Canopy Area Research Articles

Effect of Missing Vines on Total Leaf Area Determined by NDVI Calculated from Sentinel Satellite Data: Progressive Vine Removal Experiments

Remote Sensing (RS) allows the estimation of some important vineyard parameters. There are several platforms for obtaining RS information. In this context, Sentinel satellites are a valuable tool for RS since they provide free and regular images of the earth’s surface. However, several problems regarding the low-resolution of the imagery arise when using this technology, such as handling mixed pixels that include vegetation, soil and shadows. Under this condition, the Normalized Difference Vegetation Index (NDVI) value in a particular pixel is an indicator of the amount of vegetation (canopy area) rather than the NDVI from the canopy (as a vigour expression), but its reliability varies depending on several factors, such as the presence of mixed pixels or the effect of missing vines (a vineyard, once established, generally loses grapevines each year due to diseases, abiotic stress, etc.). In this study, a vine removal simulation (greenhouse experiment) and an actual vine removal (field experiment) were carried out. In the field experiment, the position of the Sentinel-2 pixels was marked using high-precision GPS. Controlled removal of vines from a block of cv. Cabernet Sauvignon was done in four steps. The removal of the vines was done during the summer of 2019, matching with the start of the maximum vegetative growth. The Total Leaf Area (TLA) of each pixel was calculated using destructive field measurements. The operations were planned to have two satellite images available between each removal step. As a result, a strong linear relationship (R2 = 0.986 and R2 = 0.72) was obtained between the TLA and NDVI reductions, which quantitatively indicates the effect of the missing vines on the NDVI values.

Effect of canopy gap size on soil respiration in a mixed broadleaved-Korean pine forest: Evidence from biotic and abiotic factors

Understanding the effects of forest structure, the frequency and size of canopy gaps is pivotal for precisely modelling forest soil carbon budgets. We aimed to determine the differences in soil respiration between closed canopy areas and canopy gaps with various sizes and how soil respiration is affected by biotic and abiotic factors, e.g., soil nutrients, soil microbial biomass and community composition, enzyme activities and fine root biomass. Soil respiration and these environmental factors were measured in eleven tree fall gaps (separated into small, medium and large with sizes ranging from 20 m2 to 450 m2) and three control plots in a mixed broadleaved-Korean pine forest during the growing season. Our results showed that soil respiration was similar between the control and small canopy gaps, while it was 17–49% lower in the medium and large canopy gaps compared to that of the control. There was a significant parabolic relationship between soil respiration and soil moisture, and the optimum moisture was approximately 40%. Fine root biomass and soil enzyme activities showed positive effects on soil respiration across different levels of canopy gaps. Furthermore, soil respiration was significantly declined with increasing soil microbial diversity (OTUs of bacteria). Our findings demonstrate that canopy gap has significant impact on soil CO2 emission in a temperate mixed forest, however, further studies concerning other forest ecosystem types and larger scale are warranted.

Quantitative Airborne Inventories in Dense Tropical Forest Using Imaging Spectroscopy

Tropical forests have exceptional floristic diversity, but their characterization remains incomplete, in part due to the resource intensity of in-situ assessments. Remote sensing technologies can provide valuable, cost-effective, large-scale insights. This study investigates the combined use of airborne LiDAR and imaging spectroscopy to map tree species at landscape scale in French Guiana. Binary classifiers were developed for each of 20 species using linear discriminant analysis (LDA), regularized discriminant analysis (RDA) and logistic regression (LR). Complementing visible and near infrared (VNIR) spectral bands with short wave infrared (SWIR) bands improved the mean average classification accuracy of the target species from 56.1% to 79.6%. Increasing the number of non-focal species decreased the success rate of target species identification. Classification performance was not significantly affected by impurity rates (confusion between assigned classes) in the non-focal class (up to 5% of bias), provided that an adequate criterion was used for adjusting threshold probability assignment. A limited number of crowns (30 crowns) in each species class was sufficient to retrieve correct labels effectively. Overall canopy area of target species was strongly correlated to their basal area over 118 ha at 1.5 ha resolution, indicating that operational application of the method is a realistic prospect (R2 = 0.75 for six major commercial tree species).

Biomass partitioning and allometric relations of the Reaumuria soongorica shrub in Alxa steppe desert in NW China

Allometry and partitioning of above- and below-ground biomass are needed to evaluate the sustainability of arid ecosystems. Biomass accumulation, allocation patterns, and allometric relationships for above- and below-ground components of the desert shrub Reaumuria soongorica were studied across five age classes (0–10, 11–20, 21–30, 31–40, and > 40 years) in Alxa desert steppe, northwestern (NW) China, where the biomass of each shrub component (i.e., leaves, branches, and coarse and fine roots) was harvested by destructive sampling and the allocation patterns between leaves (ML), roots (MR), branches (MB) were studied by regression analysis of log10-transformed data, and tested for data classified by age class and pooled data. By using basal diameter, age, height, and canopy area, we can predict the allometry properties of the R. soongorica shrub in terms of age class and/or entire age-sequence. The experimental results indicate that biomass accumulation has an obvious gradient across the five age classes, branch, and coarse root biomass were the main biomass pool as mature shrub. R. soongorica shrub partitioned a greater proportion of total biomass to roots with age in order to adapt to the extreme arid conditions. Shrub allometry was affected by variation of biomass partitioning, where the allometric relationships were strongly related to basal shrub diameter for almost all shrub components. Allometric biomass relationships were improved with the introduction of a second variable crown area.

Effect of spread and shallow irrigation wetted area and application of organic mulch on citrus decline amelioration

Citrus decline threatens the orchards in the southern part of Iran. Roots begin to die-out before citrus decline deterioration. In this study, the effect of expanding the irrigation wetted area and decreasing the irrigation depth, and application of compost as organic mulch on root development and amelioration of citrus decline in Valencia orange trees (Citrus scinensis L. Osbeck) was investigated. Experimental factors contained the different percentage of irrigation wetted area and decreasing irrigation effective root depth by drip irrigation system at three levels - control (30-40% with 60 cm effective root depth), 50-60% with 45 cm effective root depth and 70-80% with 30 cm effective root depth under tree canopy area and the factor of annual application of compost as organic mulch at two levels - control (without) and application of 80 kg compost under tree canopy area with 10 cm thickness as ground cover, after rotating the top soil at 10 cm depth for all treatments. The results showed that, annual application of compost as organic mulch under tree canopy area and expanding the irrigation wetted area with decreasing irrigation effective root depth, significantly improved fibrous root length and density at a lower soil depth and decreased the indices of citrus decline such as root rot percentage, leaf and fruit drop and shoot die back. Also these treatments increased the water productivity and fruit quality of in declining Valencia orange trees.

Remote sensing: generation of long-term kelp bed data sets for evaluation of impacts of climatic variation.

A critical tool in assessing ecosystem change is the analysis of long-term data sets, yet such information is generally sparse and often unavailable for many habitats. Kelp forests are an example of rapidly changing ecosystems that are in most cases data poor. Because kelp forests are highly dynamic and have high intrinsic interannual variability, understanding how regional-scale drivers are driving kelp populations-and particularly how kelp populations are responding to climate change-requires long-term data sets. However, much of the work on kelp responses to climate change has focused on just a few, relatively long-lived, perennial, canopy-forming species. To understand how kelp populations with different life history traits are responding to climate-related variability, we leverage 35yr of Landsat satellite imagery to track the population size of an annual, ruderal kelp, Nereocystis luetkeana, across Oregon. We found high levels of interannual variability in Nereocystis canopy area and varying population trajectories over the last 35yr. Surprisingly, Oregon Nereocystis population sizes were unresponsive to a 2014 marine heat wave accompanied by increases in urchin densities that decimated northern California Nereocystis populations. Some Oregon Nereocystis populations have even increased in area relative to pre-2014 levels. Analysis of environmental drivers found that Nereocystis population size was negatively correlated with estimated nitrate levels and positively correlated with winter wave height. This pattern is the inverse of the predicted relationship based on extensive prior work on the perennial kelp Macrocystis pyrifera and may be related to the annual life cycle of Nereocystis. This article demonstrates (1) the value of novel remote sensing tools to create long-term data sets that may challenge our understanding of nearshore marine species and (2) the need to incorporate life history traits into our theory of how climate change will shape the ocean of the future.

Pollen production for 13 urban North American tree species: Allometric equations for tree trunk diameter and crown area.

Estimates of airborne pollen concentrations at the urban scale would be useful for epidemiologists, land managers, and allergy sufferers. Mechanistic models could be well suited for this task, but their development will require data on pollen production across cities, including estimates of pollen production by individual trees. In this study, we developed predictive models for pollen production as a function of trunk size, canopy area, and height, which are commonly recorded in tree surveys or readily extracted from remote sensing data. Pollen production was estimated by measuring the number of flowers per tree, the number of anthers per flower, and the number of pollen grains per anther. Variability at each morphological scale was assessed using bootstrapping. Pollen production was estimated for the following species: Acer negundo, Acer platanoides, Acer rubrum, Acer saccharinum, Betula papyrifera, Gleditsia triacanthos, Juglans nigra, Morus alba, Platanus x acerfolia, Populus deltoides, Quercus palustris, Quercus rubra, and Ulmus americana. Basal area predicted pollen production with a mean R2 of 0.72 (range: 0.41 - 0.99), whereas canopy area predicted pollen production with a mean R2 of 0.76 (range: 0.50 - 0.99). These equations are applied to two tree datasets to estimate total municipal pollen production and the spatial distribution of street tree pollen production for the focal species. We present some of the first individual-tree based estimates of pollen production at the municipal scale; the observed spatial heterogeneity in pollen production is substantial and can feasibly be included in mechanistic models of airborne pollen at fine spatial scales.

Monitoring Tree-Shrub, and Meadow Vegetation in the Volga-Akhtuba Floodplain Using Remote Sensing Methods (Based on “Krasnyy Buksir” Range)

The article deals with the assessment of the state of tree-shrub and meadow vegetation by remote sensing methods. The author reveals the reasons of degradation and change of floristic richness of vegetation. These include: trampling of grass cover and forest floor (1), mechanical damage of trees (2), increasing the area of fire pits (3), and littering and contamination of the territory (4). In addition, mowing and grazing have a great influence. The development of the path network leads to changes in water-physical properties of the soil. Changes in the species composition of meadow vegetation indicate an increase in the processes of xerophytization and pasture digression. The article considers various methods of decoding forest plantations. Among them, the method of aerospace research is the most effective. This method makes it possible to assess the state of tree-shrub and meadow vegetation in dynamics and to carry out continuous monitoring. For a greater accuracy of the assessment, Earth remote sensing data are confirmed by on-site studies. Projective coverage has been used as a sign of degradation for the assessment. The level of preservation of plantings has been determined by the area of the canopy of the stand, that is the ratio of the canopy area to the entire area of the plantings. Under the area of the canopy a set of pixels that match the tone assigned to the canopy is understood. Using the methodology given in the article, the author has carried out the vegetation analysis at “Krasnyy Buksir” range. The area of land belonging to different environmental levels has been calculated for this purpose. The author draws the conclusion that the studied site is subject to a significant anthropogenic load and environmental protection measures are strongly necessary in this area.

Experimental study on the effect of plant spacing, number of rows and arrangement on the airflow field of forest belt in a wind tunnel

Forest belts play an important role in soil wind erosion control and the prevention of aeolian sand movement in arid and semiarid regions. In order to reveal the effect of plant spacing, number of rows, and arrangement on airflow of forest belt, the airflow fields were measured in a wind tunnel for artificial single-row forest belts with different plant spacings, forest belts with different numbers of rows with the same plant spacing, and two rows of forest belts with different arrangements. The results indicate that for the single-row forest belt, the downwind airflow decreases in the canopy area and then recovers exponentially. As the plant spacing increases, the characteristic length of the downwind airflow recovery of the forest belt and the distance at which the minimum wind speed is located both decrease approximately exponentially. As the number of rows in a forest belt increases, the downwind airflow speed in the canopy area decreases. The average reduction of downwind relative wind speed decreases with plant spacing and increases with the number of rows. A forest belt with staggered arrangement has lower downwind speeds and a longer characteristic length of airflow recovery than that in rectangular arrangements.

Molecular and morphological characterization of EMS-induced chili pepper mutants resistant to Chili veinal mottle virus

Abstract. Manzila I, Priyatno TP, Nugroho K, Terryana RT, Lestari P, Hidayat SH. 2020. Molecular and morphological characterization of EMS-induced chili pepper mutants resistant to Chili veinal mottle virus. Biodiversitas 21: 1448-1457. Chili veinal mottle virus (ChiVMV) is a major prevalent virus that potentially reduces the yield of chili pepper by more than 50% in Indonesia. Therefore, the development of a ChiVMV-resistant cultivar is necessary to ensure satisfactory chili pepper production. Mutation breeding is a promising tool available to produce virus-resistant plants via the induction of new alleles due to point mutations within the existing chili germplasm. This research was conducted to assess the genetic variation of ten promising (M6) EMS-induced mutant lines of chili pepper (Capsicum annuum L.) potentially resistant to ChiVMV by their morphological characteristics and SSR profile, as well as identify potential mutants based on agronomic traits. The ten chili pepper mutant lines used in the present study were derived from the shoot tips of a Gelora cultivar treated with 0.5% ethyl methanesulfonate (EMS) as a chemical mutagen. The performance of the respective promising chili pepper mutant lines both at a molecular and morphological level was observed. Phenotypic analysis showed that all the promising chili pepper mutant lines underwent significant morphological changes. Of these, the phenotype coefficient variation (PCV) values were higher than the genotype coefficient variation (GCV) values for all the traits observed. High heritability (h2) was found for the canopy area, length of the fruit stalk, fruit weight, fruit weight per plant, thick fruit flesh, leaf width, leaf length, and fruit storage duration. A total of 52 alleles were detected from the five polymorphic SSR loci with 5.2 average alleles/loci. A dendrogram was generated and revealed two groups with five mutants clustered separately from their parents which could be valuable for further improvement.

Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images

Quantifying canopy biophysical parameters is critical to agricultural research and farm management. In this study, strawberry dry biomass and leaf area were modeled statistically using high spatial and temporal resolution imagery. A mobile field data acquisition system was used to acquire thousands of very high resolution (~0.5 mm) close-range images seven times throughout the strawberry growing season. Ortho-mosaics and dense point clouds were generated through Structure from Motion (SfM) and used in Object-Based Image Analysis (OBIA) at the sub-leaf level to extract canopy structure variables such as planimetric canopy area, canopy average height, and canopy smoothness metric. Regression analysis was carried out using these image-derived canopy variables as predictors to model leaf area (R2 = 0.79; ten-fold cross-validation RMSE = 0.056 m2) and dry biomass (R2 = 0.84; ten-fold cross-validation RMSE = 7.72 g) obtained through destructive measurements. Results indicate consistent predictive power through the season and across 17 strawberry genotypes. The study showed that the canopy smoothness metric developed in this study as an indicator of canopy density could complement other variables (planimetric canopy area, canopy average height) that describe canopy geometric properties.

A New Passive Microwave Tool for Operational Forest Fires Detection: A Case Study of Siberia in 2019

The purpose of this paper is to present a new method for early detection of forest fires, especially in forest zones prone to fires using microwave remote sensing and information-modeling tools. A decision-making system is developed as a tool for operational coupled analysis of modeling results and remote sensing data. The main operating structure of this system has blocks that calculate the moisture of forest canopy, the soil-litter layer, and the forest physical temperature using the observed brightness temperature provided by the flying platform IL-18 equipped with passive microwave radiometers of 1.43, 13.3 and 37.5 GHz frequencies. The hydrological parameters of the forest are assessed with both a developed regional hydrological model and remote sensing observations. The hydrological model allows for the detection of fire-prone zones that are subject to remote sensing when modeling results are corrected and thermal temperatures are evaluated. An approach for the real time forest fires classification via daytime remote sensing observations is proposed. The relative theoretical and experimental results presented here have allowed us to use a new approach to forests monitoring during periods of potential fire. A decision-making algorithm is presented that aims at analyzing data flows from radiometers located on the remote sensing platform to calculate the probability of forest fire occurring in geographical pixels. As case study, the state of forest fires that occurred in Siberia in 2019 using microwave remote sensing measurements conducted by a flying IL-18 laboratory is presented. This remote sensing platform is equipped with optical and microwave tools that allow the optical and microwave images of the observed forest areas. The main operating frequencies of microwave radiometers are 1.43, 13.3 and 37.5 GHz. Microwave radiometers provide data on water content in the forest canopy and on litter and physical temperatures. Based on the long-term measurements made in Siberia, the possible improvement of the proposed decision-making system for future relevant studies is discussed in detail. The basic idea of cost-effective monitoring of forested areas consists of a two-stage exploration of fire risk zones. The first monitoring stage is performed using the hydrological model of the study area to identify low moisture areas of the forest canopy and litter. The second stage of monitoring is conducted using the remote sensing platform only in the local fire-dangerous areas in order to more precisely identify the areas prone to fire and to detect and diagnose real burning zones. The developed algorithm allows the calculation of physical temperatures and the detection of temperature anomalies based on measured brightness temperatures. Finally, the spatial distribution of the probability of forest fire occurrence is given as an example of the decision-making system along with a comparison of this distribution with the satellite images provided by the EOSDIS Land data.

The investigation of in-channel aquatic vegetation (IAV) effect on hyporheic exchange (HE) with the solute tracer experiment

To explore and quantify the effect of in-channel aquatic vegetation (IAV) on hyporheic exchange (HE), the research with solute tracer method were launched in a homogenous sand bed flume. The experiments took 3 trials including one control trial and two subsequent trials with only dependent variable of emergent IAV’s canopy area. The hypothesis that that IAV area has the positive correlation with mean hydraulic residence time (HRT) and correspondingly negative correlation with mean rate of HE. Comparation of the experimental support the hypothesis. However, rate of HE shows negative correlation with IAV area increasing at initial period. It is speculated that phenomenon is caused by sediment mobility which changed water pressure diffidence and formed long seepage path under IAV area. The speculation requires further research. The exploration of the complex interaction between IAV and HE requires further is still in its infancy. This research provides the promising evidence to further investigation.

Determining water requirements for young peach trees in a humid subtropical climate

In the southern USA, low soil water holding capacity and erratic rainfall patterns create scenarios where plant water stress may occur, reducing early peach tree growth. Therefore, irrigation management is a key component to ensure adequate water supply during early tree growth stages. The objective of this study was to determine water requirements and crop coefficient (Kc) of young peach trees grown in a subtropical climate. A study was conducted in central Florida using young peach trees ‘TropicBeauty’ grafted onto ‘Flordaguard’. Daily actual evapotranspiration (ETA) was determined using weighing lysimeters. The highest daily peach water demand was recorded during the shoot development stage (23.7 L) between August and October, whereas the lowest daily ETA was 0.71 L, during dormancy in December and January. Year-round Kc values for young peach trees were obtained and ranged from 0.20 to 0.68. There was a significant correlation between plant water consumption with trunk cross-sectional area (TCSA) and projected canopy area (PCA), which can be used to estimate ETA. Peach irrigation water demand for 1–3 years old trees, expressed as daily ETA, can be estimated using daily reference evapotranspiration and PCA. The accurate determination of crop water demand allows the seasonal adjustment of irrigation scheduling avoiding water stress, or over-irrigation of young peach trees.

Interlacing Orchard Canopy Separation and Assessment using UAV Images

To minimize pesticide dosage and its adverse environmental impact, Unmanned Aerial Vehicle (UAV) spraying requires precise individual canopy information. Branches from neighboring trees may overlap, preventing image-based artificial intelligence analysis from correctly identifying individual trees. To solve this problem, this paper proposes a segmentation and evaluation method for mingled fruit tree canopies with irregular shapes. To extract the individual trees from mingled canopies, the study fitted the projection curve distribution of the interlacing tree with Gaussian Mixture Model (GMM) and solved the matter of segmentation by estimating the GMM parameters. For the intermingling degree assessment, the Gaussian parameters were used to quantify the characteristics of the mingled fruit trees and then as the input for Extreme Gradient Boosting (XGBoost) model training. The proposed method was tested on the aerial images of cherry and apple trees. Results of the experiments show that the proposed method can not only accurately identify individual trees, but also estimate the intermingledness of the interlacing canopies. The root mean squares (R) of the over-segmentation rate (Ro) and under-segmentation rate (Ru) for individual trees counting were less than 10%. Moreover, the Intersection over Union (IoU), used to evaluate the integrity of a single canopy area, was greater than 88%. An 84.3% Accuracy (ACC) with a standard deviation of 1.2% was achieved by the assessment model. This method will supply more accurate data of individual canopy for spray volume assessments or other precision-based applications in orchards.

Allometric Relationships for Predicting Aboveground Biomass and Sapwood Area of Oneseed Juniper (Juniperus monosperma) Trees.

Across the semiarid ecosystems of the southwestern USA, there has been widespread encroachment of woody shrubs and trees including Juniperus species into former grasslands. Quantifying vegetation biomass in such ecosystems is important because semiarid ecosystems are thought to play an important role in the global land carbon (C) sink, and changes in plant biomass also have implications for primary consumers and potential bioenergy feedstock. Oneseed juniper (Juniperus monosperma) is common in desert grasslands and pinyon–juniper rangelands across the intermountain region of southwestern North America; however, there is limited information about the aboveground biomass (AGB) and sapwood area (SWA) for this species, causing uncertainties in estimates of C stock and transpiration fluxes. In this study, we report on canopy area (CA), stem diameter, maximum height, and biomass measurements from J. monosperma trees sampled from central New Mexico. Dry biomass ranged between 0.4 kg and 625 kg, and cross-sectional SWA was measured on n = 200 stems using image analysis. We found a strong linear relationship between CA and AGB (r2 = 0.96), with a similar slope to that observed in other juniper species, suggesting that this readily measured attribute is well suited for upscaling studies. There was a 9% bias between different approaches to measuring CA, indicating care should be taken to account for these differences to avoid systematic biases. We found equivalent stem diameter (ESD) was a strong predictor of biomass, but that existing allometric models underpredicted biomass in larger trees. We found SWA could be predicted from individual stem diameter with a power relationship, and that tree-level SWA should be estimated by summing the SWA predictions from individual stems rather than ESD. Our improved allometric models for J. monosperma support more accurate and robust measurements of C storage and transpiration fluxes in Juniperus-dominated ecosystems.

Impacts of Urban Form on Thermal Environment Near the Surface Region at Pedestrian Height: A Case Study Based on High-Density Built-Up Areas of Nanjing City in China

The continuous worsening of urban thermal environments poses a severe threat to human health and is among the main problems associated with urban climate change and sustainable development. This issue is particularly severe in high-density built-up areas. Existing studies on the thermal environments (temperature data extracted from satellite remote sensing images) are mainly focused on urban canopy areas (airspace below the average height of trees or buildings) rather than the near surface region (at pedestrian height). However, the main outdoor activity space of urban residents is the area near surface region. Hence, this study aims to investigate the influence of urban form (i.e., building density, height, and openness) on thermal environment near the surface region. The high-density built-up areas of a typical megacity (i.e., Nanjing) in China were selected, and the thermal environments of 26 typical blocks were simulated using ENVI-met software. Temperature field measurements were carried out for simulation validation. On this basis, a classified and comparative study was conducted by selecting the key spatial form elements that affect thermal environments. The results showed that in actual high-density built-up areas, single urban form parameter does not determine the thermal environments near the urban surface but mainly affected by the use (function) of space. For this study, the overall thermal environment of a street block is optimal when the building density is between 40% and 50% and the average building height is between 8 and 17 stories. Nonetheless, the urban form can be improved to optimize the overall effects on building functions and thermal environments. Furthermore, function-specific urban form optimization strategies were proposed to optimize thermal environments according to specific functional needs.

VARIATION AND RELATIONSHIPS OF AERIAL YIELD, MORPHO-AGRONOMIC TRAITS AND ESSENTIAL OIL COMPOSITION IN DOMESTIC POPULATIONS OF Ziziphora tenuior IN IRAN

The present study was carried out to evaluate aerial yield, agronomic traits, essential oil production, and their relationships in 21 populations of Ziziphora tenuior in Karaj, Iran over two years (2016–2017). The experimental layout was a randomized complete block design with three replications. Data were collected for GDD (Growth Degree Days), plant height, canopy area, stem number, flower number, aerial fresh yield, aerial dry matter (DM) yield, seed yield, essential oil percentage and oil production. The essential oil compositions were detected in accession 2929 (Tassoj) using GC/MS. Result of combined analysis of variance across two years showed significant differences between years, populations and population x year interaction for all traits (P < 0.01). In comparisons among populations, the population of Avaj and Ijroud with average values of 13.5 and 14.33 g/p had higher aerial dry yield and other agronomic traits followed by Meshkin2 and 3. For seed yield, Ormieh with average values of 3.11 g/p had higher production. For oil content, the populations of Tassoj, Salmas and Sharkord with average values of 1.25 to 1.56% had higher oil content and essential oil production. Result of correlation analysis showed that DM yield was positively correlated with GDD, plant height, canopy area, stem number, flower number. Oil content was negatively correlated with aerial DM yield. The results of PCA analysis showed that the first four components accounted for 50, 20, 12 and 10% of the total variation, respectively. Plant height, canopy area, stem number, flower number and aerial yield in the PCA1, essential oil content and oil production in the PCA2, seed yield in the PCA3 and GDD in PCA4 components were identified as important traits. Using Ward cluster method, the 21 populations were grouped into 3 clusters. In total, 23 compounds were identified in the essential oil from the aerial parts Z. tenuior. The major components in the essential oil were pulegone ranged (47.54 to 65.26%) followed by neo-iso-dihydro carveol, carvacrol, piperitenone, limonene, 1.8-cineole, p-mentha-3,8-dien, alpha-terpinene and terpinen-u-ol. It was concluded that there were wide range of variations for agronomic trait and essential oil in domestic germplasm of Z. tenuior to improved breeding new varieties in Iran.

Microtopography is a fundamental organizing structure of vegetation and soil chemistry in black ash wetlands

Abstract. All wetland ecosystems are controlled by water table and soil saturation dynamics, so any local-scale deviation in soil elevation and thus water table position represents variability in this primary control. Wetland microtopography is the structured variability in soil elevation and is typically categorized into a binary classification of local high points (hummocks) and local low points (hollows). Although the influence of microtopography on vegetation composition and biogeochemical processes in wetlands has received attention around the globe, its role in forested wetlands is still less understood. We studied relationships among microtopography and understory vegetation communities, tree biomass, and soil chemistry in 10 black ash (Fraxinus nigra Marshall) wetlands in northern Minnesota, USA. To do so, we combined a 1 cm resolution surface elevation model generated from terrestrial laser scanning (TLS) with colocated water table, vegetation, and soil measurements. We observed that microtopography was an important structural element across sites, where hummocks were loci of greater species richness; greater midstory and canopy basal area; and higher soil concentrations of chloride, phosphorus, and base cations. In contrast, hollows were associated with higher soil nitrate and sulfate concentrations. We also found that the effect of microtopography on vegetation and soils was greater at wetter sites than at drier sites, suggesting that the distance-to-mean water table is a primary determinant of wetland biogeochemistry. These findings highlight clear controls of microtopography on vegetation and soil distributions while also supporting the notion that microtopography arises from feedbacks that concentrate biomass, soil nutrients, and productivity on microsite highs, especially in otherwise wet conditions. We therefore conclude that microtopography is a fundamental organizing structure in black ash wetlands.

The Effects of Habitat Alteration on Anuran Diversity and Assemblages on Mount Mulanje, Malawi

Anthropogenic disturbance and increased environmental degradation often lead to losses in species diversity. As continuous forests become increasingly limited, it is important to determine conservation and biodiversity values of intact forests and surrounding landscapes. Currently, there is little data on how anuran communities react to the alarming growth of habitat degradation in tropical East Africa, nor on the value of remnant forests. This study evaluated the alpha, beta and gamma diversity of frogs in an altered landscape on Mount Mulanje, Malawi, East Africa, and assessed the impact of habitat degradation and diversity of a landscape matrix of various habitat types. Nine sites were sampled: three intact miombo forests, three eucalyptus plantations, and three secondary forests. Twenty-nine species were found throughout these landscapes. Intact miombo forests contained significantly more frog species than the other habitats. The degree of canopy cover and area size appeared to determine species diversity across all three landscapes. Although eucalyptus plantations were impoverished, naturally regenerating secondary forests can help relieve the effects of habitat alteration. Nevertheless, degraded habitats cannot substitute for continuous blocks of forest; therefore understanding these differences is crucial for maintaining the biodiversity value in the long term.