k, Morisita, and standardized Morisita indices exhibited a close relationship with each other and little progress from their precursors Lexis and Charlier. By disregarding the possibility of spatial dependence, these indices make it impossible to generate important hypotheses for the investigation of factors related to spatial structure. Therefore, they became obsolete and are falling into disuse. It should be noted that these measurements accomplished their role and contributed to science in times of limited technologies for spatial data.

Aerial and Optical Images-Based Plant Species Segmentation Using Enhancing Nested Downsampling Features

Plant species, structural combination, and spatial distribution in different regions should be adapted to local conditions, and the reasonable arrangement can bring the best ecological effect. Therefore, it is essential to understand the classification and distribution of plant species. This paper proposed an end-to-end network with Enhancing Nested Downsampling features (END-Net) to solve complex and challenging plant species segmentation tasks. There are two meaningful operations in the proposed network: (1) A compact and complete encoder–decoder structure nests in the down-sampling process; it makes each downsampling block obtain the equal feature size of input and output to get more in-depth plant species information. (2) The downsampling process of the encoder–decoder framework adopts a novel pixel-based enhance module. The enhanced module adaptively enhances each pixel’s features with the designed learnable variable map, which is as large as the corresponding feature map and has n×n variables; it can capture and enhance each pixel’s information flexibly effectively. In the experiments, our END-Net compared with eleven state-of-the-art semantic segmentation architectures on the self-collected dataset, it has the best PA (Pixel Accuracy) score and FWloU (Frequency Weighted Intersection over Union) accuracy and achieves 84.52% and 74.96%, respectively. END-Net is a lightweight model with excellent performance; it is practical in complex vegetation distribution with aerial and optical images. END-Net has the following merits: (1) The proposed enhancing module utilizes the learnable variable map to enhance features of each pixel adaptively. (2) We nest a tiny encoder–decoder module into the downsampling block to obtain the in-depth plant species features with the same scale in- and out-features. (3) We embed the enhancing module into the nested model to enhance and extract distinct plant species features. (4) We construct a specific plant dataset that collects the optical images-based plant picture captured by drone with sixteen species.

High Density and Uniform Plant Distribution Improve Soybean Yield by Regulating Population Uniformity and Canopy Light Interception

Optimizing the spatial distribution of plants under normal conditions of water and fertilizer is widely used by farmers to improve soybean yield. However, the relationship between soybean yield and spatial plant distribution in the field has not been well studied. This study examined the effect of planting density and plant distribution pattern on soybean plant growth, yield components, canopy light interception, and dry matter accumulation. We also analyzed the relationship between photosynthetic rate, dry matter accumulation, and yield under different planting densities and plant distribution. A two year field experiment was conducted during the 2018 and 2019 soybean planting seasons. Two planting densities (1.8 × 105 and 2.7 × 105 plants ha−1) and two plant distribution patterns (uniform and non-uniform plant spacing) were tested. Higher planting density significantly increased the canopy light interception and dry matter accumulation during soybean growth, leading to increased soybean productivity. The seed yield of soybean under higher planting density was 22.8% higher than under normal planting density. Soybean planted under uniform spacing significantly reduced the differences plant-to-plant. Uniform plant spacing significantly increased the canopy light interception and dry matter accumulation of the soybean population. In addition, the coefficient of variation of seed weight per plant between individual plants under uniform plant distribution decreased by 71.5% compared with non-uniform plant distribution. Furthermore, uniform plant distribution increased soybean seed yield by 9.5% over non-uniform plant distribution. This study demonstrates that increasing planting density under uniform plant distribution can be useful to obtain higher seed yield without increasing other farm inputs.

Anthropogenic and environmental determinants of alien plant species spatial distribution on an island scale

Mediterranean islands are considered especially vulnerable to biological invasions by alien plants. However, there is a lack of studies on island scale regarding the factors that determine alien plant's spatial distribution, and the way they affect invasion process. A roadside survey of alien plant species was conducted on Lesvos, the 8th largest island in Mediterranean basin. Data on species counts and explanatory variables were aggregated to a 1 sq. km vector grid and brought together into a single GIS layer. Alien species counts were modelled by using a Negative-binomial model while a Generalised Additive Model was used to examine possible non-linear relationships to the predictors by using splines. A subset of significant factors, related both to human activities and the environment, shaped the spatial distribution of aliens and influenced, in various ways, their future invasion outcome. Transformed areas with high levels of anthropogenic pressures and disturbances, including high population numbers, dense road network, ports, and intensive land use, as is the case for coastal zones, promoted the presence of alien species. Contrary, modified areas, such as grazed lands, seemed to restrict alien species occurrences, possibly due to the long grazing history these areas present, a regime in which aliens are not adapted. Alien plants presence was positively associated with high levels of NPP, diversity of geological substrates, and a west-facing aspect. Anthropogenic determinants of alien spatial patterns were primarily connected to increased propagule pressure, whereas environmental factors demonstrated the preference of alien plants for resource-rich environments.