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Describing the heterogeneous structure of forests is often challenging.
One possibility is to analyze forest biomass in different plots and to derive plot-based frequency distributions.
However, these frequency distributions depend on the plot size and thus are scale dependent.
This study provides insights about transferring them between scales. Understanding the effects of scale on distributions of biomass is particularly important for comparing information from different sources such as inventories, remote sensing and modeling, all of which can operate at different spatial resolutions. Reliable methods to compare results of vegetation models at a grid scale with field data collected at smaller scales are still missing.
The scaling of biomass and variables, which determine the forest biomass, was investigated for a tropical forest in Panama. Based on field inventory data from Barro Colorado Island, spanning 50 ha over 30 years, the distributions of aboveground biomass, biomass gain and mortality were derived at different spatial resolutions, ranging from 10 to 100 m. Methods for fitting parametric distribution functions were compared.
Further, it was tested under which assumptions about the distributions a simple stochastic simulation forest model could best reproduce observed biomass distributions at all scales. Also, an analytical forest model for calculating biomass distributions at equilibrium and assuming mortality as a white shot noise process was tested.
Scaling exponents of about 0.47 were found for the standard deviations of the biomass and gain distributions, while mortality showed a different scaling relationship with an exponent of 0.3. Lognormal and gamma distribution functions fitted with the moment matching estimation method allowed for consistent parameter transfers between scales. Both forest models (stochastic simulation and analytical solution) were able to reproduce observed biomass distributions across scales, when combined with the derived scaling relationships.
The study demonstrates a way of how to approach the scaling problem in model-data comparisons by providing a transfer relationship. Further research is needed for a better understanding of the mechanisms that shape the frequency distributions at the different scales.
In nature, plants are constantly exposed to many transient, but recurring, stresses. Thus, to complete their life cycles, plants require a dynamic balance between capacities to recover following cessation of stress and maintenance of stress memory. Recently, we uncovered a new functional role for macroautophagy/autophagy in regulating recovery from heat stress (HS) and resetting cellular memory of HS inArabidopsis thaliana. Here, we demonstrated that NBR1 (next to BRCA1 gene 1) plays a crucial role as a receptor for selective autophagy during recovery from HS. Immunoblot analysis and confocal microscopy revealed that levels of the NBR1 protein, NBR1-labeled puncta, and NBR1 activity are all higher during the HS recovery phase than before. Co-immunoprecipitation analysis of proteins interacting with NBR1 and comparative proteomic analysis of annbr1-null mutant and wild-type plants identified 58 proteins as potential novel targets of NBR1. Cellular, biochemical and functional genetic studies confirmed that NBR1 interacts with HSP90.1 (heat shock protein 90.1) and ROF1 (rotamase FKBP 1), a member of the FKBP family, and mediates their degradation by autophagy, which represses the response to HS by attenuating the expression ofHSPgenes regulated by the HSFA2 transcription factor. Accordingly, loss-of-function mutation ofNBR1resulted in a stronger HS memory phenotype. Together, our results provide new insights into the mechanistic principles by which autophagy regulates plant response to recurrent HS.
Small temporary wetlands, like kettle holes, provide many valuable ecosystem functions and serve as refuge habitats in otherwise monotonous agricultural landscapes. However, the mechanisms that maintain biodiversity in these habitats are still poorly understood. In this study, we investigate how three taxa (vascular plants, ground beetles and spiders) respond to small-scale flooding and disturbance gradients in kettle holes as well as kettle hole area. For this purpose, we determined total, hygrophilic and red list species richness for all taxa and activity density for arthropods along transects extending from the edge towards the center of kettle holes. Furthermore, we calculated the community-weighted mean body size for arthropods and seed mass for plants as surrogates for the ability to respond to disturbance. Our analyses revealed that in particular plants and ground beetles showed strong responses along the small-scale spatial gradient. Total plant species richness decreased towards the center, while hygrophilic plant species increased. In contrast, both total and hygrophilic species richness of ground beetles increased towards the center. Spiders showed similar responses as ground beetles, but less pronounced. We found no evidence that disturbance at the edge of kettle holes leads to smaller body sizes or seed masses. However, arthropods in adjacent arable fields (one meter from the kettle hole edge) were particularly small. Kettle hole area had only weak effects on plants, but not on arthropods. Our study indicates that differences in the depth at the drier edge and the moist, regularly flooded center have a large and taxon-dependent influence on the species composition. Therefore, small-scale heterogeneity seems to be an important predictor for the maintenance of species diversity.
Large agricultural streams receive excessive inputs of nitrogen.
However, quantifying the role of these streams in nitrogen processing remains limited because continuous direct measurements of the interacting and highly time-varying nitrogen processing pathways in larger streams and rivers are very complex.
Therefore, we employed a monitoring-driven modelling approach with high-frequency in situ data and the river water quality model Water Quality Analysis Simulation Program (WASP) 7.5.2 in the 27.4 km reach of the sixth-order agricultural stream called Lower Bode (central Germany) for a 5-year period (2014-2018).
Paired high-frequency sensor data (15 min interval) of discharge, nitrate, dissolved oxygen, and chlorophyll a at upstream and downstream stations were used as model boundaries and for setting model constraints.
The WASP model simulated 15 min intervals of discharge, nitrate, and dissolved oxygen with Nash-Sutcliffe efficiency values higher than 0.9 for calibration and validation, enabling the calculation of gross and net dissolved inorganic nitrogen uptake and pathway rates on a daily, seasonal, and multiannual scale.
Results showed daily net uptake rate of dissolved inorganic nitrogen ranged from -17.4 to 553.9 mgNm(-2)d(-1). The highest daily net uptake could reach almost 30 % of the total input loading, which occurred at extreme low flow in summer 2018.
The growing season (spring and summer) accounted for 91 % of the average net annual uptake of dissolved inorganic nitrogen in the measured period. In spring, both the DIN gross and net uptake were dominated by the phytoplankton uptake pathway. In summer, benthic algae assimilation dominated the gross uptake of dissolved inorganic nitrogen.
Conversely, the reach became a net source of dissolved inorganic nitrogen with negative daily net uptake values in autumn and winter, mainly because the release from benthic algae surpassed uptake processes.
Over the 5 years, average gross and net uptake rates of dissolved inorganic nitrogen were 124.1 and 56.8 mgNm(-2)d(-1), which accounted for only 2.7 % and 1.2 % of the total loadings in the Lower Bode, respectively. The 5-year average gross DIN uptake decreased from assimilation by benthic algae through assimilation by phytoplankton to denitrification.
Our study highlights the value of combining river water quality modelling with high-frequency data to obtain a reliable budget of instream dissolved inorganic nitrogen processing which facilitates our ability to manage nitrogen in aquatic systems.
This study provides a methodology that can be applied to any large stream to quantify nitrogen processing pathway dynamics and complete our understanding of nitrogen cycling.
Soil microbial communities are crucial for plant growth and are already depleted by anthropogenic activities.
The application of microbial transplants provides a strategy to restore beneficial soil traits, but less is known about the microbiota of traditional inoculants used in biodynamic agriculture.
In this study, we used amplicon sequencing and quantitative PCR to decipher microbial communities of composts, biodynamic manures, and plant preparations from Austria and France.
In addition, we investigated the effect of extracts derived from biodynamic manure and compost on the rhizosphere microbiome of apple trees. Microbiota abundance, composition, and diversity of biodynamic manures, plant preparations, and composts were distinct. Microbial abundances ranged between 1010-1011 (bacterial 16S rRNA genes) and 109-1011 (fungal ITS genes). The bacterial diversity was significantly higher in biodynamic manures compared to compost without discernible differences in abundance. Fungal diversity was not significantly different while abundance was increased in biodynamic manures. The microbial communities of biodynamic manures and plant preparations were specific for each production site, but all contain potentially plant-beneficial bacterial genera.
When applied in apple orchards, biodynamic preparations (extracts) had the non-significant effect of reducing bacterial and fungal abundance in apple rhizosphere (4 months post-application), while increasing fungal and lowering bacterial Shannon diversity.
One to four months after inoculation, individual taxa indicated differential abundance. We observed the reduction of the pathogenic fungus Alternaria, and the enrichment of potentially beneficial bacterial genera such as Pseudomonas.
Our study paves way for the science-based adaptation of empirically developed biodynamic formulations under different farming practices to restore the vitality of agricultural soils.
Plant cell walls are versatile materials that can adopt a wide range of mechanical properties through controlled deposition of cellulose fibrils. Wall integrity requires a sufficiently homogeneous fibril distribution to cope effectively with wall stresses. Additionally, specific conditions, such as the negative pressure in water transporting xylem vessels, may require more complex wall patterns, e.g., bands in protoxylem.
The orientation and patterning of cellulose fibrils are guided by dynamic cortical microtubules.
New microtubules are predominantly nucleated from parent microtubules causing positive feedback on local microtubule density with the potential to yield highly inhomogeneous patterns. Inhomogeneity indeed appears in all current cortical array simulations that include microtubule-based nucleation, suggesting that plant cells must possess an as-yet unknown balancing mechanism to prevent it.
Here, in a combined simulation and experimental approach, we show that a limited local recruitment of nucleation complexes to microtubules can counter the positive feedback, whereas local tubulin depletion cannot.
We observe that nucleation complexes preferentially appear at the plasma membrane near microtubules. By incorporating our experimental findings in stochastic simulations, we find that the spatial behavior of nucleation complexes delicately balances the positive feedback, such that differences in local microtubule dynamics-as in developing protoxylem-can quickly turn a homogeneous array into a banded one. Our results provide insight into how the plant cytoskeleton has evolved to meet diverse mechanical requirements and greatly increase the predictive power of computational cell biology studies.
During a survey of aquatic fungi from Anzali Lagoon in Iran, several fungal specimens were isolated from freshwater habitats. Morphological evidence and comparing sequencing based on rDNA (ITS and LSU) and protein-coding genes (TEF1 and TUB2) showed that some isolates belong to undescribed fungal species.
These isolates belong to Arthrobotrys and Sarocladium, two ascomycetes genera. Arthrobotrys hyrcanus, sp. nov., differs from closely related species such as A. dianchiensis by its larger conidia and septation of primary conidia. Sarocladium pseudokiliense, sp. nov., was similar to S. kiliense, but distinguished by its conidial shape and the absence of adelophialides and chlamydospores.
Morphological descriptions, illustrations and multilocus phylogenetic analysis for both new species are provided.
The inclusion of exotic germplasm serves as a crucial means to enhance allelic and
consequently phenotypic diversity in inbred crop species. Such species have experienced a reduction in diversity due to artificial selection focused on a limited set of traits. The natural biodiversity within ecosystems presents an opportunity to explore various traits influencing plant survival, reproductive fitness and yield potential. In agricultural research, the study of wild species closely related to cultivated plants serves as a means to comprehend the genetic foundations of past domestication events and the polymorphisms essential for future breeding efforts to develop superior varieties. In order to examine the metabolic composition, pinpoint quantitative trait loci (QTL) and facilitate their resolution an extensive large-scale analysis of metabolic QTL (mQTL) was conducted on tomato backcross inbred lines (BILs) derived from a cross between the wild species S. pennellii (5240) incorporated into the background of S. lycopersicum cv. LEA determinate inbred which can be grown in open fields and cv. TOP indeterminate which can be grown in greenhouse conditions. A large number of mQTL associated with primary secondary and lipid metabolism in fruit were identified across the two BIL populations. Epistasis, the interactions between genes at different loci, has been an interest in molecular and quantitative genetics for many decades. The study of epistasis requires the analysis of very large populations with multiple independent genotypes that carry specific genomic regions. In order to understand the genetic basis of tomato fruit metabolism, I extended the work to investigate epistatic interactions of the genomic regions. In addition, two candidate genes were identified through quantitative trait loci underlying fruit-specific sucrose and jasmonic acid derivatives. Finally, in this study, I assessed the genetic framework of fruit metabolic traits with a high level of detail, utilizing the newly created Solanum pennellii (5240) backcrossed introgression lines (n=3000). This investigation resulted in the discovery of promising candidate loci associated with significant fruit quality traits, including those to the abundance of glutamic acid and aspartic acid crucial elements contributing to the development of acidity and flavors.
Moderate and temporary heat stresses prime plants to tolerate, and survive, a subsequent severe heat stress. Such acquired thermotolerance can be maintained for several days under normal growth conditions, and can create a heat stress memory. We recently demonstrated that plastid-localized small heat shock protein 21 ( HSP21) is a key component of heat stress memory in Arabidopsis thaliana. A sustained high abundance of HSP21 during the heat stress recovery phase extends heat stress memory. The level of HSP21 is negatively controlled by plastid-localized metalloprotease FtsH6 during heat stress recovery. Here, we demonstrate that autophagy, a cellular recycling mechanism, exerts additional control over HSP21 degradation. Genetic and chemical disruption of both metalloprotease activity and autophagy trigger superior HSP21 accumulation, thereby improving memory. Furthermore, we provide evidence that autophagy cargo receptor ATG8-INTERACTING PROTEIN1 (ATI1) is associated with heat stress memory. ATI1 bodies co-localize with both autophagosomes and HSP21, and their abundance and transport to the vacuole increase during heat stress recovery. Together, our results provide new insights into the module for control of the regulation of heat stress memory, in which two distinct protein degradation pathways act in concert to degrade HSP21, thereby enabling cells to recover from the heat stress effect at the cost of reducing the heat stress memory.
Quantifying root water uptake is essential to understanding plant water use and responses to different environmental conditions. However, non-destructive measurement of water transport and related hydraulics in the soil-root system remains a challenge.
Neutron imaging, with its high sensitivity to hydrogen, has become an unparalleled tool to visualize and quantify root water uptake in vivo. In combination with isotopes (e.g., deuterated water) and a diffusion-convection model, root water uptake and hydraulic redistribution in root and soil can be quantified.
Here, we review recent advances in utilizing neutron imaging to visualize and quantify root water uptake, hydraulic redistribution in roots and soil, and root hydraulic properties of different plant species.
Under uniform soil moisture distributions, neutron radiographic studies have shown that water uptake was not uniform along the root and depended on both root type and age. For both tap (e.g., lupine [Lupinus albus L.]) and fibrous (e.g., maize [Zea mays L.]) root systems, water was mainly taken up through lateral roots. In mature maize, the location of water uptake shifted from seminal roots and their laterals to crown/nodal roots and their laterals.
Under non-uniform soil moisture distributions, part of the water taken up during the daytime maintained the growth of crown/nodal roots in the upper, drier soil layers. Ultra-fast neutron tomography provides new insights into 3D water movement in soil and roots. We discuss the limitations of using neutron imaging and propose future directions to utilize neutron imaging to advance our understanding of root water uptake and soil-root interactions.