Combined analysis of tree rings and MODIS images to evaluate beech forest productivity along geographic gradients

2020 ◽  
Author(s):  
Luca Di Fiore ◽  
Gianluca Piovesan ◽  
Michele Baliva ◽  
Alfredo Di Filippo
Keyword(s):  
Tree Ring ◽  
Spatial Resolution ◽  
Vegetation Indices ◽  
Growing Season ◽  
Forest Productivity ◽  
Tree Cover ◽  
Multispectral Images ◽  
Continental Scale ◽  
Tree Ring Data ◽  
The Mean

<p>Remote sensing is widely used for monitoring vegetation status and ecosystem productivity. The increasing interest in connecting satellite vegetation indices to actual forest productivity has led to explore their relationship mainly at coarse spatial resolution and continental scale. The aim of this study is to find a connection and predict tree growth using medium resolution multispectral images and tree ring data for a sample of Italian and Austrian beech forests along latitudinal and altitudinal gradients. Beech tree ring data were collected and analyzed during the last 20 years, recording tree positions with a GPS device. MODIS pre-composite 250 m 16 days images (MOD13Q1) from 2000 to 2018 were first re-projected and quality checked using the MODIS quality assessment. Vegetation indices (NDVI and EVI) were extracted within a distance of 750 meters from every site centroid. Only deciduous forests (assessed by Corine Land Cover) with a dense canopy cover (assessed by Global Forest Change tree cover) were selected. Eight different phenology metrics were calculated using a threshold method and a modified one and then correlated with tree ring data (Basal Area Increment, BAI). The overall network and the relationship between metrics were characterized first with a Principal Component Analysis (PCA), and then evaluating the mean phenology, exploring its relationship with environmental variables (elevation, temperature). Last, the model for predicting BAI at every site was calculated for the period 2000-2009 using the metrics as predictors in a multiple linear regression. Two group of metrics were identified from PCA: the first is made of metrics based on dates (named DOY, e.g. start of growing season), the second on the vegetation index values (named VALUE, e.g. peak value,). BAI was modeled using as predictors the highest correlate from each of the two groups of metrics. BAI predictions for every site were generally significant: the 61% of the sites had at least one significant predictor, with a mean R-squared of 0.55 over the 41 sampled sites. DOY metrics were significantly related to altitude and temperature. Because of the wide latitudinal gradient of the study sites, mean annual temperatures showed higher correlations than the altitude with the DOY metrics. The mean growing season was longer for warm sites at low altitude. The relation between multispectral images and beech populations actual growth at medium spatial resolution is consistent even for those sites that are in complex environmental conditions, making possible to predict the annual diameter growth.</p>

scholarly journals A 368-year maximum temperature reconstruction based on tree-ring data in the northwestern Sichuan Plateau (NWSP), China

2016 ◽  
Vol 12 (7) ◽  
pp. 1485-1498 ◽  
Author(s):  
Liangjun Zhu ◽  
Yuandong Zhang ◽  
Zongshan Li ◽  
Binde Guo ◽  
Xiaochun Wang
Keyword(s):  
Tree Ring ◽  
Land Surface ◽  
Temperature Reconstruction ◽  
Temperature Variability ◽  
Ice Age ◽  
Maximum Temperature ◽  
Tree Ring Data ◽  
The Mean ◽  
Extreme Cold ◽  
The 19Th Century

Abstract. We present a reconstruction of July–August mean maximum temperature variability based on a chronology of tree-ring widths over the period AD 1646–2013 in the northern part of the northwestern Sichuan Plateau (NWSP), China. A regression model explains 37.1 % of the variance of July–August mean maximum temperature during the calibration period from 1954 to 2012. Compared with nearby temperature reconstructions and gridded land surface temperature data, our temperature reconstruction had high spatial representativeness. Seven major cold periods were identified (1708–1711, 1765–1769, 1818–1821, 1824–1828, 1832–1836, 1839–1842, and 1869–1877), and three major warm periods occurred in 1655–1668, 1719–1730, and 1858–1859 from this reconstruction. The typical Little Ice Age climate can also be well represented in our reconstruction and clearly ended with climatic amelioration at the late of the 19th century. The 17th and 19th centuries were cold with more extreme cold years, while the 18th and 20th centuries were warm with less extreme cold years. Moreover, the 20th century rapid warming was not obvious in the NWSP mean maximum temperature reconstruction, which implied that mean maximum temperature might play an important and different role in global change as unique temperature indicators. Multi-taper method (MTM) spectral analysis revealed significant periodicities of 170-, 49–114-, 25–32-, 5.7-, 4.6–4.7-, 3.0–3.1-, 2.5-, and 2.1–2.3-year quasi-cycles at a 95 % confidence level in our reconstruction. Overall, the mean maximum temperature variability in the NWSP may be associated with global land–sea atmospheric circulation (e.g., ENSO, PDO, or AMO) as well as solar and volcanic forcing.

scholarly journals SHCal20 Southern Hemisphere Calibration, 0–55,000 Years cal BP

Radiocarbon ◽  
2020 ◽  
Vol 62 (4) ◽  
pp. 759-778 ◽  
Author(s):  
Alan G Hogg ◽  
Timothy J Heaton ◽  
Quan Hua ◽  
Jonathan G Palmer ◽  
Chris SM Turney ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Tree Ring ◽  
Calibration Curve ◽  
Data Sets ◽  
Errors In Variables ◽  
Time Intervals ◽  
Tree Ring Data ◽  
The Mean ◽  
Statistical Approaches

ABSTRACTEarly researchers of radiocarbon levels in Southern Hemisphere tree rings identified a variable North-South hemispheric offset, necessitating construction of a separate radiocarbon calibration curve for the South. We present here SHCal20, a revised calibration curve from 0–55,000 cal BP, based upon SHCal13 and fortified by the addition of 14 new tree-ring data sets in the 2140–0, 3520–3453, 3608–3590 and 13,140–11,375 cal BP time intervals. We detail the statistical approaches used for curve construction and present recommendations for the use of the Northern Hemisphere curve (IntCal20), the Southern Hemisphere curve (SHCal20) and suggest where application of an equal mixture of the curves might be more appropriate. Using our Bayesian spline with errors-in-variables methodology, and based upon a comparison of Southern Hemisphere tree-ring data compared with contemporaneous Northern Hemisphere data, we estimate the mean Southern Hemisphere offset to be 36 ± 27 14C yrs older.

Dendroclimatology and Dendroecology

1971 ◽  
Vol 1 (4) ◽  
pp. 419-449 ◽  
Author(s):  
Harold C. Fritts
Keyword(s):  
Tree Ring ◽  
Tree Rings ◽  
Climatic Factors ◽  
Physiological Activity ◽  
Ring Width ◽  
Growing Season ◽  
Dry Matter Accumulation ◽  
New Developments ◽  
Cambial Age ◽  
Tree Ring Data

Dendrochronology is the science of dating annual growth layers (rings) in woody plants. Two related subdisciplines are dendroclimatology and dendroecology. The former uses the information in dated rings to study problems of present and past climates, while the latter deals with changes in the local environment rather than regional climate.Successful applications of dendroclimatology and dendroecology depend upon careful stratification. Ring-width samples are selected from trees on limiting sites, where widths of growth layers vary greatly from one year to the next (sensitivity) and autocorrelation of the widths is not high. Rings also must be cross-dated and sufficiently replicated to provide precise dating. This selection and dating assures that the climatic information common to all trees, which is analogous to the “signal”, is large and properly placed in time. The random error or nonclimatic variations in growth, among trees, is analogous to “noise” and is reduced when ring-width indices are averaged for many trees.Some basic facts about the growth are presented along with a discussion of important physiological processes operating throughout the roots, stems, and leaves. Certain gradients associated with tree height, cambial age, and physiological activity control the size of the growth layers as they vary throughout the tree. These biological gradients interact with environmental variables and complicate the task of modeling the relationships linking growth with environment.Biological models are described for the relationships between variations in ring widths from conifers on arid sites, and variations in temperature and precpitation. These climatic factors may influence the tree at any time in the year. Conditions preceding the growing season sometimes have a greater influence on ring width than conditions during the growing season, and the relative effects of these factors on growth vary with latitude, altitude, and differences in factors of the site. The effects of some climatic factors on growth are negligible during certain times of the year, but important at other times. Climatic factors are sometimes directly related to growth and at other times are inversely related to growth. Statistical methods are described for ascertaining these differences in the climatic response of trees from different sites.A practical example is given of a tree-ring study and the mechanics are described for stratification and selection of tree-ring materials, for laboratory preparation, for cross-dating, and for computer processing. Several methods for calibration of the ring-width data with climatic variation are described. The most recent is multivariate analysis, which allows simultaneous calibration of a variety of tree-ring data representing different sites with a number of variables of climate.Several examples of applications of tree-ring analysis to problems of environment and climate are described. One is a specification from tree rings of anomalies in atmosphere circulation for a portion of the Northern Hemisphere since 1700 A.D. Another example treats and specifies past conditions in terms of conditional probabilities. Other methods of comparing present climate with past climate are described along with new developments in reconstructing past hydrologic conditions from tree rings.Tree-ring studies will be applied in the future to problems of temperate and mesic environments, and to problems of physiological, genetic, and anatomical variations within and among trees. New developments in the use of X-ray techniques will facilitate the measurement and study of cell size and cell density. Tree rings are an important source of information on productivity and dry-matter accumulation at various sites. Some tree-ring studies will deal with environmental pollution. Statistical developments will improve estimation of certain past anomalies in weather factors and the reconstructtion of atmosphere circulation associated with climate variability and change. Such information should improve chances for measuring and assessing the possibility of inadvertent modification of climate by man.

scholarly journals Assessing the Effect of Real Spatial Resolution of In Situ UAV Multispectral Images on Seedling Rapeseed Growth Monitoring

2020 ◽  
Vol 12 (7) ◽  
pp. 1207 ◽  
Author(s):  
Jian Zhang ◽  
Chufeng Wang ◽  
Chenghai Yang ◽  
Tianjin Xie ◽  
Zhao Jiang ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Crop Growth ◽  
Growth Monitoring ◽  
Multispectral Images ◽  
Area Index ◽  
Uav Images

The spatial resolution of in situ unmanned aerial vehicle (UAV) multispectral images has a crucial effect on crop growth monitoring and image acquisition efficiency. However, existing studies about optimal spatial resolution for crop monitoring are mainly based on resampled images. Therefore, the resampled spatial resolution in these studies might not be applicable to in situ UAV images. In order to obtain optimal spatial resolution of in situ UAV multispectral images for crop growth monitoring, a RedEdge Micasense 3 camera was installed onto a DJI M600 UAV flying at different heights of 22, 29, 44, 88, and 176m to capture images of seedling rapeseed with ground sampling distances (GSD) of 1.35, 1.69, 2.61, 5.73, and 11.61 cm, respectively. Meanwhile, the normalized difference vegetation index (NDVI) measured by a GreenSeeker (GS-NDVI) and leaf area index (LAI) were collected to evaluate the performance of nine vegetation indices (VIs) and VI*plant height (PH) at different GSDs for rapeseed growth monitoring. The results showed that the normalized difference red edge index (NDRE) had a better performance for estimating GS-NDVI (R2 = 0.812) and LAI (R2 = 0.717), compared with other VIs. Moreover, when GSD was less than 2.61 cm, the NDRE*PH derived from in situ UAV images outperformed the NDRE for LAI estimation (R2 = 0.757). At oversized GSD (≥5.73 cm), imprecise PH information and a large heterogeneity within the pixel (revealed by semi-variogram analysis) resulted in a large random error for LAI estimation by NDRE*PH. Furthermore, the image collection and processing time at 1.35 cm GSD was about three times as long as that at 2.61 cm. The result of this study suggested that NDRE*PH from UAV multispectral images with a spatial resolution around 2.61 cm could be a preferential selection for seedling rapeseed growth monitoring, while NDRE alone might have a better performance for low spatial resolution images.

scholarly journals A 368-year maximum temperature reconstruction based on tree ring data in northwest Sichuan Plateau (NWSP), China

2016 ◽  
Author(s):  
Liangjun Zhu ◽  
Yuandong Zhang ◽  
Zongshan Li ◽  
Binde Guo ◽  
Xiaochun Wang
Keyword(s):  
Tree Ring ◽  
Land Surface ◽  
Temperature Reconstruction ◽  
Temperature Variability ◽  
Maximum Temperature ◽  
Spatial Correlations ◽  
Calibration Period ◽  
Tree Ring Data ◽  
Temperature Reconstructions ◽  
The Mean

Abstract. We present a reconstruction of July–August mean maximum temperature variability for northern West Sichuan Plateau (NWSP), China based on a chronology of tree-ring widths over the period 1646–2013 AD. A regression model explains 37.1 % of the variance of July–August mean maximum temperature during the calibration period from 1954 to 2012. Seven major cold periods were identified including 1708–1711, 1765–1769, 1818–1821, 1824–1828, 1832–1836, 1839–1842 and 1869–1877, and three major warm periods occurred between 1655–1668, 1719–1730 and 1858–1859 in our reconstruction. Comparison with other nearby temperature reconstructions and spatial correlations with gridded land surface temperature dates revealed that our temperature reconstruction has high spatial representativeness. 20th century rapid warming wasn’t obvious in the NWSP mean maximum temperature reconstruction, which implied that mean maximum temperature might play an important and different role in global change as unique temperature indicators. Multi-taper method (MTM) spectral analysis revealed significant periodicities of 170-, 49–114-, 25–32-, 5.7-, 4.6–4.7-, 3.0–3.1-, 2.5- and 2.1–2.3-year quasi-cycles at a 95 % confidence level. The mean maxi mum temperature variability in northwest Sichuan may be affected by ENSO, PDO, AMO and solar activity.

scholarly journals New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data

2017 ◽  
Vol 114 (27) ◽  
pp. 6966-6971 ◽  
Author(s):  
Bao Yang ◽  
Minhui He ◽  
Vladimir Shishov ◽  
Ivan Tychkov ◽  
Eugene Vaganov ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Tibetan Plateau ◽  
Tree Ring ◽  
Remote Sensing Data ◽  
Growing Season ◽  
The Tibetan Plateau ◽  
Vegetation Phenology ◽  
Sensing Data ◽  
Tree Ring Data

Phenological responses of vegetation to climate, in particular to the ongoing warming trend, have received much attention. However, divergent results from the analyses of remote sensing data have been obtained for the Tibetan Plateau (TP), the world’s largest high-elevation region. This study provides a perspective on vegetation phenology shifts during 1960–2014, gained using an innovative approach based on a well-validated, process-based, tree-ring growth model that is independent of temporal changes in technical properties and image quality of remote sensing products. Twenty composite site chronologies were analyzed, comprising about 3,000 trees from forested areas across the TP. We found that the start of the growing season (SOS) has advanced, on average, by 0.28 d/y over the period 1960–2014. The end of the growing season (EOS) has been delayed, by an estimated 0.33 d/y during 1982–2014. No significant changes in SOS or EOS were observed during 1960–1981. April–June and August–September minimum temperatures are the main climatic drivers for SOS and EOS, respectively. An increase of 1 °C in April–June minimum temperature shifted the dates of xylem phenology by 6 to 7 d, lengthening the period of tree-ring formation. This study extends the chronology of TP phenology farther back in time and reconciles the disparate views on SOS derived from remote sensing data. Scaling up this analysis may improve understanding of climate change effects and related phenological and plant productivity on a global scale.

scholarly journals Detrending ability of several regression equations in tree-ring research: a case study based on tree-ring data of Norway spruce (Picea abies [L.])

2011 ◽  
Vol 57 (No. 11) ◽  
pp. 491-499 ◽  
Author(s):  
M. Bošeľa ◽  
L. Kulla ◽  
R. Marušák
Keyword(s):  
Norway Spruce ◽  
Tree Ring ◽  
Goodness Of Fit ◽  
Ring Width ◽  
Regression Equations ◽  
Growth Responses ◽  
Growth Trends ◽  
Tree Ring Data ◽  
The Mean ◽  
Similar Growth

  The aim of this study was to investigate tree-ring width variability and to distinguish groups of trees with similar growth trends in order to study tree growth responses to various stand and site conditions. The methods of cluster analysis were employed for this purpose. Four distinct groups of trees were identified. For each group, the mean tree-ring curve was calculated in order to look for the main signals that distinguish the groups from one another. The idea behind this was to divide the samples into homogeneous groups with similar growth trends, representing typical examples of variability of the studied Norway spruce population. In the next step, several regression functions were studied and compared for their ability to fit the ring-width-age data applied to the mean ring-width curve of each group. Fischer’s F-test was used to test the differences in goodness of fit between the equations in each group. From all examined/applied equations, smoothing spline, polynomial of degree 5, and Šmelko-Burgan functions were found to be the most universal and suitable for detrending of all examined ring width curves. Hugershoff function was found to be suitable for curves with one local maximum only. Exponential and Korf’s functions were unsatisfactory for the purposes of tree ring curves detrending.

scholarly journals Supporting Restoration Decisions through Integration of Tree-Ring and Modeling Data: Reconstructing Flow and Salinity in the San Francisco Estuary over the Past Millennium

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2139
Author(s):  
Paul H. Hutton ◽  
David M. Meko ◽  
Sujoy B. Roy
Keyword(s):  
San Francisco ◽  
Tree Ring ◽  
San Francisco Estuary ◽  
Salinity Intrusion ◽  
Estuarine Ecosystem ◽  
Freshwater Flow ◽  
The Past ◽  
Decadal Scale ◽  
Tree Ring Data ◽  
Past Millennium

This work presents updated reconstructions of watershed runoff to San Francisco Estuary from tree-ring data to AD 903, coupled with models relating runoff to freshwater flow to the estuary and salinity intrusion. We characterize pre-development freshwater flow and salinity conditions in the estuary over the past millennium and compare this characterization with contemporary conditions to better understand the magnitude and seasonality of changes over this time. This work shows that the instrumented flow record spans the range of runoff patterns over the past millennium (averaged over 5, 10, 20 and 100 years), and thus serves as a reasonable basis for planning-level evaluations of historical hydrologic conditions in the estuary. Over annual timescales we show that, although median freshwater flow to the estuary has not changed significantly, it has been more variable over the past century compared to pre-development flow conditions. We further show that the contemporary period is generally associated with greater spring salinity intrusion and lesser summer–fall salinity intrusion relative to the pre-development period. Thus, salinity intrusion in summer and fall months was a common occurrence under pre-development conditions and has been moderated in the contemporary period due to the operations of upstream reservoirs, which were designed to hold winter and spring runoff for release in summer and fall. This work also confirms a dramatic decadal-scale hydrologic shift in the watershed from very wet to very dry conditions during the late 19th and early 20th centuries; while not unprecedented, these shifts have been seen only a few times in the past millennium. This shift resulted in an increase in salinity intrusion in the first three decades of the 20th century, as documented through early records. Population growth and extensive watershed modification during this period exacerbated this underlying hydrologic shift. Putting this shift in the context of other anthropogenic drivers is important in understanding the historical response of the estuary and in setting salinity targets for estuarine restoration. By characterizing the long-term behavior of San Francisco Estuary, this work supports decision-making in the State of California related to flow and salinity management for restoration of the estuarine ecosystem.

scholarly journals The Impacts of Spatial Resolution, Viewing Angle, and Spectral Vegetation Indices on the Quantification of Woody Mediterranean Species Seasonality Using Remote Sensing

2021 ◽  
Vol 13 (10) ◽  
pp. 1958
Author(s):  
Shelly Elbaz ◽  
Efrat Sheffer ◽  
Itamar M. Lensky ◽  
Noam Levin
Keyword(s):  
Spatial Resolution ◽  
Seasonal Changes ◽  
Dominant Role ◽  
Vegetation Indices ◽  
Individual Species ◽  
Viewing Angle ◽  
Pixel Size ◽  
Mediterranean Species ◽  
Near Surface ◽  
Nadir Point

Discriminating between woody plant species using a single image is not straightforward due to similarity in their spectral signatures, and limitations in the spatial resolution of many sensors. Seasonal changes in vegetation indices can potentially improve vegetation mapping; however, for mapping at the individual species level, very high spatial resolution is needed. In this study we examined the ability of the Israel/French satellite of VENμS and other sensors with higher spatial resolutions, for identifying woody Mediterranean species, based on the seasonal patterns of vegetation indices (VIs). For the study area, we chose a site with natural and highly heterogeneous vegetation in the Judean Mountains (Israel), which well represents the Mediterranean maquis vegetation of the region. We used three sensors from which the indices were derived: a consumer-grade ground-based camera (weekly images at VIS-NIR; six VIs; 547 individual plants), UAV imagery (11 images, five bands, seven VIs) resampled to 14, 30, 125, and 500 cm to simulate the spatial resolutions available from some satellites, and VENμS Level 1 product (with a nominal spatial resolution of 5.3 m at nadir; seven VIs; 1551 individual plants). The various sensors described seasonal changes in the species’ VIs at different levels of success. Strong correlations between the near-surface sensors for a given VI and species mostly persisted for all spatial resolutions ≤125 cm. The UAV ExG index presented high correlations with the ground camera data in most species (pixel size ≤125 cm; 9 of 12 species with R ≥ 0.85; p < 0.001), and high classification accuracies (pixel size ≤30 cm; 8 species with >70%), demonstrating the possibility for detailed species mapping from space. The seasonal dynamics of the species obtained from VENμS demonstrated the dominant role of ephemeral herbaceous vegetation on the signal recorded by the sensor. The low variance between the species as observed from VENμS may be explained by its coarse spatial resolution (effective ground spatial resolution of 7.5) and its non-nadir viewing angle (29.7°) over the study area. However, considering the challenging characteristics of the research site, it may be that using a VENμS type sensor (with a spatial resolution of ~1 m) from a nadir point of view and in more homogeneous and dense areas would allow for detailed mapping of Mediterranean species based on their seasonality.

scholarly journals Modelling the productivity of Siberian larch forests from Landsat NDVI time series in fragmented forest stands of the Mongolian forest-steppe

2021 ◽  
Vol 193 (4) ◽  
Author(s):  
Stefan Erasmi ◽  
Michael Klinge ◽  
Choimaa Dulamsuren ◽  
Florian Schneider ◽  
Markus Hauck
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Global Climate Change ◽  
Global Climate ◽  
Siberian Larch ◽  
Growing Season ◽  
Forest Productivity ◽  
Forest Steppe ◽  
Fragmented Forest ◽  
Southern Fringe

AbstractThe monitoring of the spatial and temporal dynamics of vegetation productivity is important in the context of carbon sequestration by terrestrial ecosystems from the atmosphere. The accessibility of the full archive of medium-resolution earth observation data for multiple decades dramatically improved the potential of remote sensing to support global climate change and terrestrial carbon cycle studies. We investigated a dense time series of multi-sensor Landsat Normalized Difference Vegetation Index (NDVI) data at the southern fringe of the boreal forests in the Mongolian forest-steppe with regard to the ability to capture the annual variability in radial stemwood increment and thus forest productivity. Forest productivity was assessed from dendrochronological series of Siberian larch (Larix sibirica) from 15 plots in forest patches of different ages and stand sizes. The results revealed a strong correlation between the maximum growing season NDVI of forest sites and tree ring width over an observation period of 20 years. This relationship was independent of the forest stand size and of the landscape’s forest-to-grassland ratio. We conclude from the consistent findings of our case study that the maximum growing season NDVI can be used for retrospective modelling of forest productivity over larger areas. The usefulness of grassland NDVI as a proxy for forest NDVI to monitor forest productivity in semi-arid areas could only partially be confirmed. Spatial and temporal inconsistencies between forest and grassland NDVI are a consequence of different physiological and ecological vegetation properties. Due to coarse spatial resolution of available satellite data, previous studies were not able to account for small-scaled land-cover patches like fragmented forest in the forest-steppe. Landsat satellite-time series were able to separate those effects and thus may contribute to a better understanding of the impact of global climate change on natural ecosystems.

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