U.S. Mussel Watch Data from 1986 to 1994:  Temporal Trend Detection at Large Spatial Scales

1997 ◽  
Vol 31 (5) ◽  
pp. 1411-1415 ◽  
Author(s):  
B. Beliaeff ◽  
Thomas P. O'Connor ◽  
D. K. Daskalakis ◽  
P. J. Smith
Keyword(s):  
Temporal Trend ◽  
Spatial Scales ◽  
Trend Detection ◽  
Mussel Watch

Tracking Temporal Trend Breaks of Anthropogenic Change in Mussel Watch (MW) Databases

2012 ◽  
Vol 46 (21) ◽  
pp. 11515-11523 ◽  
Author(s):  
Carlos Guitart ◽  
Adrian Hernández-del-Valle ◽  
J. Miguel Marín ◽  
José Benedicto
Keyword(s):  
Temporal Trend ◽  
Anthropogenic Change ◽  
Mussel Watch ◽  
Trend Breaks

Detecting climate-related trends in streamflow data

2002 ◽  
Vol 45 (8) ◽  
pp. 89-104 ◽  
Author(s):  
Paul J. Pilon ◽  
Sheng Yue
Keyword(s):  
Local Knowledge ◽  
Serial Correlation ◽  
Selection Criteria ◽  
Spatial Scales ◽  
High Density ◽  
Global Network ◽  
Trend Detection ◽  
Testing Procedures ◽  
Stable Conditions ◽  
Streamflow Data

This paper reviews the results of a number of studies that have investigated streamflow data for the existence of trend. These studies provide evidence that trends in various, but not all, streamflow regimes are occurring at rates that are higher than one might attribute to chance alone. Results of different studies using different approaches were compared and were shown, at times, to have dramatic differences. These differences might potentially be due to pre-conditioning of data prior to trend detection in attempts to minimize the impacts of serial correlation on testing procedures. It was also evident that patterns of trend can vary over small spatial scales and that a relatively high-density network is required to effectively comprehend trend and how it might be altering across an area. A global network of streamflow sites representing pristine or stable conditions is needed to assess patterns of change. Selection criteria for sites within such a network are provided, and it is highlighted that local knowledge is required to perform this selection.

TwitterTrends: a spatio-temporal trend detection and related keywords recommendation scheme

2013 ◽  
Vol 21 (1) ◽  
pp. 73-86 ◽  
Author(s):  
Daehoon Kim ◽  
Daeyong Kim ◽  
Eenjun Hwang ◽  
Seungmin Rho
Keyword(s):  
Temporal Trend ◽  
Trend Detection ◽  
Spatio Temporal

scholarly journals Applying geoscience to biodiversity monitoring: Case studies from an Australian marine park

2018 ◽  
Author(s):  
Rachel Przeslawski ◽  
Kim Picard ◽  
Scott Nichol ◽  
Ben Radford ◽  
Phil Bouchet
Keyword(s):  
Sampling Design ◽  
Spatial Scales ◽  
Biological Data ◽  
Trend Detection ◽  
Design Data ◽  
Sediment Grain Size ◽  
Marine Park ◽  
Management Plans ◽  
Robust Modelling ◽  
Research And Policy

Following the establishment of the world’s largest network of marine protected areas, Australia is now tasked with implementing national plans to manage a huge range of marine environments, from tropical to sub-Antarctic climates and shallow reef to abyssal depths. Monitoring (i.e. condition assessment and trend detection) is one of the key objectives of associated management plans. As part of a national effort to acquire baseline data for future monitoring purposes from 2009 to 2012, we collected geoscientific (bathymetry, backscatter, sub-bottom profiles, sediment grain-size) and biological data (assemblages and richness of infauna, sponges and pelagic fish) using a variety of gear (grab, sled, pelagic baited video, multibeam sonar, sparker) from the Oceanic Shoals Australian Marine Park in northern Australia. In this presentation, we describe how the integration of such data (including derived geoscientific products) helped to inform sampling design, map habitats, predict the distribution of benthic and pelagic communities at varying spatial scales, and better understand ecosystem processes. We hope to encourage ecologists and marine managers to incorporate geoscientific methods into their research and policy in order to further improve sampling design, data collection, robust modelling, and informed decision-making.

scholarly journals Estimating Minimum Detection Times for Satellite Remote Sensing of Trends in Mean and Extreme Precipitable Water Vapor

2016 ◽  
Vol 29 (22) ◽  
pp. 8211-8230 ◽  
Author(s):  
Jacola Roman ◽  
Robert Knuteson ◽  
Steve Ackerman ◽  
Hank Revercomb
Keyword(s):  
Water Vapor ◽  
Time Window ◽  
Spatial Scales ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Trend Detection ◽  
Observation System ◽  
Climate Trends ◽  
Intergovernmental Panel ◽  
Uncertainty Estimates

Abstract The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report found that changes in extreme events have occurred and the frequency of such events is expected to increase. Precipitable water vapor (PWV) is a useful measure of the moisture content of the atmosphere. This paper combines the predicted GCM trends in PWV from 2000 to 2100 with uncertainty estimates from infrared spectrometers, NASA Atmospheric Infrared Sounder (AIRS) and EUMETSAT Infrared Atmospheric Sounding Interferometer (IASI), to estimate minimum trend detection times on regional and global spatial scales. The minimum detection time (MDT) is the number of years before the multimodel GCM trend exceeds a fractional change equal to the uncertainty in the observed product, plus the width of the time window used to smooth out natural variability. Results indicate that the median value of PWV has an MDT of 15 yr or less over all scales, while extreme dry (5th) and wet (95th) PWV conditions (percentiles) have higher measurement uncertainty and corresponding larger MDTs. Product providers have done a relatively good job tuning results to the mean atmospheric state but more attention should be given to improving the satellite estimates for extreme PWV. A fractional measurement error of 3% is desirable to detect predicted climate trends within 15 years or less for the entire PDF of PWV. This paper presents an important case study for the design of observing systems directly linking the estimated uncertainty of the PWV products to the detectability of long-term trends. If there is a need to decrease detection times over the existing weather observation system then necessary changes to the climate observational system design can be understood quantitatively.

scholarly journals Change detection of bare-ice albedo in the Swiss Alps

2019 ◽  
Vol 13 (1) ◽  
pp. 397-412 ◽  
Author(s):  
Kathrin Naegeli ◽  
Matthias Huss ◽  
Martin Hoelzle
Keyword(s):  
Temporal Trend ◽  
Spatial Scales ◽  
Swiss Alps ◽  
Limited Region ◽  
Albedo Feedback ◽  
Glacier Melt ◽  
Glacier Ice ◽  
Wide Scale ◽  
Near Future ◽  
Scientific Debates

Abstract. Albedo feedback is an important driver of glacier melt over bare-ice surfaces. Light-absorbing impurities strongly enhance glacier melt rates but their abundance, composition and variations in space and time are subject to considerable uncertainties and ongoing scientific debates. In this study, we assess the temporal evolution of shortwave broadband albedo derived from 15 end-of-summer Landsat scenes for the bare-ice areas of 39 large glaciers in the western and southern Swiss Alps. Trends in bare-ice albedo crucially depend on the spatial scale considered. No significant negative temporal trend in bare-ice albedo was found on a regional to glacier-wide scale. However, at higher spatial scales, certain areas of bare ice, including the lowermost elevations and margins of the ablation zones, revealed significant darkening over the study period 1999 to 2016. A total glacier area of 13.5 km2 (equivalent to about 12 % of the average end-of-summer bare-ice area in the study area) exhibited albedo trends significant at the 95 % confidence level or higher. Most of this area was affected by a negative albedo trend of about −0.05 decade−1. Generally, bare-ice albedo exhibits a strong interannual variability, caused by a complex interplay of meteorological conditions prior to the acquisition of the data, local glacier characteristics and the date of the investigated satellite imagery. Although a darkening of glacier ice was found to be present over only a limited region, we emphasize that due to the recent and projected growth of bare-ice areas and prolongation of the ablation season in the region, the albedo feedback will considerably enhance the rate of glacier mass loss in the Swiss Alps in the near future.

scholarly journals Applying geoscience to biodiversity monitoring: Case studies from an Australian marine park

2018 ◽  
Author(s):  
Rachel Przeslawski ◽  
Kim Picard ◽  
Scott Nichol ◽  
Ben Radford ◽  
Phil Bouchet
Keyword(s):  
Sampling Design ◽  
Spatial Scales ◽  
Biological Data ◽  
Trend Detection ◽  
Design Data ◽  
Sediment Grain Size ◽  
Marine Park ◽  
Management Plans ◽  
Robust Modelling ◽  
Research And Policy

Following the establishment of the world’s largest network of marine protected areas, Australia is now tasked with implementing national plans to manage a huge range of marine environments, from tropical to sub-Antarctic climates and shallow reef to abyssal depths. Monitoring (i.e. condition assessment and trend detection) is one of the key objectives of associated management plans. As part of a national effort to acquire baseline data for future monitoring purposes from 2009 to 2012, we collected geoscientific (bathymetry, backscatter, sub-bottom profiles, sediment grain-size) and biological data (assemblages and richness of infauna, sponges and pelagic fish) using a variety of gear (grab, sled, pelagic baited video, multibeam sonar, sparker) from the Oceanic Shoals Australian Marine Park in northern Australia. In this presentation, we describe how the integration of such data (including derived geoscientific products) helped to inform sampling design, map habitats, predict the distribution of benthic and pelagic communities at varying spatial scales, and better understand ecosystem processes. We hope to encourage ecologists and marine managers to incorporate geoscientific methods into their research and policy in order to further improve sampling design, data collection, robust modelling, and informed decision-making.

State-space analysis of power to detect regional brook trout population trends over time

2019 ◽  
Vol 76 (11) ◽  
pp. 2145-2155 ◽  
Author(s):  
Kasey C. Pregler ◽  
R. Daniel Hanks ◽  
Evan S. Childress ◽  
Nathaniel P. Hitt ◽  
Daniel J. Hocking ◽  
...  
Keyword(s):  
State Space ◽  
Brook Trout ◽  
Statistical Power ◽  
Spatial Scales ◽  
Temporal Trends ◽  
Monitoring Program ◽  
Trend Detection ◽  
Data Set ◽  
Trout Population ◽  
Variable Sampling

Threats to aquatic biodiversity are expressed at broad spatial scales, but identifying regional trends in abundance is challenging owing to variable sampling designs and temporal and spatial variation in abundance. We compiled a regional data set of brook trout (Salvelinus fontinalis) counts across their southern range representing 326 sites from eight states between 1982 and 2014 and conducted a statistical power analysis using Bayesian state-space models to evaluate the ability to detect temporal trends by characterizing posterior distributions with three approaches. A combination of monitoring periods, number of sites and electrofishing passes, decline magnitude, and different revisit patterns were tested. Power increased with monitoring periods and decline magnitude. Trends in adults were better detected than young-of-the-year fish, which showed greater interannual variation in abundance. The addition of weather covariates to account for the temporal variation increased power only slightly. Single- and three-pass electrofishing methods were similar in power. Finally, power was higher for sampling designs with more frequent revisits over the duration of the monitoring program. Our results provide guidance for broad-scale monitoring designs for temporal trend detection.

scholarly journals Darkening Swiss glacier ice?

2018 ◽  
Author(s):  
Kathrin Naegeli ◽  
Matthias Huss ◽  
Martin Hoelzle
Keyword(s):  
Temporal Trend ◽  
Spatial Scales ◽  
Swiss Alps ◽  
Limited Region ◽  
Albedo Feedback ◽  
Glacier Melt ◽  
Glacier Ice ◽  
Wide Scale ◽  
Near Future ◽  
Scientific Debates

Abstract. The albedo feedback is an important driver of glacier melt over bare-ice surfaces. Light-absorbing impurities strongly enhance glacier melt rates but their abundance, composition and variations in space and time are subject to considerable uncertainties and on-going scientific debates. In this study, we assess the temporal evolution of shortwave broadband albedo derived from 19 end-of summer Landsat scenes for the bare-ice areas of 39 large glaciers in the western and southern Swiss Alps. Trends in bare-ice albedo crucially depend on the spatial scale considered. No significant negative temporal trend in bare-ice albedo was found on a regional to glacier-wide scale. However, at higher spatial scales, certain areas of bare-ice including the lowermost elevations and margins of the ablation zones revealed significant darkening over the study period 1999 to 2016. A total glacier area of 16 km2 (equivalent to about 12 % of the average end-of-summer bare-ice area in the study area) exhibited albedo trends significant at the 95 % confidence level or higher. Most of this area was affected by a negative albedo trend of about −0.05 per decade. Generally, bare-ice albedo exhibits a strong interannual variability, caused by a complex interplay of meteorological conditions prior to the acquisition of the data, local glacier characteristics and the date of the investigated satellite imagery. Although, a darkening of glacier ice was found to be present over only a limited region, we emphasise that due to the recent and projected growth of bare-ice areas and prolongation of the ablation season in the region, the albedo feedback will considerably enhance the rate of glacier mass loss in the Swiss Alps in the near future.

Sign in / Sign up

Export Citation Format

Share Document