scholarly journals Assessing Landsat Fractional Ground-Cover Time Series across Australia's Arid Rangelands: Separating Grazing Impacts from Climate Variability

2017 ◽  
Author(s):  
Jason Barnetson ◽  
Stuart Phinn ◽  
Peter Scarth ◽  
Robert Denham
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Ground Cover ◽  
Field Measurements ◽  
Change Point Detection ◽  
Grazing Impact ◽  
Growth Cycles ◽  
Grazing Impacts ◽  
Arid Rangelands

Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of the Northern Territory of Australia. This work developed and tested a time-series, change-point detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. These cycles were classified to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term (> 3 years) and short term (< 3 years) growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

scholarly journals ASSESSING LANDSAT FRACTIONAL GROUND-COVER TIME SERIES ACROSS AUSTRALIA’S ARID RANGELANDS: SEPARATING GRAZING IMPACTS FROM CLIMATE VARIABILITY

2017 ◽  
Vol XLII-3/W2 ◽  
pp. 15-26 ◽  
Author(s):  
J. Barnetson ◽  
S. Phinn ◽  
P. Scarth ◽  
R. Denham
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
High Performance ◽  
Ground Cover ◽  
Field Measurements ◽  
Grazing Impact ◽  
Growth Cycles ◽  
Grazing Impacts ◽  
Arid Rangelands

Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of Australia. This work developed and tested a time-series, changepoint detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. Utilising the High Performance Computing power of the Google Cloud Compute Engine these cycles were segmented to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term and short term growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. During periods of ground cover decline, grazing utilisation was observed across four major grasslands. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

scholarly journals Natural Climate Variability During the Holocene

Radiocarbon ◽  
2007 ◽  
Vol 49 (2) ◽  
pp. 837-854 ◽  
Author(s):  
V A Dergachev ◽  
O M Raspopov ◽  
F Damblon ◽  
H Jungner ◽  
G I Zaitseva
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Ice Cores ◽  
Cosmogenic Isotope ◽  
Radiocarbon Age ◽  
Earth’S Climate ◽  
Climatic Time Series ◽  
Natural Climate ◽  
Isotope Content

High-precision radiocarbon age calibration for different terrestrial samples allows us to establish accurate boundaries for many climatic time series. At the same time, the fluctuations of 14C content reflect solar variability. A bispectrum analysis of long-term series of the 14C content deduced from decadal measurements in tree rings demonstrates the existence of amplitude modulation, with a period of main modulation of ∼2400 yr. In 14C time series for the last 11 kyr, major oscillations are distinguished at 8.5–7.8, 5.4–4.7, 2.6–2.2, and 1.1–0.4 cal kyr BP with ∼2400-yr periodicity. High amplitudes in cosmogenic isotope content with a periodicity of about 2400 yr appear synchronous to cooling events documented in Greenland ice cores, to the timing of worldwide Holocene glacier expansion, and to the periods of lake-level changes. This paper focuses on revealing solar forcing on the Earth's climate and about the nature, significance, and impact of sharp Holocene climate variability on human societies and civilizations.

Spatial Distribution of Sheep, Feral Goats and Kangaroos in Woody Rangeland Paddocks.

1996 ◽  
Vol 18 (2) ◽  
pp. 270 ◽  
Author(s):  
J Landsberg ◽  
J Stol
Keyword(s):  
Vegetation Type ◽  
New South ◽  
Ground Cover ◽  
Tree Cover ◽  
Vegetation Types ◽  
Vegetative Cover ◽  
Large Herbivores ◽  
Grazing Impacts ◽  
South Wales

The densities and distributions of sheep, kangaroos and feral goats were assessed from extensive dung surveys following dry, moderate and green seasons in three large paddocks in the wooded rangelands of north-westem New South Wales. Densities of sheep (21 9nanimals/km2) were around the long-term district average. Densities of goats (24 animals/km2) were often higher than sheep. Densities of kangaroos (1 1 animals/km2) were usually much lower than either sheep or goats. Animal density was usually related to vegetative cover (ground cover for sheep and kangaroos, shrub and tree cover for goats), but there were also differences among paddocks. Distribution of kangaroos showed the most differentiation according to vegetation type, with densities being consistently high on a small area of alluvial grassland and very low in the paddock with no alluvial plains and the lowest levels of ground cover. The distributions of sheep and goats were correlated in the dry season and both species showed similar ranges in preferences for different vegetation types. Of the large herbivores present in these woody rangelands, kangaroos were the most selective in terms of the vegetation types they grazed, and goats were the least selective. Because their grazing activities are focussed on alluvial grasslands, kangaroos have potential to degrade this locally uncommon vegetation type. However, the densities of kangaroos in other, more widespread, vegetation types were uniformly low. Goats were frequently the most abundant large herbivores present and were also the least selective. Therefore goats probably have the greatest potential for causing widespread grazing impacts across much of these woody rangelands.

scholarly journals The Importance of Climate Variability to Wind-Driven Modulation of Hypoxia in Chesapeake Bay

2010 ◽  
Vol 40 (6) ◽  
pp. 1435-1440 ◽  
Author(s):  
Malcolm E. Scully
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Chesapeake Bay ◽  
Wind Direction ◽  
Large Scale ◽  
Nitrogen Loading ◽  
Nutrient Inputs ◽  
Westerly Direction ◽  
Hypoxic Volume

Abstract Extensive hypoxia remains a problem in Chesapeake Bay, despite some reductions in estimated nutrient inputs. An analysis of a 58-yr time series of summer hypoxia reveals that a significant fraction of the interannual variability observed in Chesapeake Bay is correlated to changes in summertime wind direction that are the result of large-scale climate variability. Beginning around 1980, the surface pressure associated with the summer Bermuda high has weakened, favoring winds from a more westerly direction, the direction most correlated with observed hypoxia. Regression analysis suggests that the long-term increase in hypoxic volume observed in this dataset is only accounted for when both changes in wind direction and nitrogen loading are considered.

scholarly journals A Comparative Assessment of Gap-filling Techniques for Ocean Carbon Time Series

2021 ◽  
Author(s):  
Jesse M. Vance ◽  
Kim Currie ◽  
John Zeldis ◽  
Peter Dillingham ◽  
Cliff S. Law
Keyword(s):  
Time Series ◽  
Spline Interpolation ◽  
Moving Average ◽  
Field Measurements ◽  
Linear Interpolation ◽  
Comparative Assessment ◽  
Mean Imputation ◽  
Ocean Carbon ◽  
Using Data

Abstract. Regularized time series of ocean carbon data are necessary for assessing seasonal dynamics, annual budgets, interannual variability and long-term trends. There are, however, no standardized methods for imputing gaps in ocean carbon time series, and only limited evaluation of the numerous methods available for constructing uninterrupted time series. A comparative assessment of eight imputation models was performed using data from seven long-term monitoring sites. Multivariate linear regression (MLR), mean imputation, linear interpolation, spline interpolation, Stineman interpolation, Kalman filtering, weighted moving average and multiple imputation by chained equation (MICE) models were compared using cross-validation to determine error and bias. A bootstrapping approach was employed to determine model sensitivity to varied degrees of data gaps and secondary time series with artificial gaps were used to evaluate impacts on seasonality and annual summations and to estimate uncertainty. All models were fit to DIC time series, with MLR and MICE models also applied to field measurements of temperature, salinity and remotely sensed chlorophyll, with model coefficients fit for monthly mean conditions. MLR estimated DIC with a mean error of 8.8 umol kg−1 among 5 oceanic sites and 20.0 ummol kg−1 among 2 coastal sites. The empirical methods of MLR, MICE and mean imputation retained observed seasonal cycles over greater amounts and durations of gaps resulting in lower error in annual budgets, outperforming the other statistical methods. MLR had lower bias and sampling sensitivity than MICE and mean imputation and provided the most robust option for imputing time series with gaps of various duration.

An Empirical Decomposition of Deep Groundwater Time Series and Possible Link to Climate Variability

2013 ◽  
Vol 16 (1) ◽  
pp. 87-103
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Polynomial Interpolation ◽  
Southern Oscillation ◽  
Global Climate ◽  
Deep Groundwater ◽  
Anthropogenic Effect ◽  
Cyclic Patterns ◽  
History Of

<p>Deep groundwater data reflects hydrological processes, climate change and variability, as well as any anthropogenic influence. Decomposition of deep groundwater signal examines the history of the groundwater region. Detrending is a vital step in decomposition of groundwater time series because it is expected to remove anthropogenic effects and long-term cyclic patterns. Eight detrending methods were applied to long-term groundwater records monitored in the Lower Chao Phraya basin in Thailand. Detrended residuals and subsequently periodograms of the residuals were computed by applying the Fourier series analysis. The result from this study indicates that the 5th order polynomial interpolation provides the trendlines that significantly relate to the groundwater withdrawal background. The detrended residual function is imbedded with two major cyclic patterns, which can be the result from global climate variability, e.g. Indian Ocean Dipole and the El Niño Southern Oscillation. The magnitude of deep groundwater dynamics as the result from the anthropogenic effect is much greater than that of the climate variability in this region. In addition, this study demonstrates that caution must be exercised when fitting groundwater time series with different detrending techniques can yield mistaken cyclic patterns and may infer to different climate variability phenomenon.</p>

scholarly journals Influence of low-frequency variability on high and low groundwater levels: example of aquifers in Paris Basin

2022 ◽  
Author(s):  
Lisa Baulon ◽  
Nicolas Massei ◽  
Delphine Allier ◽  
Matthieu Fournier ◽  
Hélène Bessiere
Keyword(s):  
Time Series ◽  
Climate Variability ◽  
Large Scale ◽  
Low Frequency ◽  
Paris Basin ◽  
Dominant Type ◽  
Groundwater Levels ◽  
Low Frequency Variability ◽  
Frequency Components

Abstract. Groundwater levels (GWL) very often fluctuate over a wide range of timescales (infra-annual, annual, multi-annual, decadal). In many instances, aquifers act as low-pass filters, dampening the high-frequency variability and amplifying low-frequency variations (from multi-annual to decadal timescales) which basically originate from large-scale climate variability. In the aim of better understanding and ultimately anticipating groundwater droughts and floods, it appears crucial to evaluate whether (and how much) the very high or very low GWLs are sensitive to such low-frequency variability (LFV), which was the main objective of the study presented here. As an example, we focused on exceedance and non-exceedance of the 80 % and 20 % GWL percentiles respectively, in the Paris Basin aquifers over the 1976–2019 period. GWL time series were extracted from a database consisting of relatively undisturbed GWL time series regarding anthropogenic influence (water abstraction by either continuous or periodic pumping) over Metropolitan France. Based on this dataset, our approach consisted of exploring the effect of GWL low-frequency components on threshold exceedance and non-exceedance by successively filtering out low-frequency components of GWL signals using maximum overlap discrete wavelet transform (MODWT). Multi-annual (~7-yr) and decadal (~17-yr) variabilities were found to be the predominant LFVs in GWL signals, in accordance with previous studies in the northern France area. Filtering out these components (either independently or jointly) to (i) examine the proportion of high level (HL) and low level (LL) occurrences generated by these variabilities, (ii) estimate the contribution of each of these variabilities in explaining the occurrence of major historical events associated to well-recognized societal impacts. A typology of GWL variations in Paris Basin aquifers was first determined by quantifying the variance distribution across timescales. Four GWL variation types could be found according to the predominance of annual, multi-annual or/and decadal variabilities in these signals: decadal dominant (type iD), multi-annual and decadal dominant (type iMD), annual dominant (type cA), annual and multi-annual dominant (type cAM). We observed a clear dependence of high and low GWL to LFV for aquifers exhibiting these four GWL variation types. In addition, the respective contribution of multi-annual and decadal variabilities in the threshold exceedance varied according to the event. In numerous aquifers, it also appeared that the sensitivity to LFV was higher for LL than HL. A similar analysis was conducted on the only available long-term GWL time series which covered a hundred years. This allowed us to highlight a potential influence of multidecadal variability on HL and LL too. This study underlined the key role of LFV in the occurrence of HL and LL. Since LFV originates from large-scale stochastic climate variability as demonstrated in many previous studies in the Paris Basin or nearby regions, our results point out that i) poor representation of LFV in General Circulation Models (GCM) outputs used afterwards for developing hydrological projections can result in strong uncertainty in the assessment of future groundwater extremes (GWE), ii) potential changes in the amplitude of LFV, be they natural or induced by global climate change, may lead to substantial changes in the occurrence and severity of GWE for the next decades. Finally, this study also stresses the fact that due to the stochastic nature of LFV, no deterministic prediction of future GWE for the mid- or long term horizons can be achieved even though LFV may look periodic.

Assessment of Drought due to Historic Climate Variability and Projected Future Climate Change in the Midwestern United States

2010 ◽  
Vol 11 (1) ◽  
pp. 46-68 ◽  
Author(s):  
Vimal Mishra ◽  
Keith A. Cherkauer ◽  
Shraddhanand Shukla
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Soil Moisture ◽  
Climate Variability ◽  
Air Temperature ◽  
Regional Scale ◽  
Future Climate ◽  
Future Climate Change ◽  
Vic Model

Abstract Understanding the occurrence and variability of drought events in historic and projected future climate is essential to managing natural resources and setting policy. The Midwest region is a key contributor in corn and soybean production, and the occurrence of droughts may affect both quantity and quality of these crops. Soil moisture observations play an essential role in understanding the severity and persistence of drought. Considering the scarcity of the long-term soil moisture datasets, soil moisture observations in Illinois have been one of the best datasets for studies of soil moisture. In the present study, the authors use the existing observational dataset and then reconstruct long-term historic time series (1916–2007) of soil moisture data using a land surface model to study the effects of historic climate variability and projected future climate change on regional-scale (Illinois and Indiana) drought. The objectives of this study are to (i) estimate changes and trends associated with climate variables in historic climate variability (1916–2007) and in projected future climate change (2009–99) and (ii) identify regional-scale droughts and associated severity, areal extent, and temporal extent under historic and projected future climate using reconstructed soil moisture data and gridded climatology for the period 1916–2007 using the Variable Infiltration Capacity (VIC) model. The authors reconstructed the soil moisture for a long-term (1916–2007) historic time series using the VIC model, which was calibrated for monthly streamflow and soil moisture at eight U.S. Geological Survey (USGS) gauge stations and Illinois Climate Network’s (ICN) soil moisture stations, respectively, and then it was evaluated for soil moisture, persistence of soil moisture, and soil temperature and heat fluxes. After calibration and evaluation, the VIC model was implemented for historic (1916–2007) and projected future climate (2009–99) periods across the study domain. The nonparametric Mann–Kendall test was used to estimate trends using the gridded climatology of precipitation and air temperature variables. Trends were also estimated for annual anomalies of soil moisture variables, snow water equivalent, and total runoff using a long-term time series of the historic period. Results indicate that precipitation, minimum air temperature, total column soil moisture, and runoff have experienced upward trends, whereas maximum air temperature, frozen soil moisture, and snow water equivalent experienced downward trends. Furthermore, the decreasing trends were significant for the frozen soil moisture in the study domain. The results demonstrate that retrospective drought periods and their severity were reconstructed using model-simulated data. Results also indicate that the study region is experiencing reduced extreme and exceptional droughts with lesser areal extent in recent decades.

Long-term Performance of Asian Pear Trees in Maryland

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 548b-548
Author(s):  
C.S. Walsh ◽  
A.J. Barton ◽  
M. Newell ◽  
G.R. Welsh
Keyword(s):  
Ground Cover ◽  
Organic Production ◽  
Alternative Crop ◽  
Asian Pear ◽  
Marketable Fruit ◽  
Long Term Performance ◽  
Organic Fruit ◽  
Term Performance ◽  
Direct Market

Three Asian pear plantings were set during the past decade. Plantings included an initial cultivar planting on OH × F rootstock, the SE Zonal planting, and a rootstock by cultivar factorial. Fireblight susceptibility and survival were assessed in the first two plantings following a summer hailstorm. Trees were compared to Magness, a blight-tolerant buttery pear. Shin Li, Daisu Li, Shinsui, and Olympic were more resistant than Magness, while Chojuro and Niitaka were nearly as tolerant. Eleven other cultivars showed greater field-susceptibility. The most-susceptible cultivars were Ya Li and Ts'e Li. The third planting, which was managed “organically,” was set at a different University farm. Trees there were precocious and productive. A high percentage of marketable fruit was picked from that planting over a 4-year period. Fireblight damage in this planting was low, despite its “organic” production. Limited damage was attributed to early bloom date, ground cover management, and a lack of insect vectors to transmit the bacteria. Hosui, Seuri and Ts'e Li produced large-sized fruit. Shinko, 20th Century, Ya Li and Shinseiki fruit were too small to be marketable without heavy hand-thinning. Asian pears are an interesting alternative crop which are suited to direct-market enterprises or to specialty growers interested in producing organic fruit in the mid-Atlantic region.

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