Regional‐scale phenology modeling based on meteorological records and remote sensing observations

Yang, Xi; Mustard, John F.; Tang, Jianwu; Hong, Xu

doi:10.1029/2012jg001977

Cited by 82 publications

(81 citation statements)

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“…1 in their general formulation have been proposed. These models rely on the use of low temperatures and photoperiods as main environmental cues and generally outperform threshold-type models (Delpierre et al 2009a;Yang et al 2012;Archetti et al 2013) but remain less accurate than budburst models, partially because the uncertainties associated with observed leaf senescence dates are considerably greater than the uncertainties regarding flowering and leaf unfolding dates.…”

Section: Modeling the Phenology Of Leaves And The Timing Of Floweringmentioning

confidence: 99%

Temperate and boreal forest tree phenology: from organ-scale processes to terrestrial ecosystem models

Delpierre

Vitasse

Chuine

et al. 2016

Annals of Forest Science

234

192

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Abstract& Key message We demonstrate that, beyond leaf phenology, the phenological cycles of wood and fine roots present clear responses to environmental drivers in temperate and boreal trees. These drivers should be included in terrestrial ecosystem models. & Context In temperate and boreal trees, a dormancy period prevents organ development during adverse climatic conditions. Whereas the phenology of leaves and flowers has received considerable attention, to date, little is known regarding the phenology of other tree organs such as wood, fine roots, fruits, and reserve compounds. & Aims Here, we review both the role of environmental drivers in determining the phenology of tree organs and the models used to predict the phenology of tree organs in temperate and boreal forest trees. & Results Temperature is a key driver of the resumption of tree activity in spring, although its specific effects vary among organs. There is no such clear dominant environmental cue involved in the cessation of tree activity in autumn and in the onset of dormancy, but temperature, photoperiod, and water stress appear as prominent factors. The phenology of a given organ is, to a certain extent, influenced by processes in distant organs. & Conclusion Inferring past trends and predicting future trends of tree phenology in a changing climate requires specific phenological models developed for each organ to consider the phenological cycle as an ensemble in which the environmental cues that trigger each phase are also indirectly involved in the subsequent phases. Incorporating such models into terrestrial ecosystem models (TEMs) would likely improve the accuracy of their predictions. The extent to which the coordination of the phenologies of tree organs will be affected in a changing climate deserves further research.

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Section: Modeling the Phenology Of Leaves And The Timing Of Floweringmentioning

confidence: 99%

Temperate and boreal forest tree phenology: from organ-scale processes to terrestrial ecosystem models

Delpierre

Vitasse

Chuine

et al. 2016

Annals of Forest Science

234

192

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“…Remote sensing imagery has been widely used over the past two decades for monitoring vegetation dynamics at regional to global scales in view of its synoptic coverage and repeated temporal sampling (Reed et al, 1994;Zhang et al, 2003;Julien and Sobrino, 2009;Yang et al, 2012;among many others). This approach also facilitates other kinds of studies that seek to explore the driving factors behind phenology change in the context of climate change Wang et al, 2011;Shen et al, 2011).…”

Section: H Liu Et Al: Soil Moisture Controls On Patterns Of Grass Gmentioning

confidence: 99%

Soil moisture controls on patterns of grass green-up in Inner Mongolia: an index based approach

Liu

Tian

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions. It is often represented in terms of soil moisture in small-scale studies, whereas it tends to be represented by precipitation in large-scale (e.g., regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology. Its potential advantage and applicability needs to be demonstrated at regional scales. The paper presents a data-based regional study of the effectiveness of novel water and temperature-based indices to predict spring vegetation greenup dates based on the Normalized Difference Vegetation Index (NDVI) observations in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC (Variable Infiltration Capacity), is employed to generate a soil moisture database across the region. In addition to a standard index based on temperature, two potential hydrologybased indices for prediction of spring onset dates are defined, based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil-moisture-derived potential onset date exhibits a significantly better correlation as a function of increasing aridity compared to that based on precipitation. In this way the soil-moisture-based index is demonstrated to be superior to the precipitation-based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water-based) indices were superior to the thermal (temperature-based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control on average. The understanding about the relative controls on grassland phenology and the effectiveness of alternative indices to capture these controls are important for future studies of vegetation phenology change under climate change.

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“…An intercomparison of SOS retrieved using 10 satellite methods shows that the difference between individual methods can be as much as two months; and two methods were more closely related to ground observations than other methods [27]. Although validation against ground observations has been conducted for remotely sensed phenological metrics in many studies [5,13,14,26,27], the validation process is not standardized because the phenology-monitoring method usually varies among sites, and even the same dataset can be processed differently. More importantly, remotely sensed phenological metrics have not been evaluated in the context of DEMs.…”

Section: Introductionmentioning

confidence: 99%

“…For example, a comprehensive comparison of existing phenological models across geographic zones may help reduce the structural uncertainties [13]. Moreover, modeling studies at the regional scale demonstrated that, due to the difference in species type and composition, forests at different locations do not share common parameters, such as base temperature for growing degree day (GDD) calculation [13,14]. Thus, location-specific parameterization has the potential to reduce the uncertainty associated with model parameters.…”

Section: Introductionmentioning

confidence: 99%

“…Phenological models can potentially be improved by reducing the uncertainties that stem from model structure, model parameters, or drivers [12]. For example, a comprehensive comparison of existing phenological models across geographic zones may help reduce the structural uncertainties [13]. Moreover, modeling studies at the regional scale demonstrated that, due to the difference in species type and composition, forests at different locations do not share common parameters, such as base temperature for growing degree day (GDD) calculation [13,14].…”

Section: Introductionmentioning

confidence: 99%

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Evaluating Remotely Sensed Phenological Metrics in a Dynamic Ecosystem Model

2014

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Vegetation phenology plays an important role in regulating processes of terrestrial ecosystems. Dynamic ecosystem models (DEMs) require representation of phenology to simulate the exchange of matter and energy between the land and atmosphere. Location-specific parameterization with phenological observations can potentially improve the performance of phenological models embedded in DEMs. As ground-based phenological observations are limited, phenology derived from remote sensing can be used as an alternative to parameterize phenological models. It is important to evaluate to what extent remotely sensed phenological metrics are capturing the phenology observed on the ground. We evaluated six methods based on two vegetation indices (VIs) (i.e., Normalized Difference Vegetation Index and Enhanced Vegetation Index) for retrieving the phenology of temperate forest in the Agro-IBIS model. First, we compared the remotely sensed phenological metrics with observations at Harvard Forest and found that most of the methods have large biases regardless of the VI used. Only two methods for the leaf onset and one method for the leaf offset showed a moderate performance. When remotely sensed phenological metrics were used to parameterize phenological models, the bias is maintained, and errors propagate to predictions of gross primary productivity and net ecosystem production. Our results show that Agro-IBIS has different sensitivities to leaf onset and offset in terms of carbon assimilation, suggesting it might be better to examine the respective impact of leaf onset and offset rather than the overall impact of the growing season length.

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Regional‐scale phenology modeling based on meteorological records and remote sensing observations

Cited by 82 publications

References 100 publications

Temperate and boreal forest tree phenology: from organ-scale processes to terrestrial ecosystem models

Temperate and boreal forest tree phenology: from organ-scale processes to terrestrial ecosystem models

Soil moisture controls on patterns of grass green-up in Inner Mongolia: an index based approach

Evaluating Remotely Sensed Phenological Metrics in a Dynamic Ecosystem Model

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