scholarly journals No growth stimulation of Canada’s boreal forest under half-century of combined warming and CO2 fertilization

2016 ◽  
Vol 113 (52) ◽  
pp. E8406-E8414 ◽  
Author(s):  
Martin P. Girardin ◽  
Olivier Bouriaud ◽  
Edward H. Hogg ◽  
Werner Kurz ◽  
Niklaus E. Zimmermann ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boreal Forest ◽  
Spatial Patterns ◽  
Tree Growth ◽  
Hydrological Cycle ◽  
Forest Growth ◽  
Spatiotemporal Variability ◽  
Late 20Th Century ◽  
Growth Trends ◽  
Growth Variability

Considerable evidence exists that current global temperatures are higher than at any time during the past millennium. However, the long-term impacts of rising temperatures and associated shifts in the hydrological cycle on the productivity of ecosystems remain poorly understood for mid to high northern latitudes. Here, we quantify species-specific spatiotemporal variability in terrestrial aboveground biomass stem growth across Canada’s boreal forests from 1950 to the present. We use 873 newly developed tree-ring chronologies from Canada’s National Forest Inventory, representing an unprecedented degree of sampling standardization for a large-scale dendrochronological study. We find significant regional- and species-related trends in growth, but the positive and negative trends compensate each other to yield no strong overall trend in forest growth when averaged across the Canadian boreal forest. The spatial patterns of growth trends identified in our analysis were to some extent coherent with trends estimated by remote sensing, but there are wide areas where remote-sensing information did not match the forest growth trends. Quantifications of tree growth variability as a function of climate factors and atmospheric CO2 concentration reveal strong negative temperature and positive moisture controls on spatial patterns of tree growth rates, emphasizing the ecological sensitivity to regime shifts in the hydrological cycle. An enhanced dependence of forest growth on soil moisture during the late-20th century coincides with a rapid rise in summer temperatures and occurs despite potential compensating effects from increased atmospheric CO2 concentration.

scholarly journals Investigation of Precipitation Variability and Extremes Using Information Theory

2020 ◽  
Vol 4 (1) ◽  
pp. 14 ◽  
Author(s):  
Ravi Kumar Guntu ◽  
Ankit Agarwal
Keyword(s):  
Information Theory ◽  
Spatial Patterns ◽  
Hydrological Cycle ◽  
Rainfall Variability ◽  
Central India ◽  
Rainfall Amount ◽  
Spatiotemporal Variability ◽  
Spatial And Temporal Variability ◽  
Seasonal Scale ◽  
The Impact

Quantifying the spatiotemporal variability of rainfall is the principal component for the assessment of the impact of climate change on the hydrological cycle. A better understanding of the quantification of variability and its trend is vital for water resources planning and management. Therefore, a multitude of studies has been dedicated to quantifying the rainfall variability over the years. Despite their importance for modelling rainfall variability, the studies mainly focused on the amount of rainfall and its spatial patterns. The studies investigating the spatial and temporal variability of rainfall across Central India, in general, and at multiscale, in particular, are limited. In this study, we used a Standardized Variability Index (SVI), based on information theory to investigate the spatiotemporal variability of rainfall. SVI is independent of the temporal scale, length of the data and can compare the rainfall variability at multiple timescales. Distinct spatial patterns were observed for information entropies at the monthly and seasonal scale. Grid points with statistically significant trends were observed and vary from monthly to seasonal scale. There is an increase in the variability of rainfall amount from South to North, indicating that spread of the rainfall is high in the South when compared to North of Central India. Trend analysis revealed there is changing behavior in the rainfall amount as well as rainy days, showing an increase in variability of rainfall over Central India, hence the high probability of occurrence of extreme events in the near future.

scholarly journals Spatial pattern evaluation of a calibrated national hydrological model – a remote-sensing-based diagnostic approach

2017 ◽  
Vol 21 (12) ◽  
pp. 5987-6005 ◽  
Author(s):  
Gorka Mendiguren ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Hydrological Model ◽  
Temporal Dynamics ◽  
Remote Sensing Data ◽  
Spatiotemporal Variability ◽  
Eof Analysis ◽  
Area Index ◽  
Sensing Data

Abstract. Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land–atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds spatial features found in the spatial pattern of remote-sensing-based ET.

scholarly journals Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

2014 ◽  
Vol 11 (11) ◽  
pp. 3057-3068 ◽  
Author(s):  
X. Wu ◽  
F. Babst ◽  
P. Ciais ◽  
D. Frank ◽  
M. Reichstein ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Patterns ◽  
Water Availability ◽  
Vegetation Index ◽  
Crop Yields ◽  
Spatiotemporal Patterns ◽  
Spatiotemporal Variability ◽  
Simultaneous Increase ◽  
Ecosystem Productivity ◽  
Terrestrial Productivity

Abstract. Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975–2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

scholarly journals Seasonal Divergent Tree Growth Trends and Growth Variability along Drought Gradient over Northeastern China

Forests ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Fangzhong Shi ◽  
Xiuchen Wu ◽  
Xiaoyan Li ◽  
Pei Wang ◽  
Xiaofan Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
Tree Growth ◽  
Large Scale ◽  
Spatial Scales ◽  
Northeastern China ◽  
Spring Temperature ◽  
Growth Trends ◽  
Growth Variability ◽  
Different Seasons ◽  
Semi Arid

With the increasing temperature and intensified drought, global climate change has profound impacts on tree growth in temperate regions, which consequently regulates terrestrial-atmosphere biogeochemical processes and biophysical feedbacks. Thus, increasing numbers of studies have addressed the long-term annual trends in tree growth and their response to climate change at diverse spatial scales. However, the potential divergence in tree growth trends and growth variability (represented by coefficient of variance) in different seasons across large-scale climate gradients remains poorly understood. Here, we investigated the tree growth trends and growth variability in different seasons across diverse drought conditions in forested regions over northeastern China during the period 1982–2015, using both remote sensing observations and in situ tree-ring measurements. We found clear seasonal divergence in tree growth trends during 1982–2015, and the apparent increase was mainly observed in spring and autumn, attributed mainly to the increase in spring temperature and autumn solar radiation, respectively, but not in summer. The magnitudes of increasing trends in tree growth decrease with the increase of the multi-year average dryness index (MAI) in semi-arid areas (1.5 < MAI < 4.0) in all seasons. We further revealed that the interannual variability in tree growth was much larger in the semi-arid regions than in the humid and semi-humid regions in all seasons, and tree growth variability was significantly and negatively correlated with the variations in temperature and water deficit. Our findings improve our understanding of seasonal divergence in tree growth trends and provide new insights into spatial patterns in forest vulnerability in a warmer and drier climate.

scholarly journals Run to the hills: Forest growth responsiveness to drought increased at higher elevation during the late 20th century

2021 ◽  
Vol 772 ◽  
pp. 145286
Author(s):  
Marín Pompa-García ◽  
Marcos González-Cásares ◽  
Antonio Gazol ◽  
J. Julio Camarero
Keyword(s):  
20Th Century ◽  
Forest Growth ◽  
Late 20Th Century

scholarly journals Shedding New Light on Mountainous Forest Growth: A Cross-Scale Evaluation of the Effects of Topographic Illumination Correction on 25 Years of Forest Cover Change across Nepal

2021 ◽  
Vol 13 (11) ◽  
pp. 2131
Author(s):  
Jamon Van Den Hoek ◽  
Alexander C. Smith ◽  
Kaspar Hurni ◽  
Sumeet Saksena ◽  
Jefferson Fox
Keyword(s):  
Remote Sensing ◽  
Geographic Distribution ◽  
Classification Accuracy ◽  
Forest Cover ◽  
Forest Growth ◽  
Forest Cover Change ◽  
Scale Evaluation ◽  
Beneficial Effects ◽  
Affect Detection

Accurate remote sensing of mountainous forest cover change is important for myriad social and ecological reasons, but is challenged by topographic and illumination conditions that can affect detection of forests. Several topographic illumination correction (TIC) approaches have been developed to mitigate these effects, but existing research has focused mostly on whether TIC improves forest cover classification accuracy and has usually found only marginal gains. However, the beneficial effects of TIC may go well beyond accuracy since TIC promises to improve detection of low illuminated forest cover and thereby normalize measurements of the amount, geographic distribution, and rate of forest cover change regardless of illumination. To assess the effects of TIC on the extent and geographic distribution of forest cover change, in addition to classification accuracy, we mapped forest cover across mountainous Nepal using a 25-year (1992–2016) gap-filled Landsat time series in two ways—with and without TIC (i.e., nonTIC)—and classified annual forest cover using a Random Forest classifier. We found that TIC modestly increased classifier accuracy and produced more conservative estimates of net forest cover change across Nepal (−5.2% from 1992–2016) TIC. TIC also resulted in a more even distribution of forest cover gain across Nepal with 3–5% more net gain and 4–6% more regenerated forest in the least illuminated regions. These results show that TIC helped to normalize forest cover change across varying illumination conditions with particular benefits for detecting mountainous forest cover gain. We encourage the use of TIC for satellite remote sensing detection of long-term mountainous forest cover change.

scholarly journals Using a Groundwater Adjusted Water Balance Approach and Copulas to Evaluate Spatial Patterns and Dependence Structures in Remote Sensing Derived Evapotranspiration Products

2021 ◽  
Vol 13 (5) ◽  
pp. 853
Author(s):  
Mohsen Soltani ◽  
Julian Koch ◽  
Simon Stisen
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Spatial Pattern ◽  
Spatial Patterns ◽  
Principal Component ◽  
Small Scale ◽  
Dependence Structure ◽  
Test Case ◽  
Catchment Scale ◽  
Balance Approach

This study aims to improve the standard water balance evapotranspiration (WB ET) estimate, which is typically used as benchmark data for catchment-scale ET estimation, by accounting for net intercatchment groundwater flow in the ET calculation. Using the modified WB ET approach, we examine errors and shortcomings associated with the long-term annual mean (2002–2014) spatial patterns of three remote-sensing (RS) MODIS-based ET products from MODIS16, PML_V2, and TSEB algorithms at 1 km spatial resolution over Denmark, as a test case for small-scale, energy-limited regions. Our results indicate that the novel approach of adding groundwater net in water balance ET calculation results in a more trustworthy ET spatial pattern. This is especially relevant for smaller catchments where groundwater net can be a significant component of the catchment water balance. Nevertheless, large discrepancies are observed both amongst RS ET datasets and compared to modified water balance ET spatial pattern at the national scale; however, catchment-scale analysis highlights that difference in RS ET and WB ET decreases with increasing catchment size and that 90%, 87%, and 93% of all catchments have ∆ET < ±150 mm/year for MODIS16, PML_V2, and TSEB, respectively. In addition, Copula approach captures a nonlinear structure of the joint relationship with multiple densities amongst the RS/WB ET products, showing a complex dependence structure (correlation); however, among the three RS ET datasets, MODIS16 ET shows a closer spatial pattern to the modified WB ET, as identified by a principal component analysis also. This study will help improve the water balance approach by the addition of groundwater net in the ET estimation and contribute to better understand the true correlations amongst RS/WB ET products especially over energy-limited environments.

Tree growth across the Nepal Himalaya during the last four centuries

2017 ◽  
Vol 41 (4) ◽  
pp. 478-495 ◽  
Author(s):  
UK Thapa ◽  
S St. George ◽  
DK Kharal ◽  
NP Gaire
Keyword(s):  
Tree Ring ◽  
Tree Growth ◽  
Environmental Changes ◽  
Ring Width ◽  
High Elevation ◽  
Forest Growth ◽  
Tree Ring Width ◽  
Early 19Th Century ◽  
Tree Ring Data ◽  
Instrumental Records

The climate of Nepal has changed rapidly over the recent decades, but most instrumental records of weather and hydrology only extend back to the 1980s. Tree rings can provide a longer perspective on recent environmental changes, and since the early 2000s, a new round of field initiatives by international researchers and Nepali scientists have more than doubled the size of the country’s tree-ring network. In this paper, we present a comprehensive analysis of the current tree-ring width network for Nepal, and use this network to estimate changes in forest growth nation-wide during the last four centuries. Ring-width chronologies in Nepal have been developed from 11 tree species, and half of the records span at least 290 years. The Nepal tree-ring width network provides a robust estimate of annual forest growth over roughly the last four centuries, but prior to this point, our mean ring-width composite fluctuates wildly due to low sample replication. Over the last four centuries, two major events are prominent in the all-Nepal composite: (i) a prolonged and widespread growth suppression during the early 1800s; and (ii) heightened growth during the most recent decade. The early 19th century decline in tree growth coincides with two major Indonesian eruptions, and suggests that short-term disturbances related to climate extremes can exert a lasting influence on the vigor of Nepal’s forests. Growth increases since AD 2000 are mainly apparent in high-elevation fir, which may be a consequence of the observed trend towards warmer temperatures, particularly during winter. This synthesis effort should be useful to establish baselines for tree-ring data in Nepal and provide a broader context to evaluate the sensitivity or behavior of this proxy in the central Himalayas.

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