Differentiating moss from higher plants is critical in studying the carbon cycle of the boreal biome

Yuan, Wenping; Liu, Shuguang; Dong, Wenjie; Liang, Shunlin; Zhao, Shuqing; Chen, Jingming; Xu, Wenfang; Li, Xianglan; Barr, Alan G.; Black, T. Andrew; Yan, Wende; Goulden, Michael L.; Kulmala, Liisa; Lindroth, Anders; Margolis, Hank A.; Matsuura, Yukiko; Moors, E.J.; Molen, M. K. van der; Ohta, Takeshi; Pilegaard, Kim; Varlagin, Andrej; Vesala, Timo

doi:10.1038/ncomms5270

Cited by 48 publications

(29 citation statements)

References 60 publications

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“…In forests with incomplete canopy closure, which tends to be the case at high latitudes (Scheffer et al., ), a significant portion of the remotely sensed imagery is from understory vegetation, which may show different responses to climate and relationships with productivity (McDowell et al., ; Yuan et al., ). Indeed, tree‐level growth is not always correlated with ecosystem productivity (Gea‐Izquierdo et al., ).…”

Section: Discussionmentioning

confidence: 99%

“…For illustration purposes, we only show the combination of NDVI products and inventory data that resulted in long time series, and only the EWS metrics that displayed consistent relationships. Each heat map has a separate scale centered around zero the remotely sensed imagery is from understory vegetation, which may show different responses to climate and relationships with productivity Yuan et al, 2014). Indeed, treelevel growth is not always correlated with ecosystem productivity (Gea-Izquierdo et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

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Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

Rogers

Solvik

Hogg

et al. 2018

Global Change Biology

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Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

Rogers

Solvik

Hogg

et al. 2018

Global Change Biology

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“…The understanding of how these factors influence GPP remains unclear due to the complex interactions of these factors and the vegetation [27]. Therefore, the performance of LUE models depends on how a model integrates environmental variables to describe the mechanisms that drive the ecosystem processes [28,29]. Model inter-comparison can provide insights to help resolve model discrepancies in GPP estimates and improve our understanding of the terrestrial production.…”

Section: Introductionmentioning

confidence: 99%

Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

et al. 2014

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Terrestrial gross primary production (GPP) is the largest global CO 2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE) models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000-2010 varied from 95.10 to 139.71 Pg C·yr −1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

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“…Vascular plants could take hundreds of years to es-tablish once climatic conditions become appropriate due to the large timescales involved in soil development. The vegetation at Bayelva is largely mosses and lichens, which can grow in nutrient-poor conditions but photosynthesise more slowly than vascular plants (Yuan et al, 2014). Therefore, to simulate the CO 2 flux at a very nutrient-limited site, it is necessary to have a different PFT that represents the low-nutrient but low-GPP vegetation such as moss and to include nutrient limitation for the other PFTs.…”

Section: Nutrient Limitation and Mossmentioning

confidence: 99%

Carbon stocks and fluxes in the high latitudes: using site-level data to evaluate Earth system models

et al. 2017

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Abstract. It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra carbon stocks and fluxes in three land surface schemes that each form part of major Earth system models (JSBACH, Germany; JULES, UK; ORCHIDEE, France). We use a site-level approach in which comprehensive, high-frequency datasets allow us to disentangle the importance of different processes. The models have improved physical permafrost processes and there is a reasonable correspondence between the simulated and measured physical variables, including soil temperature, soil moisture and snow.We show that if the models simulate the correct leaf area index (LAI), the standard C3 photosynthesis schemes produce the correct order of magnitude of carbon fluxes. Therefore, simulating the correct LAI is one of the first priorities. LAI depends quite strongly on climatic variables alone, as we see by the fact that the dynamic vegetation model can simulate most of the differences in LAI between sites, based almost entirely on climate inputs. However, we also identify an influence from nutrient limitation as the LAI becomes too large at some of the more nutrient-limited sites. We conclude that including moss as well as vascular plants is of primary importance to the carbon budget, as moss contributes a large fraction to the seasonal CO 2 flux in nutrient-limited conditions. Moss photosynthetic activity can be strongly influenced by the moisture content of moss, and the carbon uptake can be significantly different from vascular plants with a similar LAI.The soil carbon stocks depend strongly on the rate of input of carbon from the vegetation to the soil, and our analysis suggests that an improved simulation of photosynthesis would also lead to an improved simulation of soil carbon stocks. However, the stocks are also influenced by soil carbon burial (e.g. through cryoturbation) and the rate of heterotrophic respiration, which depends on the soil physical state. More detailed below-ground measurements are needed to fully evaluate biological and physical soil processes. Furthermore, even if these processes are well modelled, the soil carbon profiles cannot resemble peat layers as peat accumulation processes are not represented in the models.Thus, we identify three priority areas for model development: (1) dynamic vegetation including (a) climate and (b) nutrient limitation effects; (2) adding moss as a plant functional type; and an (3) improved vertical profile of soil carbon including peat processes.

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Differentiating moss from higher plants is critical in studying the carbon cycle of the boreal biome

Cited by 48 publications

References 60 publications

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

Carbon stocks and fluxes in the high latitudes: using site-level data to evaluate Earth system models

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