Responses of Terrestrial Ecosystem to Climate Change: Results from Approach of Conditional Nonlinear Optimal Perturbation of Parameters

AbstractGlobal climate change likely alters the structure and function of vegetation and the stability of terrestrial ecosystems. It is therefore important to assess the factors controlling ecosystem resilience from local to global scales. Here we assess terrestrial vegetation resilience over the past 35 years using early warning indicators calculated from normalized difference vegetation index data. On a local scale we find that climate change reduced the resilience of ecosystems in 64.5% of the global terrestrial vegetated area. Temperature had a greater influence on vegetation resilience than precipitation, while climate mean state had a greater influence than climate variability. However, there is no evidence for decreased ecological resilience on larger scales. Instead, climate warming increased spatial asynchrony of vegetation which buffered the global-scale impacts on resilience. We suggest that the response of terrestrial ecosystem resilience to global climate change is scale-dependent and influenced by spatial asynchrony on the global scale.

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Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections

Environmental Research Letters ◽

10.1088/1748-9326/7/4/044008 ◽

2012 ◽

Vol 7 (4) ◽

pp. 044008 ◽

Cited By ~ 168

Author(s):

A Ahlström ◽

G Schurgers ◽

A Arneth ◽

B Smith

Keyword(s):

Climate Change ◽

Terrestrial Ecosystem ◽

Climate Change Projections ◽

Ecosystem Carbon

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A coupled multi-proxy and process modelling approach for extraction of quantitative terrestrial ecosystem information from speleothems

10.5194/egusphere-egu21-4761 ◽

2021 ◽

Author(s):

Franziska Lechleitner ◽

Christopher C. Day ◽

Oliver Kost ◽

Micah Wilhelm ◽

Negar Haghipour ◽

...

Keyword(s):

Climate Change ◽

Soil Respiration ◽

Western Europe ◽

Global Climate ◽

Terrestrial Ecosystem ◽

Terrestrial Ecosystems ◽

Clear Correlation ◽

Northern Spain ◽

Regional Temperature ◽

Global Carbon

Terrestrial ecosystems are intimately linked with the global climate system, but their response to ongoing and future anthropogenic climate change remains poorly understood. Reconstructing the response of terrestrial ecosystem processes over past periods of rapid and substantial climate change can serve as a tool to better constrain the sensitivity in the ecosystem-climate response.In this talk, we will present a new reconstruction of soil respiration in the temperate region of Western Europe based on speleothem carbon isotopes (&#948;13C). Soil respiration remains poorly constrained over past climatic transitions, but is critical for understanding the global carbon cycle and its response to ongoing anthropogenic warming. Our study builds upon two decades of speleothem research in Western Europe, which has shown clear correlation between &#948;13C and regional temperature reconstructions during the last glacial and the deglaciation, with exceptional regional coherency in timing, amplitude, and absolute &#948;13C variation. By combining innovative multi-proxy geochemical analysis (&#948;13C, Ca isotopes, and radiocarbon) on three speleothems from Northern Spain, and quantitative forward modelling of processes in soil, karst, and cave, we show how deglacial variability in speleothem &#948;13C is best explained by increasing soil respiration. Our study is the first to quantify and remove the effects of prior calcite precipitation (PCP, using Ca isotopes) and bedrock dissolution (open vs closed system, using the radiocarbon reservoir effect) from the speleothem &#948;13C signal to derive changes in respired &#948;13C over time. Our approach allows us to estimate the temperature sensitivity of soil respiration (Q10), which is higher than current measurements, suggesting that part of the speleothem signal may be related to a change in the composition of the soil respired &#948;13C. This is likely related to changing substrate through increasing contribution from vegetation biomass with the onset of the Holocene.These results highlight the exciting possibilities speleothems offer as a coupled archive for quantitative proxy-based reconstructions of climate and ecosystem conditions.

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Deriving SAR Soil Moisture Retrieval Algorithms and Soil Drainage Classification for Boreal Peatlands

10.5194/egusphere-egu21-6503 ◽

2021 ◽

Author(s):

Laura Bourgeau-Chavez ◽

Jeremy Graham ◽

Andrew Poley ◽

Dorthea Leisman ◽

Michael Battaglia

Keyword(s):

Climate Change ◽

Soil Moisture ◽

Land Surface ◽

Ground Surface ◽

Terrestrial Ecosystem ◽

Independent Study ◽

Additive Models ◽

Soil Drainage ◽

Boreal Peatlands ◽

Retrieval Algorithms

Eighty percent of global peatlands are distributed across the boreal and subarctic regions, storing an estimated 30% of earth&#8217;s soil organic carbon (1,016 to 1,105 Gt C) despite representing only about 3% of the global land surface. The accumulation of C in peatlands generally depends on hydrologic conditions that maintain saturated soils and impede rates of decomposition. Boreal Peatlands have provided rich reservoirs of stored C for millennia. However, with climate change, warming and drying patterns across the boreal and arctic are resulting in dramatic changes in ecosystems and putting these systems at risk of changing from a C sink to a source.&#160; Recent changes in climate including earlier springs, longer summers and changes in moisture patterns across the landscape, are affecting wildfire regimes of the boreal region including intensity, severity and frequency of wildfires. This in turn has potential to cause shifts in successional trajectories.&#160; Understanding how these changes in climate are affecting peatlands and their vulnerability to wildfire has been a focus of study of the research team since 2009. &#160;Soil moisture is one variable which can provide information to understand wildfire behavior including the depth of peat consumption in these wildfires but it also has a direct effect on post-fire successional trajectories. Further it is needed to understand methane emissions from peatlands.&#160; To develop the soil moisture retrieval algorithms, we studied a range of boreal peatland sites (bogs and fens) stratified across geographic regions from 2012-2014.&#160; We developed soil moisture retrieval algorithms from polarimetric C-band (5.7 cm wavelength) synthetic aperture radar (SAR) data.&#160; Peatlands have low enough aboveground biomass (<3.0 kg/m2) to allow this shorter wavelength SAR to penetrate the canopy to reach the ground surface.&#160; Data from over 60, 4 ha sites were collected over 3 seasons from Alaska and Michigan USA and Alberta Canada.&#160; Both multi-linear regressions and general additive models (GAM) were developed.&#160; Using both polarimetric SAR parameters that are sensitive to vegetation structure and parameters most sensitive to surface soil moisture in the models provided the best results.&#160; GAM models were tested in an independent study area, Northwest Territories (NWT), Canada.&#160; The sites of NWT were sampled in 2016-2019 coincident to Radarsat-2 polarimetric image collections.&#160; The high accuracy results will be presented as well as methods developed to use multidate C-band data from Sentinel-1 to classify soil drainage (well drained to poorly drained) in recently burned peatlands.&#160; These products are being used in a fire effects and emissions model, CanFIRE, as we parameterize it for peatlands; as well as the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) to understand the effects of wildfire and hydrology on peatland ecosystems.&#160; Characterization and quantification of boreal peatlands in global C cycling is critical for proper accounting given that peatlands play a significant role in sequestering and releasing large amounts of C. The ability to retrieve soil moisture from C-band SAR, therefore, provides a means to monitor a key variable in scaling C flux estimates as well as understanding the vulnerability and resiliency of boreal peatlands to climate change.&#160;

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Spatial-temporal changes in river runoff and terrestrial ecosystem water retention under 1.5 °C and 2 °C warming scenarios across China

10.5194/esd-2017-96 ◽

2017 ◽

Author(s):

Ran Zhai ◽

Fulu Tao ◽

Zhihui Xu

Keyword(s):

Climate Change ◽

Interannual Variability ◽

River Runoff ◽

Water Retention ◽

Terrestrial Ecosystem ◽

Maximum Temperature ◽

Climate Scenarios ◽

Warming Scenario ◽

Basin Scale ◽

The Impact

Abstract. The Paris Agreement set a long-term temperature goal of holding the global average temperature increase to below 2.0 ℃ above pre-industrial levels, and pursuing efforts to limit this to 1.5 ℃, it is therefore important to understand the impacts of climate change under 1.5 ℃ and 2.0 ℃ warming scenarios for climate adaptation and mitigation. Here, climate scenarios by four Global Circulation Models (GCMs) for the baseline (2006–2015), 1.5 ℃ and 2.0 ℃ warming scenarios (2106–2115) were used to drive the validated Variable Infiltration Capacity (VIC) hydrological model to investigate the impacts of global warming on river runoff and Terrestrial Ecosystem Water Retention (TEWR) in China. The trends in annual mean temperature, precipitation, river runoff and TEWR were analysed at the grid and basin scale. Results showed that there were large uncertainties in climate scenarios from the different GCMs, which led to large uncertainties in the impact assessment. The differences among the four GCMs were larger than differences between the two warming scenarios. The interannual variability of river runoff increased notably in areas where it was projected to increase, and the interannual variability increased notably from 1.5 ℃ warming scenario to 2.0 ℃ warming scenario. By contrast, TEWR would remain relatively stable. Both extreme low and high river runoff would increase under the two warming scenarios in most areas in China, with high river runoff increasing more. And the risk of extreme river runoff events would be higher under 2.0 ℃ warming scenario than under 1.5 ℃ warming scenario in term of both extent and intensity. River runoff was significantly positively correlated to precipitation, while increase in maximum temperature would generally cause river runoff to decrease through increasing evapotranspiration. Likewise, precipitation also played a dominant role in affecting TEWR. Our findings highlight climate change mitigation and adaptation should be taken to reduce the risks of hydrological extreme events.

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