Weather and climate extremes substantially affect global- and regional-scale carbon (C) cycling, and thus spatially or temporally extended climatic extreme events jeopardize terrestrial ecosystem carbon sequestration. We illustrate the relevance of drought and/or heat events (“DHE”) for the carbon cycle and highlight underlying concepts and complex impact mechanisms. We review recent results, discuss current research needs and emerging research topics.

Amplification of the hydrologic cycle as a consequence of global warming is predicted to increase climate variability and the frequency and severity of droughts. Recent large‐scale drought and flooding over numerous continents provide unique opportunities to understand ecosystem responses to climatic extremes. In this study, we investigated the impacts of the early 21st century extreme hydroclimatic variations in southeastern Australia on phenology and vegetation productivity using Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index and Standardized Precipitation‐Evapotranspiration Index. Results revealed dramatic impacts of drought and wet extremes on vegetation dynamics, with abrupt between year changes in phenology. Drought resulted in widespread reductions or collapse in the normal patterns of seasonality such that in many cases there was no detectable phenological cycle during drought years. Across the full range of biomes examined, we found semiarid ecosystems to exhibit the largest sensitivity to hydroclimatic variations, exceeding that of arid and humid ecosystems. This result demonstrated the vulnerability of semiarid ecosystems to climatic extremes and potential loss of ecosystem resilience with future mega‐drought events. A skewed distribution of hydroclimatic sensitivity with aridity is of global biogeochemical significance because it suggests that current drying trends in semiarid regions will reduce hydroclimatic sensitivity and suppress the large carbon sink that has been reported during recent wet periods (e.g., 2011 La Niña).

Land surface phenological cycles of vegetation greening and browning are influenced by variability in climatic forcing. Quantitative spatial information on phenological cycles and their variability is important for agricultural applications, wildfire fuel accumulation, land management, land surface modeling, and climate change studies. Most phenology studies have focused on temperature-driven Northern Hemisphere systems, where phenology shows annually recurring patterns. However, precipitation-driven non-annual phenology of arid and semi-arid systems (i.e., drylands) received much less attention, despite the fact that they cover more than 30% of the global land surface. Here, we focused on Australia, a continent with one of the most variable rainfall climates in the world and vast areas of dryland systems, where a detailed phenological investigation and a characterization of the relationship between phenology and climate variability are missing. To fill this knowledge gap, we developed an algorithm to characterize phenological cycles, and analyzed geographic and climate-driven variability in phenology from 2000 to 2013, which included extreme drought and wet years. We linked derived phenological metrics to rainfall and the Southern Oscillation Index (SOI). We conducted a continent-wide investigation and a more detailed investigation over the Murray–Darling Basin (MDB), the primary agricultural area and largest river catchment of Australia. Results showed high inter- and intra-annual variability in phenological cycles across Australia. The peak of phenological cycles occurred not only during the austral summer, but also at any time of the year, and their timing varied by more than a month in the interior of the continent. The magnitude of the phenological cycle peak and the integrated greenness were most significantly correlated with monthly SOI within the preceding 12 months. Correlation patterns occurred primarily over northeastern Australia and within the MDB, predominantly over natural land cover and particularly in floodplain and wetland areas. Integrated greenness of the phenological cycles (surrogate of vegetation productivity) showed positive anomalies of more than 2 standard deviations over most of eastern Australia in 2009–2010, which coincided with the transition from the El Niño-induced decadal droughts to flooding caused by La Niña.

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO₂ and photosynthesis and in-situ flux tower measures. We show the 2010–11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010–11 net CO₂ uptake was highly transient with rapid dissipation through drought. The size of the 2010–11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011–12, and was nearly eliminated in 2012–13 (0.08 Pg). We further report evidence of an earlier 2000–01 large net CO₂ uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.

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 and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP.