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The long‐term increase in satellite‐based proxies of vegetation cover is a well‐documented response of seasonally snow‐covered ecosystems to climate warming. However, observed greening trends are far from uniform, and substantial uncertainty remains concerning the underlying causes of this spatial variability. Here, we processed surface reflectance of the moderate resolution imaging spectroradiometer (MODIS) to investigate trends and drivers of changes in the annual peak values of the Normalized Difference Vegetation Index (NDVI). Our study focuses on above‐treeline ecosystems in the European Alps. NDVI changes in these ecosystems are highly sensitive to land cover and biomass changes and are marginally affected by anthropogenic disturbances. We observed widespread greening for the 2000–2020 period, a pattern that is consistent with the overall increase in summer temperature. At the local scale, the spatial variability of greening was mainly due to the preferential response of north‐facing slopes between 1900 and 2400 m. Using high‐resolution imagery, we noticed that the presence of screes and outcrops locally magnified this response. At the regional scale, we identified hotspots of greening where vegetation cover is sparser than expected given the elevation and exposure. Most of these hotspots experienced delayed snow melt and green‐up dates in recent years. We conclude that the ongoing greening in the Alps primarily reflects the high responsiveness of sparsely vegetated ecosystems that are able to benefit the most from temperature and water‐related habitat amelioration above treeline. [ABSTRACT FROM AUTHOR]

Anthropogenic nitrogen (N) deposition and resulting differences in ecosystem N and phosphorus (P) ratios are expected to impact photosynthetic capacity, that is, maximum gross primary productivity (GPPmax). However, the interplay between N and P availability with other critical resources on seasonal dynamics of ecosystem productivity remains largely unknown. In a Mediterranean tree–grass ecosystem, we established three landscape‐level (24 ha) nutrient addition treatments: N addition (NT), N and P addition (NPT), and a control site (CT). We analyzed the response of ecosystem to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations, and digital repeat photography. A set of metrics, including phenological transition dates (PTDs; timing of green‐up and dry‐down), slopes during green‐up and dry‐down period, and seasonal amplitude, were extracted from time series of GPPmax and used to represent the seasonality of vegetation activity. The seasonal amplitude of GPPmax was higher for NT and NPT than CT, which was attributed to changes in structure and physiology induced by fertilization. PTDs were mainly driven by rainfall and exhibited no significant differences among treatments during the green‐up period. Yet, both fertilized sites senesced earlier during the dry‐down period (17–19 days), which was more pronounced in the NT due to larger evapotranspiration and water usage. Fertilization also resulted in a faster increase in GPPmax during the green‐up period and a sharper decline in GPPmax during the dry‐down period, with less prominent decline response in NPT. Overall, we demonstrated seasonality of vegetation activity was altered after fertilization and the importance of nutrient–water interaction in such water‐limited ecosystems. With the projected warming‐drying trend, the positive effects of N fertilization induced by N deposition on GPPmax may be counteracted by an earlier and faster dry‐down in particular in areas where the N:P ratio increases, with potential impact on the carbon cycle of water‐limited ecosystems. [ABSTRACT FROM AUTHOR]

Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration ( RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error ( RMSE) and a 6% increase in the modeling efficiency ( EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. [ABSTRACT FROM AUTHOR]