Refine
Year of publication
Document Type
- Article (3398) (remove)
Language
- English (3398) (remove)
Is part of the Bibliography
- yes (3398)
Keywords
- Arabidopsis thaliana (40)
- climate change (28)
- Arabidopsis (25)
- ancient DNA (20)
- biodiversity (19)
- Dictyostelium (16)
- functional traits (16)
- Climate change (14)
- animal personality (14)
- competition (14)
Institute
- Institut für Biochemie und Biologie (3398) (remove)
Pre-exposing (priming) plants to mild, non-lethal elevated temperature improves their tolerance to a later higher-temperature stress (triggering stimulus), which is of great ecological importance. 'Thermomemory' is maintaining this tolerance for an extended period of time. NAM/ATAF1/2/ CUC2 (NAC) proteins are plant-specific transcription factors (TFs) that modulate responses to abiotic stresses, including heat stress (HS). Here, we investigated the potential role of NACs for thermomemory. We determined the expression of 104 Ara bidopsis NAC genes after priming and triggering heat stimuli, and found ATAF1 expression is strongly induced right after priming and declines below control levels thereafter during thermorecovery. Knockout mutants of ATAF1 show better thermomemory than wild type, revealing a negative regulatory role. Differential expression analyses of RNA-seq data from ATAF1 overexpressor, ataf1 mutant and wild-type plants after heat priming revealed five genes that might be priming-associated direct targets of ATAF1: AT2G31260 (ATG9), AT2G41640 (GT61), AT3G44990 (XTH31), AT4G27720 and AT3G23540. Based on co-expression analyses applied to the aforementioned RNA-seq profiles, we identified ANAC055 to be transcriptionally co-regulated with ATAF1. Like atafl, anac055 mutants show improved thermomemory, revealing a potential co-control of both NACTFs over thermomemory. Our data reveals a core importance of two NAC transcription factors, ATAF1 and ANAC055, for thermomemory.
PRI: Re-analysis of a public mass cytometry dataset reveals patterns of effective tumor treatments
(2022)
Recently, mass cytometry has enabled quantification of up to 50 parameters for millions of cells per sample. It remains a challenge to analyze such high-dimensional data to exploit the richness of the inherent information, even though many valuable new analysis tools have already been developed. We propose a novel algorithm "pattern recognition of immune cells (PRI)" to tackle these high-dimensional protein combinations in the data. PRI is a tool for the analysis and visualization of cytometry data based on a three or more-parametric binning approach, feature engineering of bin properties of multivariate cell data, and a pseudo-multiparametric visualization. Using a publicly available mass cytometry dataset, we proved that reproducible feature engineering and intuitive understanding of the generated bin plots are helpful hallmarks for re-analysis with PRI. In the CD4(+)T cell population analyzed, PRI revealed two bin-plot patterns (CD90/CD44/CD86 and CD90/CD44/CD27) and 20 bin plot features for threshold-independent classification of mice concerning ineffective and effective tumor treatment. In addition, PRI mapped cell subsets regarding co-expression of the proliferation marker Ki67 with two major transcription factors and further delineated a specific Th1 cell subset. All these results demonstrate the added insights that can be obtained using the non-cluster-based tool PRI for re-analyses of high-dimensional cytometric data.
The terrestrial ecosystem in the Yellow River Source Area (YRSA) is sensitive to climate change and human impacts, although past vegetation change and the degree of human disturbance are still largely unknown. A 170-cm-long sediment core covering the last 7,400 years was collected from Lake Xingxinghai (XXH) in the YRSA. Pollen, together with a series of other environmental proxies (including grain size, total organic carbon (TOC) and carbonate content), were analysed to explore past vegetation and environmental changes for the YRSA. Dominant and common pollen components-Cyperaceae, Poaceae, Artemisia, Chenopodiaceae and Asteraceae-are stable throughout the last 7,400 years. Slight vegetation change is inferred from an increasing trend of Cyperaceae and decreasing trend of Poaceae, suggesting that alpine steppe was replaced by alpine meadow at ca. 3.5 ka cal bp. The vegetation transformation indicates a generally wetter climate during the middle and late Holocene, which is supported by increased amounts of TOC and Pediastrum (representing high water-level) and is consistent with previous past climate records from the north-eastern Tibetan Plateau. Our results find no evidence of human impact on the regional vegetation surrounding XXH, hence we conclude the vegetation change likely reflects the regional climate signal.
Wildfires play an essential role in the ecology of boreal forests.
In eastern Siberia, fire activity has been increasing in recent years, challenging the livelihoods of local communities. Intensifying fire regimes also increase disturbance pressure on the boreal forests, which currently protect the permafrost beneath from accelerated degradation.
However, long-term relationships between changes in fire regime and forest structure remain largely unknown.
We assess past fire-vegetation feedbacks using sedimentary proxy records from Lake Satagay, Central Yakutia, Siberia, covering the past c. 10,800 years.
Results from macroscopic and microscopic charcoal analyses indicate high amounts of burnt biomass during the Early Holocene, and that the present-day, low-severity surface fire regime has been in place since c. 4,500 years before present.
A pollen-based quantitative reconstruction of vegetation cover and a terrestrial plant record based on sedimentary ancient DNA metabarcoding suggest a pronounced shift in forest structure toward the Late Holocene.
Whereas the Early Holocene was characterized by postglacial open larch-birch woodlands, forest structure changed toward the modern, mixed larch-dominated closed-canopy forest during the Mid-Holocene.
We propose a potential relationship between open woodlands and high amounts of burnt biomass, as well as a mediating effect of dense larch forest on the climate-driven intensification of fire regimes.
Considering the anticipated increase in forest disturbances (droughts, insect invasions, and wildfires), higher tree mortality may force the modern state of the forest to shift toward an open woodland state comparable to the Early Holocene.
Such a shift in forest structure may result in a positive feedback on currently intensifying wildfires.
These new long-term data improve our understanding of millennial-scale fire regime changes and their relationships to changes of vegetation in Central Yakutia, where the local population is already being confronted with intensifying wildfire seasons.
Hantaviruses are enveloped viruses that possess a tri-segmented, negative-sense RNA genome.
The viral S-segment encodes the multifunctional nucleocapsid protein (N), which is involved in genome packaging, intracellular protein transport, immunoregulation, and several other crucial processes during hantavirus infection.
In this study, we generated fluorescently tagged N protein constructs derived from Puumalavirus (PUUV), the dominant hantavirus species in Central, Northern, and Eastern Europe.
We comprehensively characterized this protein in the rodent cell line CHO-K1, monitoring the dynamics of N protein complex formation and investigating co-localization with host proteins as well as the viral glycoproteins Gc and Gn.
We observed formation of large, fibrillar PUUV N protein aggregates, rapidly coalescing from early punctate and spike-like assemblies.
Moreover, we found significant spatial correlation of N with vimentin, actin, and P-bodies but not with microtubules. N constructs also co-localized with Gn and Gc albeit not as strongly as the glycoproteins associated with each other.
Finally, we assessed oligomerization of N constructs, observing efficient and concentration-dependent multimerization, with complexes comprising more than 10 individual proteins.
Assessing the risk of yield loss in African drought-affected regions is key to identify feasible solutions for stable crop production. Recent studies have demonstrated that Copula-based probabilistic methods are well suited for such assessment owing to reasonably inferring important properties in terms of exceedance probability and joint dependence of different characterization. However, insufficient attention has been given to quantifying the probability of yield loss and determining the contribution of climatic factors. This study applies the Copula theory to describe the dependence between drought and crop yield anomalies for rainfed maize, millet, and sorghum crops in sub-Saharan Africa (SSA). The environmental policy integrated climate model, calibrated with Food and Agriculture Organization country-level yield data, was used to simulate yields across SSA (1980-2012). The results showed that the severity of yield loss due to drought had a higher magnitude than the severity of drought itself. Sensitivity analysis to identify factors contributing to drought and high-temperature stresses for all crops showed that the amount of precipitation during vegetation and grain filling was the main driver of crop yield loss, and the effect of temperature was stronger for sorghum than for maize and millet. The results demonstrate the added value of probabilistic methods for drought-impact assessment. For future studies, we recommend looking into factors influencing drought and high-temperature stresses as individual/concurrent climatic extremes.
Uncertainty in climate change impact studies for irrigated maize cropping systems in southern Spain
(2022)
This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability.
Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields.
The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014-2017).
By considering combinations of allocation strategies, the adjusted R-2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%).
However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses.
Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.
The contribution of dead zooplankton biomass to carbon cycle in aquatic ecosystems is practically unknown. Using abundance data of zooplankton in water column and dead zooplankton in sediment traps in Lake Stechlin, an ecological-mathematical model was developed to simulate the abundance and sinking of zooplankton carcasses and predict the related release of labile organic matter (LOM) into the water column. We found species-specific differences in mortality rate of the dominant zooplankton: Daphnia cucullata, Bosmina coregoni and Diaphanosoma brachyurum (0.008, 0.129 and 0.020 day(-1), respectively) and differences in their carcass sinking velocities in metalimnion (and hypolimnion): 2.1 (7.64), 14.0 (19.5) and 1.1 (5.9) m day(-1), respectively. Our model simulating formation and degradation processes of dead zooplankton predicted a bimodal distribution of the released LOM: epilimnic and metalimnic peaks of comparable intensity, ca. 1 mg DW m(-3) day(-1). Maximum degradation of carcasses up to ca. 1.7 mg DW m(-3) day(-1) occurred in the density gradient zone of metalimnion. LOM released from zooplankton carcasses into the surrounding water may stimulate microbial activity and facilitate microbial degradation of more refractory organic matter; therefore, dead zooplankton are expected to be an integral part of water column carbon source/sink dynamics in stratified lakes.
A bacterial effector counteracts host autophagy by promoting degradation of an autophagy component
(2022)
Beyond its role in cellular homeostasis, autophagy plays anti- and promicrobial roles in host-microbe interactions, both in animals and plants.
One prominent role of antimicrobial autophagy is to degrade intracellular pathogens or microbial molecules, in a process termed xenophagy.
Consequently, microbes evolved mechanisms to hijack or modulate autophagy to escape elimination.
Although well-described in animals, the extent to which xenophagy contributes to plant-bacteria interactions remains unknown.
Here, we provide evidence that Xanthomonas campestris pv. vesicatoria (Xcv) suppresses host autophagy by utilizing type-III effector XopL. XopL interacts with and degrades the autophagy component SH3P2 via its E3 ligase activity to promote infection.
Intriguingly, XopL is targeted for degradation by defense-related selective autophagy mediated by NBR1/Joka2, revealing a complex antagonistic interplay between XopL and the host autophagy machinery.
Our results implicate plant antimicrobial autophagy in the depletion of a bacterial virulence factor and unravel an unprecedented pathogen strategy to counteract defense-related autophagy in plant-bacteria interactions.
Etmopteridae (lantern sharks) is the most species-rich family of sharks, comprising more than 50 species.
Many species are described from few individuals, and re-collection of specimens is often hindered by the remoteness of their sampling sites.
For taxonomic studies, comparative morphological analysis of type specimens housed in natural history collections has been the main source of evidence.
In contrast, DNA sequence information has rarely been used.
Most lantern shark collection specimens, including the types, were formalin fixed before long-term storage in ethanol solutions.
The DNA damage caused by both fixation and preservation of specimens has excluded these specimens from DNA sequence-based phylogenetic analyses so far.
However, recent advances in the field of ancient DNA have allowed recovery of wet-collection specimen DNA sequence data.
Here we analyse archival mitochondrial DNA sequences, obtained using ancient DNA approaches, of two wet-collection lantern shark paratype specimens, namely Etmopterus litvinovi and E. pycnolepis, for which the type series represent the only known individuals.
Target capture of mitochondrial markers from single-stranded DNA libraries allows for phylogenetic placement of both species.
Our results suggest synonymy of E. benchleyi with E. litvinovi but support the species status of E. pycnolepis. This revised taxonomy is helpful for future conservation and management efforts, as our results indicate a larger distribution range of E. litvinovi. This study further demonstrates the importance of wet-collection type specimens as genetic resource for taxonomic research.
Air chemistry is affected by the emission of biogenic volatile organic compounds (BVOCs), which originate from almost all plants in varying qualities and quantities. They also vary widely among different crops, an aspect that has been largely neglected in emission inventories. In particular, bioenergy-related species can emit mixtures of highly reactive compounds that have received little attention so far. For such species, long-term field observations of BVOC exchange from relevant crops covering different phenological phases are scarcely available. Therefore, we measured and modeled the emission of three prominent European bioenergy crops (maize, ryegrass, and oil-seed rape) for full rotations in north-eastern Germany. Using a proton transfer reaction-mass spectrometer combined with automatically moving large canopy chambers, we were able to quantify the characteristic seasonal BVOC flux dynamics of each crop species. The measured BVOC fluxes were used to parameterize and evaluate the BVOC emission module (JJv) of the physiology-oriented LandscapeDNDC model, which was enhanced to cover de novo emissions as well as those from plant storage pools. Parameters are defined for each compound individually. The model is used for simulating total compound-specific reactivity over several years and also to evaluate the importance of these emissions for air chemistry. We can demonstrate substantial differences between the investigated crops with oil-seed rape having 37-fold higher total annual emissions than maize. However, due to a higher chemical reactivity of the emitted blend in maize, potential impacts on atmospheric OH-chemistry are only 6-fold higher.
Leaf area index (LAI) is a key variable in understanding and modeling crop-environment interactions.
With the advent of increasingly higher spatial resolution satellites and sensors mounted on remotely piloted aircrafts (RPAs), the use of remote sensing in precision agriculture is becoming more common.
Since also the availability of methods to retrieve LAI from image data have also drastically expanded, it is necessary to test simultaneously as many methods as possible to understand the advantages and disadvantages of each approach.
Ground-based LAI data from three years of barley experiments were related to remote sensing information using vegetation indices (VI), machine learning (ML) and radiative transfer models (RTM), to assess the relative accuracy and efficacy of these methods.
The optimized soil adjusted vegetation index and a modified version of the Weighted Difference Vegetation Index performed slightly better than any other retrieval method. However, all methods yielded coefficients of determination of around 0.7 to 0.9.
The best performing machine learning algorithms achieved higher accuracies when four Sentinel-2 bands instead of 12 were used.
Also, the good performance of VIs and the satisfactory performance of the 4-band RTM, strongly support the synergistic use of satellites and RPAs in precision agriculture. One of the methods used, Sen2-Agri, an open source ML-RTM-based operational system, was also able to accurately retrieve LAI, although it is restricted to Sentinel-2 and Landsat data.
This study shows the benefits of testing simultaneously a broad range of retrieval methods to monitor crops for precision agriculture.
After initial detection of target archival DNA of a 116-year-old syntype specimen of the smooth lantern shark, Etmopterus pusillus, in a single-stranded DNA library, we shotgun-sequenced additional 9 million reads from this same DNA library. Sequencing reads were used for extracting mitochondrial sequence information for analyses of mitochondrial DNA characteristics and reconstruction of the mitochondrial genome. The archival DNA is highly fragmented. A total of 4599 mitochondrial reads were available for the genome reconstruction using an iterative mapping approach. The resulting genome sequence has 12 times coverage and a length of 16 741 bp. All 37 vertebrate mitochondrial loci plus the control region were identified and annotated. The mitochondrial NADH2 gene was subsequently used to place the syntype haplotype in a network comprising multiple E. pusillus samples from various distant localities as well as sequences from a morphological similar species, the shortfin smooth lantern shark Etmopterus joungi. Results confirm the almost global distribution of E. pusillus and suggest E. joungi to be a junior synonym of E. pusillus. As mitochondrial DNA often represents the only available reference information in non-model organisms, this study illustrates the importance of mitochondrial DNA from an aged, wet collection type specimen for taxonomy.
This paper presents two new pollen records and quantitative climate reconstructions from northern Chukotka documenting environmental changes over the last 27.9 ka. Open tundra- and steppe-like habitats dominated between 27.9 and 18.7 cal. ka BP. Betula and Alnus shrubs might have grown in sheltered microhabitats but disappeared after 18.7 cal. ka BP. Although the climate was rather harsh, local herb-dominated communities supported herbivores as is evident by the presence of coprophilous spores in the sediments. The increase in Salix and Cyperaceae similar to 16.1 cal. ka BP suggests climate amelioration. Shrub Betula appeared similar to 15.9 cal. ka BP, and became dominant after similar to 15.52 cal. ka BP, whilst typical steppe communities drastically reduced. Very high presence of Botryococcus in the Lateglacial sediments reflects widespread shallow habitats, probably due to lake level increase. Shrub Alnus became common after similar to 13 cal. ka BP reflecting further climate amelioration. Simultaneously, herb communities gradually decreased in the vegetation reaching a minimum similar to 11.8 cal. ka BP. A gradual decrease of algae remains suggests a reduction of shallow-water habitats. Shrubby and graminoid tundra was dominant similar to 11.8-11.1 cal. ka BP, later Salix stands significantly decreased. The forest-tundra ecotone established in the Early Holocene, shortly after 11.1 cal. ka BP. Low contents of green algae in the Early Holocene sediments likely reflect deeper aquatic conditions. The most favourable climate conditions were between similar to 10.6 and 7 cal. ka BP. Vegetation became similar to the modern after similar to 7 cal. ka BP but Pinus pumila came to the Ilirney area at about 1.2 cal. ka BP. It is important to emphasize that the study area provided refugia for Betula and Alnus during MIS 2. It is also notable that our records do not reflect evidence of Younger Dryas cooling, which is inconsistent with some regional environmental records but in good accordance with some others.
The nature of the interaction between prehistoric humans and their environment, especially the vegetation, has long been of interest. The Qinghai Lake Basin in North China is well-suited to exploring the interactions between prehistoric humans and vegetation in the Tibetan Plateau, because of the comparatively dense distribution of archaeological sites and the ecologically fragile environment. Previous pollen studies of Qinghai Lake have enabled a detailed reconstruction of the regional vegetation, but they have provided relatively little information on vegetation change within the Qinghai Lake watershed. To address the issue we conducted a pollen-based vegetation reconstruction for an archaeological site (YWY), located on the southern shore of Qinghai Lake. We used high temporal-resolution pollen records from the YWY site and from Qinghai Lake, spanning the interval since the last deglaciation (15.3 kyr BP to the present) to quantitatively reconstruct changes in the local and regional vegetation using Landscape Reconstruction Algorithm models. The results show that, since the late glacial, spruce forest grew at high altitudes in the surrounding mountains, while the lakeshore environment was occupied mainly by shrub-steppe. From the lateglacial to the middle Holocene, coniferous woodland began to expand downslope and reached the YWY site at 7.1 kyr BP. The living environment of the local small groups of Paleolithic-Epipaleolithic humans (during 15.3-13.1 kyr BP and 9-6.4 kyr BP) changed from shrub-steppe to coniferous forest-steppe. The pollen record shows no evidence of pronounced changes in the vegetation community corresponding to human activity. However, based on a comparison of the local and regional vegetation reconstructions, low values of biodiversity and a significant increase in two indicators of vegetation degradation, Chenopodiaceae and Rosaceae, suggest that prehistoric hunters-gatherers likely disturbed the local vegetation during 9.0-6.4 kyr BP. Our findings are a preliminary attempt to study human-environment interactions at Paleolithic-Epipaleolithic sites in the region, and they contribute to ongoing environmental archaeology research in the Tibetan Plateau.
Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems
(2022)
Biodiversity in urban ecosystems has the potential to increase ecosystem functions and support a suite of services valued by society, including services provided by soils. Specifically, the sequestration of carbon in soils has often been advocated as a solution to mitigate the steady increase in CO2 concentration in the atmosphere as a key driver of climate change. However, urban ecosystems are also characterized by an often high level of ecological novelty due to profound human-mediated changes, such as the presence of high numbers of non-native species, impervious surfaces or other disturbances. Yet it is poorly understood whether and how biodiversity affects ecosystem functioning and services of urban soils under these novel conditions. In this study, we assessed the influence of above- and below-ground diversity, as well as urbanization and plant invasions, on multifunctionality and organic carbon stocks of soils in non-manipulated grasslands along an urbanization gradient in Berlin, Germany. We focused on plant diversity (measured as species richness and functional trait diversity) and, in addition, on soil organism diversity as a potential mediator for the relationship of plant species diversity and ecosystem functioning. Our results showed positive effects of plant diversity on soil multifunctionality and soil organic carbon stocks along the entire gradient. Structural equation models revealed that plant diversity enhanced soil multifunctionality and soil organic carbon by increasing the diversity of below-ground organisms. These positive effects of plant diversity on soil multifunctionality and soil fauna were not restricted to native plant species only, but were also exerted by non-native species, although to a lesser degree. Synthesis. We conclude that enhancing diversity in plants and soil fauna of urban grasslands can increase the multifunctionality of urban soils and also add to their often underestimated but very valuable role in mitigating effects of climate change.
Local biodiversity patterns are expected to strongly reflect variation in topography, land use, dispersal boundaries, nutrient supplies, contaminant spread, management practices, and other anthropogenic influences. Contrary to this expectation, studies focusing on specific taxa revealed a biodiversity homogenization effect in areas subjected to long-term intensive industrial agriculture. We investigated whether land use affects biodiversity levels and community composition (alpha- and beta-diversity) in 67 kettle holes (KH) representing small aquatic islands embedded in the patchwork matrix of a largely agricultural landscape comprising grassland, forest, and arable fields. These KH, similar to millions of standing water bodies of glacial origin, spread across northern Europe, Asia, and North America, are physico-chemically diverse and differ in the degree of coupling with their surroundings. We assessed aquatic and sediment biodiversity patterns of eukaryotes, Bacteria, and Archaea in relation to environmental features of the KH, using deep-amplicon-sequencing of environmental DNA (eDNA). First, we asked whether deep sequencing of eDNA provides a representative picture of KH aquatic biodiversity across the Bacteria, Archaea, and eukaryotes. Second, we investigated if and to what extent KH biodiversity is influenced by the surrounding land use. We hypothesized that richness and community composition will greatly differ in KH from agricultural land use compared with KH in grasslands and forests. Our data show that deep eDNA amplicon sequencing is useful for in-depth assessments of cross-domain biodiversity comprising both micro- and macro-organisms, but has limitations with respect to single-taxa conservation studies. Using this broad method, we show that sediment eDNA, integrating several years to decades, depicts the history of agricultural land-use intensification. Aquatic biodiversity was best explained by seasonality, whereas land-use type explained little of the variation. We concluded that, counter to our hypothesis, land use intensification coupled with landscape wide nutrient enrichment (including atmospheric deposition), groundwater connectivity between KH and organismal (active and passive) dispersal in the tight network of ponds, resulted in a biodiversity homogenization in the KH water, leveling off today's detectable differences in KH biodiversity between land-use types. These findings have profound implications for measures and management strategies to combat current biodiversity loss in agricultural landscapes worldwide.
Trophic transfer efficiency (TTE) is usually calculated as the ratio of production rates between two consecutive trophic levels. Although seemingly simple, TTE estimates from lakes are rare. In our review, we explore the processes and structures that must be understood for a proper lake TTE estimate.
We briefly discuss measurements of production rates and trophic positions and mention how ecological efficiencies, nutrients (N, P) and other compounds (fatty acids) affect energy transfer between trophic levels and hence TTE.
Furthermore, we elucidate how TTE estimates are linked with size-based approaches according to the Metabolic Theory of Ecology, and how food-web models can be applied to study TTE in lakes.
Subsequently, we explore temporal and spatial heterogeneity of production and TTE in lakes, with a particular focus on the links between benthic and pelagic habitats and between the lake and the terrestrial environment.
We provide an overview of TTE estimates from lakes found in the published literature. Finally, we present two alternative approaches to estimating TTE. First, TTE can be seen as a mechanistic quantity informing about the energy and matter flow between producer and consumer groups.
This approach is informative with respect to food-web structure, but requires enormous amounts of data. The greatest uncertainty comes from the proper consideration of basal production to estimate TTE of omnivorous organisms.
An alternative approach is estimating food-chain and food-web efficiencies, by comparing the heterotrophic production of single consumer levels or the total sum of all heterotrophic production including that of heterotrophic bacteria to the total sum of primary production.
We close the review by pointing to a few research questions that would benefit from more frequent and standardized estimates of TTE in lakes.
How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture?
(2022)
While ensuring food security worldwide, irrigation is altering the water cycle and generating numerous environmental side effects. As detailed knowledge about the timing and the amounts of water used for irrigation over large areas is still lacking, remotely sensed soil moisture has proved potential to fill this gap.
However, the spatial resolution and revisit time of current satellite products represent a major limitation to accurately estimating irrigation. This work aims to systematically quantify their impact on the retrieved irrigation information, hence assessing the value of satellite soil moisture for estimating irrigation timing and water amounts.
In a real-world experiment, we modeled soil moisture using actual irrigation and meteorological data, obtained from farmers and weather stations, respectively. Modeled soil moisture was compared against various remotely sensed products differing in terms of spatio-temporal resolution to test the hypothesis that high-resolution observations can disclose the irrigation signal from individual fields while coarse-scale satellite products cannot.
Then, in a synthetic experiment, we systematically investigated the effect of soil moisture spatial and temporal resolution on the accuracy of irrigation estimates. The analysis was further elaborated by considering different irrigation scenarios and by adding realistic amounts of random errors in the soil moisture time series.
We show that coarse-scale remotely sensed soil moisture products achieve higher correlations with rainfed simulations, while high-resolution satellite observations agree significantly better with irrigated simulations, suggesting that high-resolution satellite soil moisture can inform on field-scale (similar to 40 ha) irrigation. A thorough analysis of the synthetic dataset showed that satisfactory results, both in terms of detection (F-score > 0.8) and quantification (Pearson's correlation > 0.8), are found for noise-free soil moisture observations either with a temporal sampling up to 3 days or if at least one-third of the pixel covers the irrigated field(s).
However, irrigation water amounts are systematically underestimated for temporal samplings of more than one day, and decrease proportionally to the spatial resolution, i.e., coarsening the pixel size leads to larger irrigation underestimations.
Although lower spatial and temporal resolutions decrease the detection and quantification accuracies (e.g., R between 0.6 and 1 depending on the irrigation rate and spatio-temporal resolution), random errors in the soil moisture time series have a stronger negative impact (Pearson R always smaller than 0.85).
As expected, better performances are found for higher irrigation rates, i.e. when more water is supplied during an irrigation event. Despite the potentially large underestimations, our results suggest that high-resolution satellite soil moisture has the potential to track and quantify irrigation, especially over regions where large volumes of irrigation water are applied to the fields, and given that low errors affect the soil moisture observations.