查看更多>>摘要：? 2022Ecological studies have long examined large-scale geographic gradients in abiotic conditions and their relationship to the structure and function of ecological systems, but many critical processes in forested systems are driven by abiotic gradients that vary at fine spatial and temporal scales. To adequately characterize fine scale microclimatic variability, intensive sampling is required that may be cost-prohibitive with commercially available instrumentation. The expanded availability of inexpensive, and open-source environmental monitoring systems may meet the need to advance mechanistic understanding of fine-scale ecological processes. Here, we (1) present a custom, open-source, and inexpensive environmental monitoring system, (2) evaluate its performance against commercial systems and sensors, and (3) demonstrate its utility in a broad range of forest ecology applications. We demonstrate that temperature and humidity measurements are reliably captured with open-source data loggers and sensors are strongly correlated to research-grade instruments (R2 = 0.97). Further, these systems generate reliable data at 13-80% of the cost of comparable commercial systems primarily due to higher potential for scalability. We demonstrate applications in forest ecology to examine micrometeorology in fire prone ecosystems, microsite variability in dry conifer systems, and climate mediation effects in urban forested systems. The use of open-source data loggers for a broad range of forest ecology applications offer opportunities for more robust environmental characterization especially in forest ecology applications where high spatial and temporal resolution is necessary to understand ecological phenomena such as fire, regeneration, and phenology. Increased use, development, and validation of low-cost instrumentation with commercial options will increase confidence of their use among researchers in these and other applications.
查看更多>>摘要：? 2022Quantifying the ratio of transpiration (T) to evapotranspiration (ET), T/ET, is crucial for understanding and predicting the water cycle and energy balance between the land and atmosphere. Here, we used three well-validated ET partitioning models to estimate T/ET at global fluxnet sites. The models are the Shuttleworth-Wallace-Hu (SWH) model, the Priestley-Taylor Jet Propulsion Lab (PT-JPL) model, and the underlying water use efficiency (uWUE) method. SWH illustrated the most reliable estimate in both the magnitude and the across-site variability of T/ET among three models. Mean annual T/ET derived from SWH, PT-JPL, and uWUE were 0.61±0.14, 0.52±0.12 and 0.59±0.07, respectively. Leaf area index (LAI) was the key driver of spatial variations in T/ET across sites, as well as seasonal variations in T/ET in ecosystems in most climatic zones except for the tropical and arid regions. However, there were discrepancies in factors controlling inter-annual variations in T/ET among the models. SWH and PT-JPL showed that the inter-annual variation in T/ET was more related to LAI than climatic factors but an opposite result was found by uWUE due to the simple structure and less forcing data of uWUE. The findings of our research highlight the importance of capturing the controls of LAI on ET partitioning for predicting future water cycle with land models. We appeal for direct measurements of ET components at the flux tower sites for validating the models and reduce model uncertainties.
查看更多>>摘要：? 2022Accurately partitioning net ecosystem exchange (NEE) into ecosystem respiration (ER) and gross primary productivity (GPP) is critical for understanding the terrestrial carbon cycle. The standard partitioning methods rely on simplified empirical models, which have inherent structural errors. These structural errors lead to biased GPP and ER estimation, especially during extreme events (e.g., drought) and human disturbances (e.g., crop harvest). Recently, solar-induced chlorophyll fluorescence (SIF) has been shown to be well correlated to GPP, thus offering a path to improve the NEE partitioning by constraining GPP. However, the ecosystem-scale relationship between GPP and SIF remains limited. Here, we show that neural networks informed by SIF observations (NNSIF) can be successfully used to partition NEE, while simultaneously learning the ecosystem-scale GPP-SIF relationship. NNSIF was compared against standard partitioning methods and NN without SIF constraint (NNnoSIF), using field data from different ecosystems and synthetic data generated by a coupled fluorescence-photosynthesis model (SCOPE). NNSIF showed superior performance as: (1) it effectively improves the ER estimation, especially at high temperature, (2) it better captures the moisture limitation on ER, (3) it more accurately estimates LUE variations to stress, and (4) it uniquely captures the rapid GPP drop after land management (harvest). Furthermore, NNSIF can retrieve the GPP-SIF relationship at the ecosystem scale, and elucidate how this relationship responds to environmental conditions. Overall, our algorithm provides the first direct and non-empirical estimate of the ecosystem-scale GPP-SIF relationship, without relying on any prior empirical assumptions on the relationships between CO2 fluxes, climatic drivers, and SIF. The new knowledge learned by NNSIF can help better estimate global-scale GPP using satellite SIF, especially during extreme events and in the presence of land management.
查看更多>>摘要：? 2022Understanding the impact of land use and land cover change on surface energy and water budgets is increasingly important in the context of climate change research. Eddy covariance (EC) methods are the gold standard for high temporal resolution measurements of water and energy fluxes, but cannot resolve spatial heterogeneity and are limited in scope to the tower footprint (few hundred meter range). Satellite remote sensing methods have excellent coverage, but lack spatial and temporal resolution. Long-range unmanned aerial systems (UAS) can complement these other methods with high spatial resolution over larger areas. Here we use UAS thermography and multispectral data as inputs to two variants of the Two Source Energy Balance Model to accurately map surface energy and water fluxes over a nutrient manipulation experiment in a managed semi-natural oak savanna from peak growing season to senescence. We use energy flux measurements from 6 EC stations to evaluate the performance of our method and achieve good accuracy (RMSD ≈ 60 W m?2 for latent heat flux). We use the best performing latent heat estimates to produce very high-resolution evapotranspiration (ET) maps, and investigate the drivers of ET change over the transition to the senescence period. We find that nitrogen and nitrogen plus phosphorus treatments lead to significant increases in ET (P < 0.001) for both trees (4 and 6%, respectively) and grass (12 and 9%, respectively) compared to the control. These results highlight that the high sensitivity and spatial and temporal resolution of a UAS system allows the precise estimation of relative water and energy fluxes over heterogeneous vegetation cover.
查看更多>>摘要：? 2022 Elsevier B.V.Detecting the phenology of photosynthesis, which conveys the length of the growing season, is key for terrestrial ecosystem models to constrain total annual carbon uptake and estimate gross primary productivity (GPP). However, some of the vegetation indices that are widely used for modelling GPP lack the ability to represent changes in the magnitude of photosynthesis, leading to errors in detecting phenology and large uncertainties. Crucially, remotely sensed vegetation indices such as the photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI) can detect changes in foliar carotenoid composition that represent adjustments in photosynthetic light-use-efficiency (LUE) and changes in phenology. We modeled GPP from remote sensing data using PRI and CCI to represent foliar carotenoid changes as proxies for LUE. GPP values estimated from these PRI and CCI modified LUE models were compared against GPP from eddy covariance flux tower measurements, MODerate Resolution Imaging Spectroradiometer (MODIS) GPP product, conventional meteorological driven LUE-model, and process-based dynamic global vegetation model (ie. JULES) in an evergreen needleleaf and a deciduous broadleaf forest in the Great Lakes region. Overall, and in particular for evergreen needleleaf forests, estimates of start and end of growing season using PRI and CCI LUE-models showed less year-to-year variability than estimates obtained by process-based meteorological models. Although many process-based models provide reasonable estimates of start and end of growing season, our results demonstrate that using regulatory carotenoids and photosynthetic efficiency can improve remote monitoring of the phenology of forest vegetation.
查看更多>>摘要：? 2022Climate change is expected to have significant impacts on European forests, causing changes in the geographic distribution of species and ecosystem functioning. Douglas fir (Pseudotsuga menziesii) and silver fir (Abies alba) are considered potential alternatives to the drought endangered Norway spruce (Picea abies). However, still little is known about differences in their intra-annual growth dynamics, an important characteristic determining the adaptive capacity of each species. Here we make use of more than 5000 microcores from 132 trees of the three species distributed along three elevational transects (370–1125 m a.s.l.) spanning a temperature gradient of 5 °C in South-Western Germany to compare their intra-annual growth dynamics in a context of changing climate. Results indicate an earlier onset of cambial cell production of about 5.1 days per °C temperature increase for all tree species. Douglas fir produced the highest number of cells and exhibited the longest seasonal period of wood formation, starting two and four weeks earlier and ceasing about two and three weeks later than silver fir and Norway spruce, respectively. Additionally, Douglas fir displayed the highest maximum cell production rate and a 20% higher average cell production rate than Norway spruce and even 50% higher rate than silver fir. We found that soil moisture, but even more the number of produced cells were significantly correlated with the date of growth cessation, compared to a negligible correlation with mean annual temperature (MAT). The superior growth performance of Douglas fir resulting from a longer growth duration with higher rates of cambial cell division was consistent across our climatic gradient. These results corroborate that Douglas fir could be a high-performance alternative to the more climate-change-endangered Norway spruce.
查看更多>>摘要：? 2022 Elsevier B.V.Agroforestry is considered to be climate-smart; not only can it be profitable for smallholders, but also it represents a sustainable form of intensive agriculture that can help buffer the effects of extreme climate. However, its feasibility remains under dispute in semiarid regions, especially where there can be extreme droughts. We therefore investigated how intercropping with annual bioenergy crops, soybean (Glycine max) and canola (Brassica rapa), affects ecohydrology in young apple trees, and how the trees respond to droughts of varying degrees on the semiarid Loess Plateau of China. A monoculture orchard was used as a control, and the droughts were controlled by reducing natural precipitation by 15% (moderate drought) and 25% (severe drought). We found that, compared with the monoculture, the agroforestry system increased soil water storage (SWS) in the 80-280 cm by 5-8%, apple tree's daily water use (Q) by 76-118%, and transpiration per unit leaf area (TrL) by 33-71%; it also promoted tree growth. Both drought levels affected soil water availability and water use. Compared with agroforestry without an enforced drought, moderate drought conditions reduced SWS in the 80-180 cm by 11-15%, the Q value by 19-24%, and TrL value by 13-17%, and these apple trees still had higher Q and TrL levels than monoculture trees suffering no drought; and severe drought conditions caused the apple trees to absorb soil water from deeper soil layers, and reduced SWS in the 80-280 cm by 16-18%, Q by 50-60% and TrL by 12-38%. However, there were no significant difference in Q, TrL and aboveground growth parameters for trees between monoculture and severe drought treatments. These findings demonstrate that agroforestry has clear ecohydrological advantage to monoculture for young apple trees in semiarid regions.
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