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NASA NTRS2020

Land management and climate change determine second‐generation bioenergy potential of the US Northern Great Plains

Bioenergy with carbon capture and storage (BECCS) has been proposed as a potential climate mitigation strategy raising concerns over trade‐offs with existing ecosystem services. We evaluate the feasibility of BECCS in the Upper Missouri River Basin (UMRB), a landscape with diverse land use, ownership, and bioenergy potential. We develop land‐use change scenarios and a switchgrass (Panicum virgatum L.) crop functional type to use in a land‐surface model to simulate second‐generation bioenergy production. By the end of this century, average annual switchgrass production over the UMRB ranges from 60 to 210 Tg dry mass/year and is dependent on the Representative Concentration Pathway for greenhouse gas emissions and on land‐use change assumptions. Under our simple phase‐in assumptions this results in a cumulative total production of 2,000–6,000 Tg C over the study period with the upper estimates only possible in the absence of climate change. Switchgrass yields decreased as average CO2 concentrations and temperatures increased, suggesting the effect of elevated atmospheric CO2 was small because of its C4 photosynthetic pathway. By the end of the 21st century, the potential energy stored annually in harvested switchgrass averaged between 1 and 4 EJ/year assuming perfect conversion efficiency, or an annual electrical generation capacity of 7,000–28,000 MW assuming current bioenergy efficiency rates. Trade‐offs between bioenergy and ecosystem services were identified, including cumulative direct losses of 1,000–2,600 Tg C stored in natural ecosystems from land‐use change by 2090. Total cumulative losses of ecosystem carbon stocks were higher than the potential ~300 Tg C in fossil fuel emissions from the single largest power plant in the region over the same time period, and equivalent to potential carbon removal from the atmosphere from using biofuels grown in the same region. Numerous trade‐offs from BECCS expansion in the UMRB must be balanced against the potential benefits of a carbon‐negative energy system.

climate change↗

NASA NTRS1994

Directional radiance measurements: Challenges in the sampling of landscapes

Most earth surfaces, particularly those supporting natural vegetation ecosystems, constitute structurally and spectrally complex surfaces that are distinctly non-Lambertian reflectors. Obtaining meaningful measurements of the directional radiances of landscapes and obtaining estimates of the complete bidirectional reflectance distribution functions of ground targets with complex and variable landscape and radiometric features are challenging tasks. Reasons for the increased interest in directional radiance measurements are presented, and the issues that must be addressed when trying to acquire directional radiances for vegetated land surfaces from different types of remote sensing platforms are discussed. Priority research emphases are suggested, concerning field measurements of directional surface radiances and reflectances for future research. Primarily, emphasis must be given to the acquisition of more complete and directly associated radiometric and biometric parameter data sets that will empower the exploitation of the 'angular dimension' in remote sensing of vegetation through enabling the further development and rigorous validation of state of the art plant canopy models.

Deering, D. W.↗

NASA NTRS1989

Forest and grassland ecosystem studies using the advanced solid-state array spectroradiometer

The advanced solid-state array spectroradiometer (ASAS) is an airborne, off-nadir pointing imaging spectroradiometer used to acquire bidirectional radiance data for terrestrial targets. As its platform aircraft flies over a target the sensor can image the target through a sequence of at least seven fore-to-aft view directions ranging up to 45 deg on either side of nadir. ASAS acquires data for 29 spectral bands in the visible and near-infrared portions of the spectrum with a resolution of 15 nm. ASAS data were recently acquired for a prairie ecosystem and a northern forest ecosystem. The data demonstrate the combined effects of reflectance anisotropy and increased atmospheric path length on off-nadir observations. One result of these effects is a variation in vegetation indices as a function of view direction. Normalized-difference-vegetation-indices for prairie grass, coniferous, and deciduous canopies varied up to 14 percent, 23 percent, and 6 percent, respectively, relative to nadir as a function of view zenith angle along the solar principal plane.

Irons, James R.↗

NASA NTRS2023

Modeling Sea Ice Albedo and Transmittance Measurements With A Fully-Coupled Radiative Transfer Model

A rigorous treatment of the sea ice medium has been incorporated in the advanced Coupled Ocean-Atmosphere Radiative Transfer (COART) model. The inherent optical properties (IOPs) of brine pockets and air bubbles over the 0.25-4.0 μm spectral region are parameterized as a function of the vertical profile of the sea ice physical properties (temperature, salinity and density). We test the model performance using available albedo and transmittance measurements collected during the Impacts of Climate on the Ecosystems and Chemistry of the Arctic Pacific Environment (ICESCAPE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) field campaigns. The observations are adequately simulated when at least three layers are used to represent bare (first-year and multi-year) ice, including a thin top layer characterized by low density and high scattering. Two layers can be sufficient to model isolated cases of multi-year ice, and apply well to ponded ice except for shallow ponds over thick ice. The albedo and transmittance of ponded ice in the visible are mainly determined by the optical properties of the ice underlying the water layer used to model the pond. Sensitivity results indicate that the air volume or ice density has the largest impact on the simulated fluxes. Possible contamination from light-absorbing impurities, such as black carbon or ice algae, is also implemented in the model and is able to effectively reduce the albedo and transmittance in the visible spectrum to further improve the model-observation agreement. The agreement between the observed and modeled spectra validates the parameterization of the sea ice IOPs, and endorses COART as an accurate tool for radiation studies in the cryosphere.

Coupled Ocean-9 Atmosphere Radiative Transfer (COA↗

NASA NTRS2013

Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

Passive Remote Sensing↗

NASA NTRS2017

One Step Closer to Mars with Aquaponics: Cultivating Citizen Science in K12 Schools

The Microbial Ecology and Biogeochemistry Research Laboratory at NASA Ames Research Center focuses primarily on the nutrient cycling and diversity of complex microbial communities. NASA is interested in the composition and functioning of microbial mat communities as these processes fundamentally shape the form and function of these analogs for the earliest forms of life on Earth (3.6 billion years ago), and likely will on other planets as well. Aquaponics systems are supported by microbial communities who perform many complex ecosystem services, including cycling nitrogen. Microbes are integral to the stability and productivity of aquaponics systems, which are analogous to microbial communities in food production systems that are essential for building efficient life support systems for long-distance space travel. Students at Meadow Park Middle School created 10 parallel aquaponics systems and took temporal microbial samples to characterize whether any macro-ecology variables impacted or changed the microbial diversity of these systems. Students additionally created a website so that other classrooms can pursue similar projects in their own schools (https://go.nasa.gov/2uJhxmF). Our lab at NASA Ames has sequenced water samples from each of the 10 tanks at 3 timepoints using a MinION sequencer. MPMS students will be involved in the analysis of the bioinformatics data generated through this collaboration. Our ongoing collaboration aims to collect and analyze data in the classroom setting that has utility for research scientists, while involving students as collaborators in the research process.

Kolattukudy, Maria↗

NASA NTRS2001

Biogeochemical Processes in Microbial Ecosystems

The hierarchical organization of microbial ecosystems determines process rates that shape Earth's environment, create the biomarker sedimentary and atmospheric signatures of life and define the stage upon which major evolutionary events occurred. In order to understand how microorganisms have shaped the global environment of Earth and potentially, other worlds, we must develop an experimental paradigm that links biogeochemical processes with ever-changing temporal and spatial distributions of microbial population, and their metabolic properties. Photosynthetic microbial mats offer an opportunity to define holistic functionality at the millimeter scale. At the same time, their Biogeochemistry contributes to environmental processes on a planetary scale. These mats are possibly direct descendents of the most ancient biological communities; communities in which oxygenic photosynthesis might have been invented. Mats provide one of the best natural systems to study how microbial populations associate to control dynamic biogeochemical gradients. These are self-sustaining, complete ecosystems in which light energy absorbed over a diel (24 hour) cycle drives the synthesis of spatially-organized, diverse biomass. Tightly-coupled microorganisms in the mat have specialized metabolisms that catalyze transformations of carbon, nitrogen. sulfur, and a host of other elements.

DesMarais, David J.↗

NASA NTRS2003

Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

King, Michael D.↗

NASA NTRS2020

Structure and Parameter Uncertainty in Centennial Projections of Forest Community Structure and Carbon Cycling

Secondary forest regrowth shapes community succession and biogeochemistry for decades, including in the Upper Great Lakes region. Vegetation models encapsulate our understanding of forest function, and whether models can reproduce multi‐decadal succession patterns is an indication of our ability to predict forest responses to future change. We test the ability of a vegetation model to simulate C cycling and community composition during 100 years of forest regrowth following stand‐replacing disturbance, asking (a) Which processes and parameters are most important to accurately model Upper Midwest forest succession? (b) What is the relative importance of model structure versus parameter values to these predictions? We ran ensembles of the Ecosystem Demography model v2.2 with different representations of processes important to competition for light. We compared the magnitude of structural and parameter uncertainty and assessed which sub‐model–parameter combinations best reproduced observed C fluxes and community composition. On average, our simulations underestimated observed net primary productivity (NPP) and leaf area index (LAI) after 100 years and predicted complete dominance by a single plant functional type (PFT). Out of 4,000 simulations, only nine fell within the observed range of both NPP and LAI, but these predicted unrealistically complete dominance by either early hardwood or pine PFTs. A different set of seven simulations were ecologically plausible but under‐predicted observed NPP and LAI. Parameter uncertainty was large; NPP and LAI ranged from ~0% to >200% of their mean value, and any PFT could become dominant. The two parameters that contributed most to uncertainty in predicted NPP were plant–soil water conductance and growth respiration, both unobservable empirical coefficients. We conclude that (a) parameter uncertainty is more important than structural uncertainty, at least for ED‐2.2 in Upper Midwest forests and (b) simulating both productivity and plant community composition accurately without physically unrealistic parameters remains challenging for demographic vegetation models.

canopy radiative transfer↗

NASA NTRS2008

The NASA NEESPI Data Portal: Products, Information, and Services

Studies have indicated that land cover and use changes in Northern Eurasia influence global climate system. However, the procedures are not fully understood and it is challenging to understand the interactions between the land changes in this region and the global climate. Having integrated data collections form multiple disciplines are important for studies of climate and environmental changes. Remote sensed and model data are particularly important die to sparse in situ measurements in many Eurasia regions especially in Siberia. The NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) NEESPI data portal has generated infrastructure to provide satellite remote sensing and numerical model data for atmospheric, land surface, and cryosphere. Data searching, subsetting, and downloading functions are available. ONe useful tool is the Web-based online data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure), which allows scientists to assess easily the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with global climate system. Recently, we have created a metadata database prototype to expand the NASA NEESPI data portal for providing a venue for NEESPI scientists fo find the desired data easily and leveraging data sharing within NEESPI projects. The database provides product level information. The desired data can be found through navigation and free text search and narrowed down by filtering with a number of constraints. In addition, we have developed a Web Map Service (WMS) prototype to allow access data and images from difference data resources.

Shen, Suhung↗

NASA NTRS1975

Technology for return of planetary samples

The problem of returning a Mars sample to Earth was considered. The model ecosystem concept was advanced as the most reliable, sensitive method for assessing the biohazard from the Mars sample before it is permitted on Earth. Two approaches to ecosystem development were studied. In the first approach, the Mars sample would be introduced into the ecosystem and exposed to conditions which are as similar to the Martian environment as the constitutent terrestrial organisms can tolerate. In the second approach, the Mars sample would be tested to determine its effects on important terrestrial cellular functions. In addition, efforts were directed toward establishing design considerations for a Mars Planetary Receiving Laboratory. The problems encountered with the Lunar Receiving Laboratory were evaluated in this context. A questionnaire was developed to obtain information regarding important experiments to be conducted in the Planetary Receiving Laboratory.

Source record↗

NASA NTRS2021

Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (−30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (−19%) and ecosystem (−7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Félicien Meunier↗

NASA NTRSDate not supplied

NASA's Implementation of Cloud Services for Human Space Flight

Cloud is a tried-and-true technology used throughout United States government agencies, including the National Aeronautics and Space Administration (NASA). With reliable results and infrequent downtimes, cloud allows for secure remote access, customizability, and streamlined monitoring options, creating an environment for better data integrity and availability. As NASA increasingly migrates functions to the cloud, the Space Communications and Navigation Program (SCaN) program has been investigating how this capability can be leveraged to provide communication services to its users and customers. Currently, missions such as NASA-ISRO Synthetic Aperture Radar (NISAR), Plankton, Aerosol, Cloud, ocean Ecosystem (PACE), and Roman Space Telescope (RST) are planned to incorporate cloud into their data delivery architecture. However, SCaN is looking to expand further. This conversion to using cloud services allows for greater availability of mission data for both robotic and human space flight (HSF)missions. The SCaN program and the Near Space Network (NSN) are working to consolidate resources and create a cloud environment suitable for the entirety of the SCaN program network architecture. SCaN is in the process of finalizing its cloud architecture and soon will be implementing cloud services. The new services used will adhere to federal regulations including Federal Risk and Authorization Management Program (FedRAMP), which is built upon National Institute of Standards and Technology (NIST)documentation. While keeping in mind these security requirements, an auxiliary objective of the cloud integration is to ensure the most cost-efficient solution; providing a scalable, robust and resilient system. Using cloud services, NASA will gain access to better centralized monitoring and management features, along with customizable services on a pay-per-use plan. With the ever-growing NASA mission data volume needs, maintaining ample storage space is another major constraint. Processing and storing such large amounts of data, on the order of terabytes a day, requires dynamic processing capability which is inherently a strength of cloud computing. By routing this data from ground stations through the cloud, there will be greater ease of access for both SCaN and the user community. Artificial intelligence and other built-in cloud functions can also enhance efficiency, improving data processing time. Thereby also allowing for better data availability. As we look to the future of cloud services, NASA will continue to leverage capabilities that will benefit NASA’s ability to provide cost-effective communication services. This paper further outlines the evolution of cloud use by SCaN in the context of Human Space Flight.

cloud storage↗

NASA NTRS2016

Airborne Spectral BRDF of Various Surface Types (Ocean, Vegetation, Snow, Desert, Wetlands, Cloud Decks, Smoke Layers) for Remote Sensing Applications

In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

albedo↗

NASA NTRS1997

The Surface Heat Flux as a Function of Ground Cover for Climate Models

Surface heat fluxes were examined as a function of surface properties and meteorological conditions in a 100 km x 100 km grid square at 1-km spatial resolution centered at the location of the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE), the Forest Ecosystem Dynamics site in central Maine, and a semiarid rangeland site around Walnut Gulch, Arizona. This investigation treats the surface heat flux variability within a GCM grid box to provide insight into methods for treating that variability in climate models. The heat fluxes were calculated using NOAA AVHRR and available meteorological data. The average heat fluxes that were estimated using the various area ground-cover representations were compared with the ensemble average heat fluxes for the entire area, which were assumed to be the best representation of the heat fluxes for the areas. Average beat fluxes were estimated for the entire 100 km x 100 km area based on a single ground-cover representation, and the mean error for the area sensible heat flux was about 10% and for the area latent heat flux, 21%. The estimation error was reduced, and in some cases significantly reduced, when the area heat fluxes were estimated by partitioning the area according to significant ground cover. The most significant effect of the partitioning was on the latent heat flux estimates.

Vukovich, Fred M.↗

NASA NTRS2018

Satellite Sensor Requirements for Monitoring Essential Biodiversity Variables of Coastal Ecosystems

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration less than 2%, relative calibration of 0.2%, polarization sensitivity less than 1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

aquatic↗

NASA NTRS2001

Impact of dilution on microbial community structure and functional potential: comparison of numerical simulations and batch culture experiments

A series of microcosm experiments was performed using serial dilutions of a sewage microbial community to inoculate a set of batch cultures in sterile sewage. After inoculation, the dilution-defined communities were allowed to regrow for several days and a number of community attributes were measured in the regrown assemblages. Based upon a set of numerical simulations, community structure was expected to differ along the dilution gradient; the greatest differences in structure were anticipated between the undiluted-low-dilution communities and the communities regrown from the very dilute (more than 10(-4)) inocula. Furthermore, some differences were expected among the lower-dilution treatments (e.g., between undiluted and 10(-1)) depending upon the evenness of the original community. In general, each of the procedures used to examine the experimental community structures separated the communities into at least two, often three, distinct groups. The groupings were consistent with the simulated dilution of a mixture of organisms with a very uneven distribution. Significant differences in community structure were detected with genetic (amplified fragment length polymorphism and terminal restriction fragment length polymorphism), physiological (community level physiological profiling), and culture-based (colony morphology on R2A agar) measurements. Along with differences in community structure, differences in community size (acridine orange direct counting), composition (ratio of sewage medium counts to R2A counts, monitoring of each colony morphology across the treatments), and metabolic redundancy (i.e., generalist versus specialist) were also observed, suggesting that the differences in structure and diversity of communities maintained in the same environment can be manifested as differences in community organization and function.

Non-NASA Center↗

NASA NTRS2024

Discounting Water for Optimal Carbon Gain as a Basis of Stomatal Closure

The exchange of carbon dioxide and water vapor between terrestrial ecosystems and the atmosphere is regulated by stomata (small pores in the leaves of plants). Unsurprisingly, environmental factors controlling the opening and closure of stomata has been sought as early as 1800. One approach, popularized in the early 1970s, is a stomatal optimization framework. This framework is based on the hypothesis that plants optimize carbon gain subject to water loss or water availability constraints. This constraint optimization problem was solved in various forms assuming instantaneous adjustments of stomatal aperture to maximize a reward function with no future foresight or legacy effects. Holtzman et al. (2024, https://doi.org/10.1029/2023av001113) offers a novel approach that can diagnose the effective timescale over which the reward function maximization must be time-integrated. The developed method thus optimizes an integrated carbon gain function but adjusted by a discount factor subject to water availability in the root zone. The discount factor considers how the plant values carbon gain to save water and its timescale can be inferred from observations because the model is analytically tractable. The results suggest that the most important climate factor that determines this discount timescale is multi-annual mean of the longest dry period during the growing season. The findings highlight how local climate traits influence the spatial variation in ecosystem-level water use strategies. This sets the stage for expanding such a framework to cases where multiple constraints act in concert while operating at distinct time scales.

stomata↗