Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem

El-Madany, Tarek S.; Reichstein, Markus; Pérez-Priego, Óscar; Carrara, Arnaud; Moreno, Gerardo; Martín, M. Pilar; Pacheco‐Labrador, Javier; Wohlfahrt, Georg; Nieto, Héctor; Weber, Ulrich; Kolle, Olaf; Luo, Yunpeng; Carvalhais, Nuno; Migliavacca, Mirco

doi:10.1016/j.agrformet.2018.07.010

Cited by 65 publications

(99 citation statements)

References 53 publications

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“…We argue that seasonal variations in VIs and GPP are driven by the herbaceous layer, which dominates the ecosystem dynamics in our study sites [59]. Our sites are characterized by relatively sparse evergreen broadleaf trees (~20%) and a larger fraction of annual grasses [59]. Foliage amount in evergreen tree species remain relatively constant throughout the year, and they can utilize their vast root system to access the water deep within the soil [64][65][66].…”

Section: Characterizing Variatoin and Drivers Of Structural And Physimentioning

confidence: 99%

“…In general, seasonal variations in PhenoCam VIs were in phase with those of GPP ( Figure 3 and Table 3). We argue that seasonal variations in VIs and GPP are driven by the herbaceous layer, which dominates the ecosystem dynamics in our study sites [59]. Our sites are characterized by relatively sparse evergreen broadleaf trees (~20%) and a larger fraction of annual grasses [59].…”

Section: Characterizing Variatoin and Drivers Of Structural And Physimentioning

confidence: 99%

“…The different sites have different tree/grass proportions in the camera FOVs, as only one direction of ecosystems could be captured from the PhenoCam. However, the fractional tree canopy covers were consistent (~0.20) in the four sites by referring to field surveys and the classification analysis using airborne hyperspectral imagery [58,59]. The analysis of each footprint for each EC tower also indicates GPP is contributed from~20% tree canopy and~80% grasses [59].…”

Section: Calculation Of Vegetation Indexes From Phenocammentioning

confidence: 99%

“…However, the fractional tree canopy covers were consistent (~0.20) in the four sites by referring to field surveys and the classification analysis using airborne hyperspectral imagery [58,59]. The analysis of each footprint for each EC tower also indicates GPP is contributed from~20% tree canopy and~80% grasses [59]. In order to reduce the bias introduced by the different ratios of tree/grass in the images and camera FOV, which has to do with logistical constrains during the camera installation, the ecosystem VIs (GCC, CamNDVI, CamNIRv, CamRVI) were computed by using the weighted average of the VIs derived from Grass ROIs of 0.8 and Tree ROIs of 0.2.…”

Section: Calculation Of Vegetation Indexes From Phenocammentioning

confidence: 99%

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Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Luo

El-Madany

Filippa³

et al. 2018

Remote Sensing

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Tree-grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity-GPP) at four tree-grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural

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Section: Characterizing Variatoin and Drivers Of Structural And Physimentioning

confidence: 99%

Section: Characterizing Variatoin and Drivers Of Structural And Physimentioning

confidence: 99%

Section: Calculation Of Vegetation Indexes From Phenocammentioning

confidence: 99%

Section: Calculation Of Vegetation Indexes From Phenocammentioning

confidence: 99%

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Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Luo

El-Madany

Filippa³

et al. 2018

Remote Sensing

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“…The tree density is roughly 20 trees/ha, and the site is grazed from early December to late June by cattle at an intensity of <0.3 livestock unitsÁha À1 Áyr À1 (El-Madany et al 2018). The tree density is roughly 20 trees/ha, and the site is grazed from early December to late June by cattle at an intensity of <0.3 livestock unitsÁha À1 Áyr À1 (El-Madany et al 2018).…”

Section: Site Descriptionmentioning

confidence: 99%

Fate of N additions in a multiple resource‐limited Mediterranean oak savanna

et al. 2019

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Mediterranean oak savannas, such as Spanish dehesas, are multiple resource-limited ecosystems found in semiarid regions which are key contributors to interannual variability of the global carbon (C) budget. Interactions between nitrogen (N) and phosphorus (P) cycles are expected to play a major role in overall ecosystem function as anthropogenic N deposition shifts ecosystems from N to P limitation, leaving unknown how increased N availability might influence C uptake. Therefore, the fate of N additions in dehesas is important for understanding global C cycling. Using a 15 N tracer experiment within fertilized (N or N + P) plots of a Holm oak dehesa, we tested the effects of ecosystem spatial heterogeneity (habitat), P addition, and time on the fate of added N. We expected that open pasture areas would retain more of the added N in biological components due to greater N limitation, that the addition of P would enhance N retention in biological components relative to N alone, and that added N would shift from being within the microbial biomass immediately after addition to being predominantly within plants at the beginning of the following growing season. We found that open pasture plots with N only had the greatest label recovery seven months after the start of the experiment, supporting the idea that open pasture was more N-limited than under-canopy areas. However, soil was the largest sink for added N, regardless of habitat, treatment, or time. Our results suggest that abiotic fixation of N may play an important role in modifying the effects of N deposition in dehesas.

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Plant‐available N:P alters root litter N recycling in a Mediterranean tree–grass ecosystem

Nair

Morris

Migliavacca

et al. 2020

J. Plant Nutr. Soil Sci.

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Background: Nitrogen deposition can cause an ecosystem‐level shift in available N (nitrogen) to P (phosphorus) availability. However, most plant N nutrition is from edaphic sources rather than deposition and in seasonally dry grassland systems, root litter is the predominant nutrient source.Aims: We were interested how litter turnover and altered nutrient recycling from dead biomass can compensate for these shifts in ecosystem stoichiometry.Methods: We studied a Mediterranean savanna amended with N or NP treatments three years prior. We measured root and plant‐available soil N:P stoichiometry in two micro‐habitats: open pasture and beneath oak canopies. 15N‐labelled root litter incubated in topsoils without litterbags was used to trace uptake of litter N by herbaceous strata roots.Results: Since fertilization, NP added sites have become relatively P enriched, resulting in lower N:P ratios in living roots than either when N was added alone or control sites. Total litter‐derived 15N uptake by roots was proportional to root ingrowth response but higher in the NP than N treatment, indicating a higher N demand when N and P were added together. We observed more 15N uptake by plants under tree canopies, indicating a tighter nutrient recycling loop in these micro‐habitats in contrast to treatment level ‘fertility' trends.Conclusions: Root stoichiometry responded to manipulated soil nutrient availability and N uptake was altered as plants attempted to compensate for nutrient availability imbalances, indicating that these ecosystem perturbations have long term effects on nutrient cycling which can propagate to whole system function. This was also related to functional community‐level adaptions between micro‐habitats with under canopy communities more able to take advantage of the litter nutrient source.

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Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem

Cited by 65 publications

References 53 publications

Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

Fate of N additions in a multiple resource‐limited Mediterranean oak savanna

Plant‐available N:P alters root litter N recycling in a Mediterranean tree–grass ecosystem

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