scholarly journals Scale-dependent portfolio effects explain growth inflation and volatility reduction in landscape demography

2017 ◽  
Vol 114 (47) ◽  
pp. 12507-12511 ◽  
Author(s):  
Cang Hui ◽  
Gordon A. Fox ◽  
Jessica Gurevitch
Keyword(s):  
Invasive Species ◽  
Time Series ◽  
Regional Scale ◽  
Scaling Up ◽  
Range Shifts ◽  
Attainable Set ◽  
Local Populations ◽  
Accumulation Curve ◽  
Invasive Organisms ◽  
Regional Population

Population demography is central to fundamental ecology and for predicting range shifts, decline of threatened species, and spread of invasive organisms. There is a mismatch between most demographic work, carried out on few populations and at local scales, and the need to predict dynamics at landscape and regional scales. Inspired by concepts from landscape ecology and Markowitz’s portfolio theory, we develop a landscape portfolio platform to quantify and predict the behavior of multiple populations, scaling up the expectation and variance of the dynamics of an ensemble of populations. We illustrate this framework using a 35-y time series on gypsy moth populations. We demonstrate the demography accumulation curve in which the collective growth of the ensemble depends on the number of local populations included, highlighting a minimum but adequate number of populations for both regional-scale persistence and cross-scale inference. The attainable set of landscape portfolios further suggests tools for regional population management for both threatened and invasive species.

scholarly journals Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in semi-arid grassland savannas?

2015 ◽  
Vol 12 (14) ◽  
pp. 4407-4419 ◽  
Author(s):  
J. L. Olsen ◽  
S. Miehe ◽  
P. Ceccato ◽  
R. Fensholt
Keyword(s):  
Time Series ◽  
Species Composition ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Grazing Intensity ◽  
Test Site ◽  
Grazing Pressure ◽  
Modis Ndvi ◽  
Coarse Resolution

Abstract. Most regional scale studies of vegetation in the Sahel have been based on Earth observation (EO) imagery due to the limited number of sites providing continuous and long term in situ meteorological and vegetation measurements. From a long time series of coarse resolution normalized difference vegetation index (NDVI) data a greening of the Sahel since the 1980s has been identified. However, it is poorly understood how commonly applied remote sensing techniques reflect the influence of extensive grazing (and changes in grazing pressure) on natural rangeland vegetation. This paper analyses the time series of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI metrics by comparing it with data from the Widou Thiengoly test site in northern Senegal. Field data include grazing intensity, end of season standing biomass (ESSB) and species composition from sizeable areas suitable for comparison with moderate – coarse resolution satellite imagery. It is shown that sampling plots excluded from grazing have a different species composition characterized by a longer growth cycle as compared to plots under controlled grazing or communal grazing. Also substantially higher ESSB is observed for grazing exclosures as compared to grazed areas, substantially exceeding the amount of biomass expected to be ingested by livestock for this area. The seasonal integrated NDVI (NDVI small integral; capturing only the signal inherent to the growing season recurrent vegetation), derived using absolute thresholds to estimate start and end of growing seasons, is identified as the metric most strongly related to ESSB for all grazing regimes. However plot-pixel comparisons demonstrate how the NDVI/ESSB relationship changes due to grazing-induced variation in annual plant species composition and the NDVI values for grazed plots are only slightly lower than the values observed for the ungrazed plots. Hence, average ESSB in ungrazed plots since 2000 was 0.93 t ha−1, compared to 0.51 t ha−1 for plots subjected to controlled grazing and 0.49 t ha−1 for communally grazed plots, but the average integrated NDVI values for the same period were 1.56, 1.49, and 1.45 for ungrazed, controlled and communal, respectively, i.e. a much smaller difference. This indicates that a grazing-induced development towards less ESSB and shorter-cycled annual plants with reduced ability to turn additional water in wet years into biomass is not adequately captured by seasonal NDVI metrics.

scholarly journals Changes in Vegetation Phenology and Productivity in Alaska Over the Past Two Decades

2020 ◽  
Vol 12 (10) ◽  
pp. 1546 ◽  
Author(s):  
Christopher Potter ◽  
Olivia Alexander
Keyword(s):  
Time Series ◽  
Coastal Plain ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Regional Scale ◽  
Data Sets ◽  
Vegetation Phenology ◽  
Vegetation Growth ◽  
The Past ◽  
Moderate Resolution Imaging Spectroradiometer

Understanding trends in vegetation phenology and growing season productivity at a regional scale is important for global change studies, particularly as linkages can be made between climate shifts and the vegetation’s potential to sequester or release carbon into the atmosphere. Trends and geographic patterns of change in vegetation growth and phenology from the MODerate resolution Imaging Spectroradiometer (MODIS) satellite data sets were analyzed for the state of Alaska over the period 2000 to 2018. Phenology metrics derived from the MODIS Normalized Difference Vegetation Index (NDVI) time-series at 250 m resolution tracked changes in the total integrated greenness cover (TIN), maximum annual NDVI (MAXN), and start of the season timing (SOST) date over the past two decades. SOST trends showed significantly earlier seasonal vegetation greening (at more than one day per year) across the northeastern Brooks Range Mountains, on the Yukon-Kuskokwim coastal plain, and in the southern coastal areas of Alaska. TIN and MAXN have increased significantly across the western Arctic Coastal Plain and within the perimeters of most large wildfires of the Interior boreal region that burned since the year 2000, whereas TIN and MAXN have decreased notably in watersheds of Bristol Bay and in the Cook Inlet lowlands of southwestern Alaska, in the same regions where earlier-trending SOST was also detected. Mapping results from this MODIS time-series analysis have identified a new database of localized study locations across Alaska where vegetation phenology has recently shifted notably, and where land cover types and ecosystem processes could be changing rapidly.

Investigating the Mixing Efficiencies of Liquid-to-Liquid Chemical Injection Manifolds for Aquatic Invasive Species Management

2018 ◽  
Vol 141 (3) ◽  
Author(s):  
Thomas J. Zolper ◽  
Aaron R. Cupp ◽  
David L. Smith
Keyword(s):  
Invasive Species ◽  
Large Scale ◽  
Open Systems ◽  
Mixing Time ◽  
Water Injection ◽  
The United States ◽  
Aquatic Invasive Species ◽  
Chemical Treatments ◽  
Invasive Organisms ◽  
Closed Systems

Aquatic invasive species (AIS) have spread throughout the United States via major rivers and tributaries. Locks and dams positioned along affected waterways, specifically lock chambers, are being evaluated as potential management sites to prevent further expansion into new areas. Recent research has shown that infusion of chemicals (e.g., carbon dioxide) into water can block or kill several invasive organisms and could be a viable option at navigational structures such as lock chambers because chemical infusion would not interfere with vessel passage or lock operation. Chemical treatments near lock structures will require large-scale fluid-mechanic systems and significant energy. Mixing must extend to all stagnation regions within a lock structure to prevent the passage of an invasive fish. This work describes the performance of both wall- and floor-based CO2-infused-water to water injection manifolds targeted for lock structures in terms of mixing time, mixing homogeneity, injection efficiency, and operational power requirements. Both systems have strengths and weaknesses so selection recommendations are given for applications such as open systems and closed systems.

scholarly journals SST Comparison of AVHRR and MODIS Time Series in the Western Mediterranean Sea

2020 ◽  
Vol 12 (14) ◽  
pp. 2241
Author(s):  
María José López García
Keyword(s):  
Time Series ◽  
Regional Scale ◽  
Atmospheric Correction ◽  
Western Mediterranean ◽  
Western Mediterranean Sea ◽  
Temporal And Spatial Variability ◽  
Moderate Resolution ◽  
Long Term Trends ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Development And Validation

Sea Surface Temperature (SST) is a key parameter for understanding atmospheric and oceanic processes. Since the late 1980s, infrared satellite images have been used to complement in situ records for studying the temporal and spatial variability of SST. The Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)’s satellite was the first sensor successfully used to compute SST following the development and validation of the atmospheric correction algorithm known as “split-window”. More recently, the MODerate-resolution Imaging Spectroradiometer (MODIS) on board the National Aeronautics and Space Administration (NASA)’s Terra and Aqua satellites, launched in 1999 and 2002, respectively, also provides SST products which can be combined with AVHRR series to complete the analysis of time series. This paper presents a comparison of the monthly SST data derived from both sensors, AVHRR and MODIS, in a series of ten years (2000–2009) in the Western Mediterranean basins. The results showed a high correlation (R2 = 0.99) between the sensors when averaged values at the regional scale were compared. SST obtained from AVHRR were slightly higher (+0.18 °C ± 0.2 °C, on average) than SST from MODIS. The series were most similar during winter and spring (+0.09 °C ± 0.1 °C for January to May) with a greater difference from June to December (+0.24 °C ± 0.2 °C). The comparative analysis showed that the two sensors can be used jointly to estimate long-term trends at the regional scale.

A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm

2019 ◽  
Vol 80 ◽  
pp. 127-136 ◽  
Author(s):  
Ana Cláudia dos Santos Luciano ◽  
Michelle Cristina Araújo Picoli ◽  
Jansle Vieira Rocha ◽  
Daniel Garbellini Duft ◽  
Rubens Augusto Camargo Lamparelli ◽  
...  
Keyword(s):  
Time Series ◽  
Random Forest ◽  
Classification Scheme ◽  
Regional Scale ◽  
Space Time ◽  
Random Forest Algorithm ◽  
Landsat Images

scholarly journals Drifting Effects of NOAA Satellites on Long-Term Active Fire Records of Europe

2019 ◽  
Vol 11 (4) ◽  
pp. 467 ◽  
Author(s):  
Helga Weber ◽  
Stefan Wunderle
Keyword(s):  
Time Series ◽  
Explicit Knowledge ◽  
Regional Scale ◽  
Error Sources ◽  
Fire Cycle ◽  
Active Fire ◽  
Maximum Delay ◽  
Orbital Drift ◽  
The Impact

Explicit knowledge of different error sources in long-term climate records from space is required to understand and mitigate their impacts on resulting time series. Imagery of the heritage Advanced Very High Resolution Radiometer (AVHRR) provides unique potential for climate research dating back to the 1980s, flying onboard a series of successive National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (MetOp) satellites. However, the NOAA satellites are affected by severe orbital drift that results in spurious trends in time series. We identified the impact and extent of the orbital drift in 1 km AVHRR long-term active fire data. This record contains data of European fire activity from 1985–2016 and was analyzed on a regional scale and extended across Europe. Inconsistent sampling of the diurnal active fire cycle due to orbital drift with a maximum delay of ∼5 h over NOAA-14 lifetime revealed a ∼90% decline in the number of observed fires. However, interregional results were less conclusive and other error sources as well as interannual variability were more pronounced. Solar illumination, measured by the sun zenith angle (SZA), related changes in background temperatures were significant for all regions and afternoon satellites with major changes in −0.03 to −0.09 K deg − 1 for ▵ B T 34 (p ≤ 0 . 001). Based on example scenes, we simulated the influence of changing temperatures related to changes in the SZA on the detection of active fires. These simulations showed a profound influence of the active fire detection capabilities dependent on biome and land cover characteristics. The strong decrease in the relative changes in the apparent number of active fires calculated over the satellites lifetime highlights that a correction of the orbital drift effect is essential even over short time periods.

scholarly journals Dry Spells and Extreme Precipitation are The Main Trigger of Landslides in Central Europe

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Radek Tichavský ◽  
Juan Antonio Ballesteros-Cánovas ◽  
Karel Šilhán ◽  
Radim Tolasz ◽  
Markus Stoffel
Keyword(s):  
Time Series ◽  
Central Europe ◽  
Climate Models ◽  
Regional Scale ◽  
Summer Precipitation ◽  
Greenhouse Climate ◽  
Dry Spells ◽  
Outer Western Carpathians ◽  
Triggering Mechanisms

Abstract Landslides are frequently triggered by extreme meteorological events which has led to concern and debate about their activity in a future greenhouse climate. It is also hypothesized that dry spells preceding triggering rainfall may increase slope predisposition to sliding, especially in the case of clay-rich soils. Here we combined dendrogeomorphic time series of landslides and climatic records to test the possible role of dry spells and extreme downpours on process activity in the Outer Western Carpathians (Central Europe). To this end, we tested time series of past frequencies and return periods of landslide reactivations at the regional scale with a Generalized Linear Mixed (GLM) model to explore linkages between landslide occurrences and triggering climate variables. Results show that landslide reactivations are concentrated during years in which spring and summer precipitation sums were significantly higher than usual, and that triggering mechanisms vary between different types of landslides (i.e. complex, shallow or flow-like). The GLM model also points to the susceptibility of landslide bodies to the combined occurrence of long, dry spells followed by large precipitation. Such situations are likely to increase in frequency in the future as climate models predict an enhancement of heatwaves and dry spells in future summers, that would be interrupted by less frequent, yet more intense storms, especially also in mountain regions.

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