Abstract
In July 2021, parts of Germany and Belgium were hit by severe floods. In ‘The central role of forests in the 2021 European floods’, published in
Environmental Research Letters
(2022
Environ. ...Res. Lett.
17
064053), Insua-Costa
et al
reported that ‘moisture from North American forests was a more important source of the rainfall contributing to the event than evaporation over nearby seas’. This suggests that the event was (partly) caused by anomalous contributions from North America. In this comment, we show that this is a misleading interpretation, as: (1) the relative contribution of North American land was below average for the time of year; and (2) rather, the anomalous moisture that contributed to the floods originated mainly from European land. However, consistent with Insua-Costa
et al
, we find no enhanced evaporation from Europe prior to the event and we therefore conclude that there is a lack of evidence for the ‘central role’ of forests in the 2021 European floods.
Abstract
The southeastern Amazon has recently been shown to be a net carbon source, which is partly caused by drying conditions. Drying depends on a number of factors, one of which is the land cover ...at the locations where the moisture has originated as evaporation. Here we assess for the first time the origins of the moisture that precipitates in the Amazon carbon source region, using output from a Lagrangian atmospheric moisture tracking model. We relate vegetation productivity in the Amazon carbon source region to precipitation patterns and derive land-cover data at the moisture origins of these areas, allowing us to estimate how the carbon cycle and hydrological cycle are linked in this critical part of the Amazon. We find that, annually, 13% of the precipitation in the Amazon carbon source region has evaporated from that same area, which is half of its land-derived moisture. We further find a moisture-recycling-mediated increase in gross primary productivity of roughly 41 Mg carbon km
−2
yr
−1
within the Amazon carbon source region if it is fully forested compared to any other land cover. Our results indicate that the parts of the Amazon forest that are already a net carbon source, still help sustain their own biomass production. Although the most degraded parts of the Amazon depend mostly on oceanic input of moisture, further degradation of this region would amplify carbon losses to the atmosphere.
Determining the sources of water inside plants using its isotopic composition is a long‐standing research challenge in ecohydrology. A better understanding of water sources can help improve models ...and ultimately contribute to more accurate forecasts of water availability, food production, carbon sequestration or ecosystem status. Over the years, several methods have been developed and applied to water source partitioning, and Gai et al. (2023, https://doi.org/10.1029/2022wr033849) provide a systematic assessment of the uncertainty of different isotopic tracers (2H, 3H, 17O, 18O) and mixing models (IsoSource, SIAR, MixSIR, MixSIAR) for an apple tree orchard on the Loess Plateau in north‐central China. For that study area, the combination of 2H and 18O with the MixSIAR mixing model is recommended. Importantly, the systematic assessment provides a framework that can be applied to select a suitable combination of tracers and mixing models for different ecosystems and climate zones. This commentary aims to provide a wider context for a selection of key results from Gai et al. (2023, https://doi.org/10.1029/2022wr033849) and highlight potential future research directions.
Plain Language Summary
Plants use water from the soil to survive, reproduce and grow. Plants can access water sources in shallow soil layers or from greater depth. The source of water can be determined by extracting water from a plant and measuring it precisely. This involves sophisticated machines and the use of models. Knowing where water is coming from, helps researchers to predict how plants respond to a changing climate or extreme weather. There exist several methods to estimate water sources and Gai et al. (2023, https://doi.org/10.1029/2022wr033849) test which of these methods works best for an apple tree orchard in China. This same procedure can be used for selecting the most appropriate method for other ecosystems and climate zones.
Key Points
The source of water inside plants, which can vary with season and across the field, can be traced using isotopes in water
Gai et al. (2023, https://doi.org/10.1029/2022wr033849) present a systematic assessment of tracers and mixing models to partition water sources in vegetation
Understanding water use strategies in vegetation can support modeling the response to extreme environmental conditions, such as droughts
Abstract
The year 2022 saw record breaking temperatures in Europe during both summer and fall. Similar to the recent 2018 drought, close to 30% (3.0 million km
2
) of the European continent was under ...severe summer drought. In 2022, the drought was located in central and southeastern Europe, contrasting the Northern-centered 2018 drought. We show, using multiple sets of observations, a reduction of net biospheric carbon uptake in summer (56-62 TgC) over the drought area. Specific sites in France even showed a widespread summertime carbon release by forests, additional to wildfires. Partial compensation (32%) for the decreased carbon uptake due to drought was offered by a warm autumn with prolonged biospheric carbon uptake. The severity of this second drought event in 5 years suggests drought-induced reduced carbon uptake to no longer be exceptional, and important to factor into Europe’s developing plans for net-zero greenhouse gas emissions that rely on carbon uptake by forests.
The power of forecasts to advance ecological theory Lewis, Abigail S. L.; Rollinson, Christine R.; Allyn, Andrew J. ...
Methods in ecology and evolution,
March 2023, 2023-03-00, 20230301, 2023-03-01, Letnik:
14, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Ecological forecasting provides a powerful set of methods for predicting short‐ and long‐term change in living systems. Forecasts are now widely produced, enabling proactive management for many ...applied ecological problems. However, despite numerous calls for an increased emphasis on prediction in ecology, the potential for forecasting to accelerate ecological theory development remains underrealized.
Here, we provide a conceptual framework describing how ecological forecasts can energize and advance ecological theory. We emphasize the many opportunities for future progress in this area through increased forecast development, comparison and synthesis.
Our framework describes how a forecasting approach can shed new light on existing ecological theories while also allowing researchers to address novel questions. Through rigorous and repeated testing of hypotheses, forecasting can help to refine theories and understand their generality across systems. Meanwhile, synthesizing across forecasts allows for the development of novel theory about the relative predictability of ecological variables across forecast horizons and scales.
We envision a future where forecasting is integrated as part of the toolset used in fundamental ecology. By outlining the relevance of forecasting methods to ecological theory, we aim to decrease barriers to entry and broaden the community of researchers using forecasting for fundamental ecological insight.
Abstract
The clumped isotope composition (Δ
47
, the anomaly of the mass 47 isotopologue relative to the abundance expected from a random isotope distribution) of CO
2
has been suggested as an ...additional tracer for gross CO
2
fluxes. However, the effect of photosynthetic gas exchange on Δ
47
has not been directly determined and two indirect/conceptual studies reported contradicting results. In this study, we quantify the effect of photosynthetic gas exchange on Δ
47
of CO
2
using leaf cuvette experiments with one C
4
and two C
3
plants. The experimental results are supported by calculations with a leaf cuvette model. Our results demonstrate the important roles of the Δ
47
value of CO
2
entering the leaf, kinetic fractionation as CO
2
diffuses into, and out of the leaf and CO
2
–H
2
O isotope exchange with leaf water. We experimentally confirm the previously suggested dependence of Δ
47
of CO
2
in the air surrounding a leaf on the stomatal conductance and back-diffusion flux. Gas exchange can enrich or deplete the Δ
47
of CO
2
depending on the Δ
47
of CO
2
entering the leaf and the fraction of CO
2
exchanged with leaf water and diffused back to the atmosphere, but under typical ambient conditions, it will lead to a decrease in Δ
47
.
This paper summarizes the open community conventions developed by the Ecological Forecasting Initiative (EFI) for the common formatting and archiving of ecological forecasts and the metadata ...associated with these forecasts. Such open standards are intended to promote interoperability and facilitate forecast communication, distribution, validation, and synthesis. For output files, we first describe the convention conceptually in terms of global attributes, forecast dimensions, forecasted variables, and ancillary indicator variables. We then illustrate the application of this convention to the two file formats that are currently preferred by the EFI, netCDF (network common data form), and comma-separated values (CSV), but note that the convention is extensible to future formats. For metadata, EFI's convention identifies a subset of conventional metadata variables that are required (e.g., temporal resolution and output variables) but focuses on developing a framework for storing information about forecast uncertainty propagation, data assimilation, and model complexity, which aims to facilitate cross-forecast synthesis. The initial application of this convention expands upon the Ecological Metadata Language (EML), a commonly used metadata standard in ecology. To facilitate community adoption, we also provide a Github repository containing a metadata validator tool and several vignettes in R and Python on how to both write and read in the EFI standard. Lastly, we provide guidance on forecast archiving, making an important distinction between short-term dissemination and long-term forecast archiving, while also touching on the archiving of code and workflows. Overall, the EFI convention is a living document that can continue to evolve over time through an open community process.
Defining model complexity: An ecological perspective Malmborg, Charlotte A.; Willson, Alyssa M.; Bradley, L. M. ...
Meteorological applications,
May/June 2024, 2024-05-00, 2024-05-01, Letnik:
31, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Models have become a key component of scientific hypothesis testing and climate and sustainability planning, as enabled by increased data availability and computing power. As a result, understanding ...how the perceived ‘complexity’ of a model corresponds to its accuracy and predictive power has become a prevalent research topic. However, a wide variety of definitions of model complexity have been proposed and used, leading to an imprecise understanding of what model complexity is and its consequences across research studies, study systems, and disciplines. Here, we propose a more explicit definition of model complexity, incorporating four facets—model class, model inputs, model parameters, and computational complexity—which are modulated by the complexity of the real‐world process being modelled. We illustrate these facets with several examples drawn from ecological literature. Overall, we argue that precise terminology and metrics of model complexity (e.g., number of parameters, number of inputs) may be necessary to characterize the emergent outcomes of complexity, including model comparison, model performance, model transferability and decision support.
A wide variety of definitions of model complexity have been proposed and used, leading to an imprecise understanding of what model complexity is and its consequences across research studies, study systems, and disciplines. Here, we propose a more explicit definition of model complexity, incorporating four facets–model class, model inputs, model parameters, and computational complexity–which are modulated by the complexity of the real‐world process being modeled. We illustrate these facets with several examples drawn from ecological literature. Overall, we argue that precise terminology and metrics of model complexity may be necessary to characterize the emergent outcomes of complexity, including model comparison, model performance, model transferability, and decision support.
Current and upcoming Sun-Induced chlorophyll Fluorescence (SIF) satellite products (e.g., GOME, TROPOMI, OCO, FLEX) have medium-to-coarse spatial resolutions (i.e., 0.3–80 km) and integrate radiances ...from different sources into a single ground surface unit (i.e., pixel). However, intrapixel heterogeneity, i.e., different soil and vegetation fractional cover and/or different chlorophyll content or vegetation structure in a fluorescence pixel, increases the challenge in retrieving and quantifying SIF. High spatial resolution Sentinel-2 (S2) data (20 m) can be used to better characterize the intrapixel heterogeneity of SIF and potentially extend the application of satellite-derived SIF to heterogeneous areas. In the context of the COST Action Optical synergies for spatiotemporal SENsing of Scalable ECOphysiological traits (SENSECO), in which this study was conducted, we proposed direct (i.e., spatial heterogeneity coefficient, standard deviation, normalized entropy, ensemble decision trees) and patch mosaic (i.e., local Moran’s I) approaches to characterize the spatial heterogeneity of SIF collected at 760 and 687 nm (SIF760 and SIF687, respectively) and to correlate it with the spatial heterogeneity of selected S2 derivatives. We used HyPlant airborne imagery acquired over an agricultural area in Braccagni (Italy) to emulate S2-like top-of-the-canopy reflectance and SIF imagery at different spatial resolutions (i.e., 300, 20, and 5 m). The ensemble decision trees method characterized FLEX intrapixel heterogeneity best (R2 > 0.9 for all predictors with respect to SIF760 and SIF687). Nevertheless, the standard deviation and spatial heterogeneity coefficient using k-means clustering scene classification also provided acceptable results. In particular, the near-infrared reflectance of terrestrial vegetation (NIRv) index accounted for most of the spatial heterogeneity of SIF760 in all applied methods (R2 = 0.76 with the standard deviation method; R2 = 0.63 with the spatial heterogeneity coefficient method using a scene classification map with 15 classes). The models developed for SIF687 did not perform as well as those for SIF760, possibly due to the uncertainties in fluorescence retrieval at 687 nm and the low signal-to-noise ratio in the red spectral region. Our study shows the potential of the proposed methods to be implemented as part of the FLEX ground segment processing chain to quantify the intrapixel heterogeneity of a FLEX pixel and/or as a quality flag to determine the reliability of the retrieved fluorescence.
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