Estimating spatial variability in developing assemblages of epibiota on subtidal hard substrata

1998 ◽  
Vol 49 (5) ◽  
pp. 429 ◽  
Author(s):  
T. M. Glasby
Keyword(s):  
Environmental Impact ◽  
Spatial Variability ◽  
Large Scale ◽  
Sampling Design ◽  
Spatial Scales ◽  
Rocky Reefs ◽  
Natural Substratum ◽  
Spatial Replication ◽  
Supporting Structures ◽  
Hard Substrata

A nested hierarchical sampling design was used to estimate the scales of natural variability in developing assemblages of subtidal epibiota on rocky reefs. The appropriate spatial scales were needed for sampling to test for environmental impact in this habitat. Sandstone settlement plates were used to mimic the natural substratum. They were designed and deployed in such a way that the effects of any supporting structures were minimized. Differences in recruitment of epibiota were found at all of the spatial scales examined (10s, 100s and 1000s of metres). When differences were found at the smallest spatial scale, they were generally still detected at the two larger scales. The results highlighted the need for adequate small- and large-scale spatial replication for studies of environmental impact.

scholarly journals A Remote Sensing Survey of the Role of Landform on the Organization of Orographic Precipitation in Central and Southern Mexico

2008 ◽  
Vol 9 (6) ◽  
pp. 1267-1283 ◽  
Author(s):  
Jason P. Giovannettone ◽  
Ana P. Barros
Keyword(s):  
Spatial Variability ◽  
Large Scale ◽  
Spatial Scales ◽  
Coastal Region ◽  
La Niña ◽  
Southern Mexico ◽  
La Nina ◽  
Basin Scale ◽  
Sierra Madre ◽  
Average Rainfall

Abstract Data from NASA’s TRMM satellite and NOAA’s GOES satellites were used to survey the orographic organization of cloud precipitation in central and southern Mexico during the monsoon with two main objectives: 1) to investigate large-scale forcing versus local landform controls, and 2) to compare the results with previous work in the Himalayas. At large scales, the modes of spatial variability of cloudiness were estimated using the empirical orthogonal function (EOF) analysis of GOES brightness temperatures. Terrain modulation of synoptic-scale high-frequency variability (3–5- and 6–9-day cycles normally associated with the propagation of easterly waves) was found to cause higher dispersion in the EOF spectrum, with the first mode explaining less than 30% of the spatial variability in central and southern Mexico as opposed to 50% and higher in the Himalayas. A detailed analysis of the first three EOFs for 1999, an average La Niña year with above average rainfall, and for 2001, a weak La Niña year with below average rainfall, shows that landform (mountain peaks and land–ocean contrast) and large-scale circulation (moisture convergence) alternate as the key controls of regional hydrometeorology in dry and wet years, or as active and break (midsummer drought) phases of the monsoon, respectively. The diurnal cycle is the dominant time scale of variability in 2001, as it is during the midsummer drought in all years. Strong variability at time scales beyond two weeks is only present during the active phases of the monsoon. At the river basin scale, the data show increased cloudiness over the mountain ranges during the afternoon, which moves over the low-lying regions at the foot of the major orographic barriers [the Sierra Madre Occidental (SMO)/Sierra Madre del Sur (SMS) and Trans-Mexican Volcanic Belt (TMVB)], specifically the Balsas and the Rio de Santiago basins at nighttime and in the early morning. At the ridge–valley scale (∼100–200 km), robust day–night (ridge–valley) asymmetries suggest strong local controls on cloud and precipitation, with convective activity along the coastal region of the SMO and topographically forced convection at the foothills of headwater ridges in the Altiplano and the SMS. These day–night spatial shifts in cloudiness and precipitation are similar to those found in the Himalayas at the same spatial scales.

scholarly journals Different drought types and the spatial variability in their hazard, impact, and propagation characteristics

2021 ◽  
Author(s):  
Erik Tijdeman ◽  
Veit Blauhut ◽  
Michael Stoelzle ◽  
Lucas Menzel ◽  
Kerstin Stahl
Keyword(s):  
Spatial Variability ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Spatial Scales ◽  
Time Lag ◽  
Severe Drought ◽  
Drought Management ◽  
Propagation Characteristics ◽  
Drought Impacts ◽  
Drought Hazard

Abstract. Droughts often have a severe impact on environment, society, and economy. Only a multifaceted assessment of such droughts and their impacts can provide insights in the variables and scales that are relevant for drought management. Motivated by this aim, we compared hazard and propagation characteristics as well as impacts of major droughts between 1990–2019 in Southwestern Germany. We bring together high-resolution datasets of air temperature, precipitation, soil moisture simulations, streamflow and groundwater level observations, as well as text-based information on drought impacts. Various drought characteristics were derived from the hydrometeorological and drought impact time series and compared across variables and spatial scales. Results revealed different drought types sharing similar hazard and impact characteristics. The most severe drought type identified is an intense multi-seasonal drought type peaking in summer, i.e. the events in 2003, 2015 and 2018. This drought type appeared in all domains of the hydrological cycle and coincided with high air temperatures, causing a high number and variability of drought impacts. The regional average drought signals of this drought type exhibit typical drought propagation characteristics such as a time lag between meteorological and hydrological drought, whereas propagation characteristics of local drought signals are variable in space. This spatial variability in drought hazard increased when droughts propagated through the hydrological cycle, causing distinct differences among variables, and regional average and local drought information. Accordingly, single variable or regional average drought information is considered to be not sufficient to fully explain the variety of drought impacts that occurred. In addition to large-scale drought monitoring, drought management needs to consider local drought information from different hydrometeorological variables and could be type based.

scholarly journals Parameterization of the Spatial Variability of Rain for Large-Scale Models and Remote Sensing

2015 ◽  
Vol 54 (10) ◽  
pp. 2027-2046 ◽  
Author(s):  
Z. J. Lebo ◽  
C. R. Williams ◽  
G. Feingold ◽  
V. E. Larson
Keyword(s):  
Spatial Variability ◽  
Large Scale ◽  
Rain Rate ◽  
Numerical Models ◽  
Spatial Scales ◽  
Warm Pool ◽  
Radar Data ◽  
Model Output ◽  
Wide Range ◽  
Averaged Model

AbstractThe spatial variability of rain rate R is evaluated by using both radar observations and cloud-resolving model output, focusing on the Tropical Warm Pool–International Cloud Experiment (TWP-ICE) period. In general, the model-predicted rain-rate probability distributions agree well with those estimated from the radar data across a wide range of spatial scales. The spatial variability in R, which is defined according to the standard deviation of R (for R greater than a predefined threshold Rmin) σ(R), is found to vary according to both the average of R over a given footprint μ(R) and the footprint size or averaging scale Δ. There is good agreement between area-averaged model output and radar data at a height of 2.5 km. The model output at the surface is used to construct a scale-dependent parameterization of σ(R) as a function of μ(R) and Δ that can be readily implemented into large-scale numerical models. The variability in both the rainwater mixing ratio qr and R as a function of height is also explored. From the statistical analysis, a scale- and height-dependent formulation for the spatial variability of both qr and R is provided for the analyzed tropical scenario. Last, it is shown how this parameterization can be used to assist in constraining parameters that are often used to describe the surface rain-rate distribution.

scholarly journals Small to large-scale patterns of ground-dwelling spider (Araneae) diversity across northern Canada

FACETS ◽  
2018 ◽  
Vol 3 (1) ◽  
pp. 880-895 ◽  
Author(s):  
Sarah Loboda ◽  
Christopher M. Buddle
Keyword(s):  
Large Scale ◽  
Sampling Design ◽  
Spatial Scales ◽  
Regional Scale ◽  
Biotic Interactions ◽  
Longitudinal Patterns ◽  
Northern Canada ◽  
Multiple Spatial Scales ◽  
Spatial Influence ◽  
Total Species

We examined how Arctic spider (Araneae) biodiversity is distributed at multiple spatial scales in northern Canada using a standardized hierarchical sampling design. We investigated which drivers, environmental or spatial, influence the patterns observed. Spatial patterns of Arctic spider species richness and composition were assessed in 12 sites located in arctic, subarctic, and north boreal ecoclimatic regions, spanning 30 degrees of latitude and 80 degrees of longitude. Variation in diversity was partitioned in relation to multiple environmental and spatial drivers of diversity patterns. Over 23 000 adult spiders, representing 306 species in 14 families, were collected in northern Canada, with 107 species (35% of the total species collected) representing new territorial or provincial records. Spider diversity was structured at the regional scale across ecoclimatic regions but was not structured with latitude. Longitudinal patterns of spider diversity across Canada may be explained by post-glacial dispersal. At local scales, diversity was non-randomly distributed and possibly limited by biotic interactions. We recommend the use of ecoclimatic regions as a framework for conservation of biodiversity in northern Canada and spiders as useful bioindicators that can help us understand the effects of climate change across ecoclimatic regions of northern Canada.

Suborbital Measurements of Spectral Aerosol Optical Depth and Its Variability at Subsatellite Grid Scales in Support of CLAMS 2001

2005 ◽  
Vol 62 (4) ◽  
pp. 993-1007 ◽  
Author(s):  
J. Redemann ◽  
B. Schmid ◽  
J. A. Eilers ◽  
R. Kahn ◽  
R. C. Levy ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Large Scale ◽  
Spatial Scales ◽  
The United States ◽  
Horizontal Distance ◽  
Airborne Measurements ◽  
Low Level ◽  
Modis Aod

Abstract As part of the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) experiment, 10 July–2 August 2001, off the central East Coast of the United States, the 14-channel NASA Ames Airborne Tracking Sunphotometer (AATS-14) was operated aboard the University of Washington’s Convair 580 (CV-580) research aircraft during 10 flights (∼45 flight hours). One of the main research goals in CLAMS was the validation of satellite-based retrievals of aerosol properties. The goal of this study in particular was to perform true over-ocean validations (rather than over-ocean validation with ground-based, coastal sites) at finer spatial scales and extending to longer wavelengths than those considered in previous studies. Comparisons of aerosol optical depth (AOD) between the Aerosol Robotic Network (AERONET) Cimel instrument at the Chesapeake Lighthouse and airborne measurements by AATS-14 in its vicinity showed good agreement with the largest r-square correlation coefficients at wavelengths of 0.38 and 0.5 μm (>0.99). Coordinated low-level flight tracks of the CV-580 during Terra overpass times permitted validation of over-ocean Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (MOD04_L2) multiwavelength AOD data (10 km × 10 km, nadir) in 16 cases on three separate days. While the correlation between AATS-14- and MODIS-derived AOD was weak with an r square of 0.55, almost 75% of all MODIS AOD measurements fell within the prelaunch estimated uncertainty range Δτ = ±0.03 ± 0.05τ. This weak correlation may be due to the small AODs (generally less than 0.1 at 0.5 μm) encountered in these comparison cases. An analogous coordination exercise resulted in seven coincident over-ocean matchups between AATS-14 and Multiangle Imaging Spectroradiometer (MISR) measurements. The comparison between AATS-14 and the MISR standard algorithm regional mean AODs showed a stronger correlation with an r square of 0.94. However, MISR AODs were systematically larger than the corresponding AATS values, with an rms difference of ∼0.06. AATS data collected during nine extended low-level CV-580 flight tracks were used to assess the spatial variability in AOD at horizontal scales up to 100 km. At UV and midvisible wavelengths, the largest absolute gradients in AOD were 0.1–0.2 per 50-km horizontal distance. In the near-IR, analogous gradients rarely reached 0.05. On any given day, the relative gradients in AOD were remarkably similar for all wavelengths, with maximum values of 70% (50 km)−1 and more typical values of 25% (50 km)−1. The implications of these unique measurements of AOD spatial variability for common validation practices of satellite data products and for comparisons to large-scale aerosol models are discussed.

scholarly journals Trophic downgrading reduces spatial variability on rocky reefs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Matthew S. Edwards ◽  
Brenda Konar
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Kelp Forest ◽  
Small Scale ◽  
Kelp Forests ◽  
Forest Communities ◽  
Opposite Pattern ◽  
Rocky Reefs ◽  
Urchin Barren ◽  
Sea Urchin Barrens

Abstract Trophic downgrading in coastal waters has occurred globally during recent decades. On temperate rocky reefs, this has resulted in widespread kelp deforestation and the formation of sea urchin barrens. We hypothesize that the intact kelp forest communities are more spatially variable than the downgraded urchin barren communities, and that these differences are greatest at small spatial scales where the influence of competitive and trophic interactions is strongest. To address this, benthic community surveys were done in kelp forests and urchin barrens at nine islands spanning 1230 km of the Aleutian Archipelago where the loss of predatory sea otters has resulted in the trophic downgrading of the region’s kelp forests. We found more species and greater total spatial variation in community composition within the kelp forests than in the urchin barrens. Further, the kelp forest communities were most variable at small spatial scales (within each forest) and least variable at large spatial scales (among forests on different islands), while the urchin barren communities followed the opposite pattern. This trend was consistent for different trophic guilds (primary producers, grazers, filter feeders, predators). Together, this suggests that Aleutian kelp forests create variable habitats within their boundaries, but that the communities within these forests are generally similar across the archipelago. In contrast, urchin barrens exhibit relatively low variability within their boundaries, but these communities vary substantially among different barrens across the archipelago. We propose this represents a shift from small-scale biological control to large-scale oceanographic control of these communities.

Improved representation of forest snow processes in coarse-resolution models: lessons learnt from upscaling hyper-resolution simulations

2021 ◽  
Author(s):  
Giulia Mazzotti ◽  
Clare Webster ◽  
Richard Essery ◽  
Johanna Malle ◽  
Tobias Jonas
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Large Scale ◽  
Snow Water Equivalent ◽  
Spatial Scales ◽  
Canopy Structure ◽  
Coarse Resolution ◽  
Wide Range ◽  
Snow Model ◽  
High Level

<p>Forest snow cover dynamics affect hydrological regimes, ecosystem processes, and climate feedbacks, and thus need to be captured by model applications that operate across a wide range of spatial scales. At large scales and coarse model resolutions, high spatial variability of the processes shaping forest snow cover evolution creates a major modelling challenge. Variability of canopy-snow interactions is determined by heterogeneous canopy structure and can only be explicitly resolved with hyper-resolution models (<5m).</p><p>Here, we address this challenge with model upscaling experiments with the forest snow model FSM2, using hyper-resolution simulations as intermediary between experimental data and coarse-resolution simulations. When run at 2-m resolution, FSM2 is shown to capture the spatial variability of forest snow dynamics with a high level of detail: Its accurate performance is verified at the level of individual energy balance components based on extensive, spatially distributed sub-canopy measurements of micrometeorological and snow variables, obtained with mobile multi-sensor platforms. Results from hyper-resolution simulations over a 150,000 m<sup>2</sup> domain are then compared to spatially lumped, coarse-resolution runs, where 50m x 50m grid cells are represented by one model run only. For the spatially lumped simulations, we evaluate alternative upscaling strategies, aiming to explore the representation of forest snow processes at model resolutions coarser than the spatial scales at which these processes vary and interact.</p><p>Different upscaling strategies exhibited large discrepancies in simulated (1) distribution of snow water equivalent at peak of winter, and (2) timing of snow disappearance. Our results indicate that detailed canopy structure metrics, as included in hyper-resolution runs, are necessary to capture the spatial variability of forest snow processes even at coarser resolutions. They further demonstrate the relevance of accounting for unresolved sub-grid variability in snowmelt calculations even at relatively small spatial aggregation scales. By identifying important model features, which allow coarse-resolution simulations to approximate spatially averaged results of corresponding hyper-resolution simulations, this work provides recommendations for modelling forest snow processes in medium- to large-scale applications.</p>

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals Insectivorous songbirds as early indicators of future defoliation by spruce budworm

2021 ◽  
Author(s):  
Marion Germain ◽  
Daniel Kneeshaw ◽  
Louis De Grandpré ◽  
Mélanie Desrochers ◽  
Patrick M. A. James ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Spruce Budworm ◽  
Detection Methods ◽  
Maximum Probability ◽  
Point Count ◽  
Probability Of Presence ◽  
Time Lagged ◽  
One Year ◽  
Local Sampling

Abstract Context Although the spatiotemporal dynamics of spruce budworm outbreaks have been intensively studied, forecasting outbreaks remains challenging. During outbreaks, budworm-linked warblers (Tennessee, Cape May, and bay-breasted warbler) show a strong positive response to increases in spruce budworm, but little is known about the relative timing of these responses. Objectives We hypothesized that these warblers could be used as sentinels of future defoliation of budworm host trees. We examined the timing and magnitude of the relationships between defoliation by spruce budworm and changes in the probability of presence of warblers to determine whether they responded to budworm infestation before local defoliation being observed by standard detection methods. Methods We modelled this relationship using large-scale point count surveys of songbirds and maps of cumulative time-lagged defoliation over multiple spatial scales (2–30 km radius around sampling points) in Quebec, Canada. Results All three warbler species responded positively to defoliation at each spatial scale considered, but the timing of their response differed. Maximum probability of presence of Tennessee and Cape May warbler coincided with observations of local defoliation, or provided a one year warning, making them of little use to guide early interventions. In contrast, the probability of presence of bay-breasted warbler consistently increased 3–4 years before defoliation was detectable. Conclusions Early detection is a critical step in the management of spruce budworm outbreaks and rapid increases in the probability of presence of bay-breasted warbler could be used to identify future epicenters and target ground-based local sampling of spruce budworm.

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