scholarly journals High-Resolution, Long-Term Trends in Relative Abundance from Spatial Modeling of Continent-Wide Bird Counts

2018 ◽  
Author(s):  
Timothy D. Meehan ◽  
Nicole L. Michel ◽  
Håvard Rue
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Bird Species ◽  
Current Standard ◽  
Science Data ◽  
Modeling Framework ◽  
American Robin ◽  
Order Of Magnitude ◽  
Community Science

AbstractContinent-wide bird counts by community volunteers provide valuable information about the conservation needs of many bird species. The statistical modeling techniques commonly used to analyze these counts provide robust long-term trend estimates from heterogeneous community science data at regional, national, and continental scales. Here we present a novel modeling framework that increases the spatial resolution of trend estimates, and reduces the computational burden of trend estimation, each by an order of magnitude. We demonstrate the approach with data for the American Robin (Turdus migratorius) from Audubon Christmas Bird Counts conducted between 1966 and 2017, and show that aggregate regional trend estimates from the proposed method align well with those from the current standard method. Thus, it appears that the proposed technique can provide reasonable large-scale trend estimates for users concerned with general patterns, while also providing higher resolution estimates for others examining correlates of abundance trends at finer spatial scales.

scholarly journals Challenges and benefits of using unstructured citizen science data to estimate seasonal timing of bird migration across large scales

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246572
Author(s):  
Nadja Weisshaupt ◽  
Aleksi Lehikoinen ◽  
Terhi Mäkinen ◽  
Jarmo Koistinen
Keyword(s):  
Large Scale ◽  
Bird Species ◽  
Science Data ◽  
The Past ◽  
Migration Phenology ◽  
Ringing Data ◽  
Valuable Complement ◽  
Species Specific ◽  
Model Approach

Millions of bird observations have been entered on online portals in the past 20 years either as checklists or arbitrary individual entries. While several hundred publications have been written on a variety of topics based on bird checklists worldwide, unstructured non-checklist observations have received little attention and praise by academia. In the present study we tested the suitability of non-checklist data to estimate key figures of large-scale migration phenology in four zones covering the whole of Finland. For that purpose, we analysed 10 years of ornithological non-checklist data including over 400 million. individuals of 115 bird species. We discuss bird- and human-induced effects to be considered in handling non-checklist data in this context and describe applied methodologies to address these effects. We calculated 5%, 50% and 95% percentile dates of spring and autumn migration period for all species in all four zones. For validation purposes we compared the temporal distributions of 43 bird species with migration phenology from standardized long-term ringing data in autumn of which 24 species (56%) showed similar medians. In a model approach, non-checklist data successfully revealed latitudinal migration progression in spring and autumn. Overall, non-checklist data proved to be well suited to determine descriptors of migration phenology in Northern Europe which are challenging to attain by any other currently available means. The effort-to-yield ratio of data processing was commensurate to the outcomes. The unprecedented spatiotemporal coverage makes non-checklist data a valuable complement to current migration databases from bird observatories. The basic concept of the present methodology is applicable to data from other bird portals, if combined with local field ornithological knowledge and literature. Species-specific descriptors of migration phenology can be potentially used in climate change studies and to support echo interpretation in radar ornithology.

scholarly journals Variability of Cloudiness over Mountain Terrain in the Western United States

2017 ◽  
Vol 18 (5) ◽  
pp. 1227-1245 ◽  
Author(s):  
Edwin Sumargo ◽  
Daniel R. Cayan
Keyword(s):  
United States ◽  
Large Scale ◽  
Spatial Scales ◽  
High Elevation ◽  
Empirical Orthogonal Functions ◽  
Western United States ◽  
Spatial And Temporal Variability ◽  
Regional Patterns ◽  
Cloud Albedo

Abstract This study investigates the spatial and temporal variability of cloudiness across mountain zones in the western United States. Daily average cloud albedo is derived from a 19-yr series (1996–2014) of half-hourly Geostationary Operational Environmental Satellite (GOES) images. During springtime when incident radiation is active in driving snowmelt–runoff processes, the magnitude of daily cloud variations can exceed 50% of long-term averages. Even when aggregated over 3-month periods, cloud albedo varies by ±10% of long-term averages in many locations. Rotated empirical orthogonal functions (REOFs) of daily cloud albedo anomalies over high-elevation regions of the western conterminous United States identify distinct regional patterns, wherein the first five REOFs account for ~67% of the total variance. REOF1 is centered over Northern California and Oregon and is pronounced between November and March. REOF2 is centered over the interior northwest and is accentuated between March and July. Each of the REOF/rotated principal components (RPC) modes associates with anomalous large-scale atmospheric circulation patterns and one or more large-scale teleconnection indices (Arctic Oscillation, Niño-3.4, and Pacific–North American), which helps to explain why anomalous cloudiness patterns take on regional spatial scales and contain substantial variability over seasonal time scales.

Generation of Low-Frequency Spiciness Variability in the Thermocline*

2011 ◽  
Vol 41 (2) ◽  
pp. 365-377 ◽  
Author(s):  
Thomas Kilpatrick ◽  
Niklas Schneider ◽  
Emanuele Di Lorenzo
Keyword(s):  
Markov Model ◽  
Large Scale ◽  
Spatial Scales ◽  
Low Frequency ◽  
Passive Tracer ◽  
Wind Stress Curl ◽  
Frequency Spectra ◽  
Low Frequencies ◽  
Geostrophic Advection

Abstract The generation of variance by anomalous advection of a passive tracer in the thermocline is investigated using the example of density-compensated temperature and salinity anomalies, or spiciness. A coupled Markov model is developed in which wind stress curl forces the large-scale baroclinic ocean pressure that in turn controls the anomalous geostrophic advection of spiciness. The “double integration” of white noise atmospheric forcing by this Markov model results in a frequency (ω) spectrum of large-scale spiciness proportional to ω−4, so that spiciness variability is concentrated at low frequencies. An eddy-permitting regional model hindcast of the northeast Pacific (1950–2007) confirms that time series of large-scale spiciness variability are exceptionally smooth, with frequency spectra ∝ ω−4 for frequencies greater than 0.2 cpy. At shorter spatial scales (wavelengths less than ∼500 km), the spiciness frequency spectrum is whitened by mesoscale eddies, but this eddy-forced variability can be filtered out by spatially averaging. Large-scale and long-term measurements are needed to observe the variance of spiciness or any other passive tracer subject to anomalous advection in the thermocline.

scholarly journals Winners and losers over 35 years of dragonfly and damselfly distributional change in Germany

2020 ◽  
Author(s):  
D.E Bowler ◽  
D. Eichenberg ◽  
K.J. Conze ◽  
F. Suhling ◽  
K. Baumann ◽  
...  
Keyword(s):  
Citizen Science ◽  
Large Scale ◽  
Positive Trend ◽  
Science Data ◽  
Running Water ◽  
Distributional Change ◽  
Novel Approach ◽  
Occupancy Detection ◽  
Declining Species

AbstractRecent studies suggest insect declines in parts of Europe; however, the generality of these trends across different taxa and regions remains unclear. Standardized data are not available to assess large-scale, long-term changes for most insect groups but opportunistic citizen science data is widespread for some taxa. We compiled over 1 million occurrence records of Odonata (dragonflies and damselflies) from different regional databases across Germany. We used occupancy-detection models to estimate annual distributional changes between 1980 and 2016 for each species. We related species attributes to changes in the species’ distributions and inferred possible drivers of change. Species showing increases were generally warm-adapted species and/or running water species while species showing decreases were cold-adapted species using standing water habitats such as bogs. We developed a novel approach using time-series clustering to identify groups of species with similar patterns of temporal change. Using this method, we defined five typical patterns of change for Odonata – each associated with a specific combination of species attributes. Overall, trends in Odonata provide mixed news – improved water quality, coupled with positive impacts of climate change, could explain the positive trend status of many species. At the same time, declining species point to conservation challenges associated with habitat loss and degradation. Our study demonstrates the great value of citizen science data for assessing large-scale distributional change and conservation decision-making.

scholarly journals Emergence of a cosmological constant in anisotropic fluid cosmology

2021 ◽  
pp. 2150156
Author(s):  
M. Cadoni ◽  
A. P. Sanna
Keyword(s):  
Cosmological Constant ◽  
Large Scale ◽  
Spatial Scales ◽  
Time Dependent ◽  
Anisotropic Fluid ◽  
Einstein Field Equations ◽  
Field Equations ◽  
Coincidence Problem ◽  
Order Of Magnitude ◽  
Natural Way

In this paper, we investigate anisotropic fluid cosmology in a situation where the space–time metric back-reacts in a local, time-dependent way to the presence of inhomogeneities. We derive exact solutions to the Einstein field equations describing Friedmann–Lemaítre–Robertson–Walker (FLRW) large-scale cosmological evolution in the presence of local inhomogeneities and time-dependent backreaction. We use our derivation to tackle the cosmological constant problem. A cosmological constant emerges by averaging the backreaction term on spatial scales of the order of 100 Mpc, at which our universe begins to appear homogeneous and isotropic. We find that the order of magnitude of the “emerged” cosmological constant agrees with astrophysical observations and is related in a natural way to baryonic matter density. Thus, there is no coincidence problem in our framework.

scholarly journals Comparing the reliability of relative bird abundance indices from standardized surveys and community science data at finer resolutions

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257226
Author(s):  
Mei-Ling Emily Feng ◽  
Judy Che-Castaldo
Keyword(s):  
Spatial Scales ◽  
Biodiversity Loss ◽  
Ecological Crisis ◽  
Science Data ◽  
Bird Abundance ◽  
Biological Surveys ◽  
Bird Populations ◽  
Modeling Approaches ◽  
Annual Changes ◽  
Community Science

Biodiversity loss is a global ecological crisis that is both a driver of and response to environmental change. Understanding the connections between species declines and other components of human-natural systems extends across the physical, life, and social sciences. From an analysis perspective, this requires integration of data from different scientific domains, which often have heterogeneous scales and resolutions. Community science projects such as eBird may help to fill spatiotemporal gaps and enhance the resolution of standardized biological surveys. Comparisons between eBird and the more comprehensive North American Breeding Bird Survey (BBS) have found these datasets can produce consistent multi-year abundance trends for bird populations at national and regional scales. Here we investigate the reliability of these datasets for estimating patterns at finer resolutions, inter-annual changes in abundance within town boundaries. Using a case study of 14 focal species within Massachusetts, we calculated four indices of annual relative abundance using eBird and BBS datasets, including two different modeling approaches within each dataset. We compared the correspondence between these indices in terms of multi-year trends, annual estimates, and inter-annual changes in estimates at the state and town-level. We found correspondence between eBird and BBS multi-year trends, but this was not consistent across all species and diminished at finer, inter-annual temporal resolutions. We further show that standardizing modeling approaches can increase index reliability even between datasets at coarser temporal resolutions. Our results indicate that multiple datasets and modeling methods should be considered when estimating species population dynamics at finer temporal resolutions, but standardizing modeling approaches may improve estimate correspondence between abundance datasets. In addition, reliability of these indices at finer spatial scales may depend on habitat composition, which can impact survey accuracy.

Interdisciplinary data-constrained 3-D potential field modelling with IGMAS+

2021 ◽  
Author(s):  
Denis Anikiev ◽  
Hans-Jürgen Götze ◽  
Judith Bott ◽  
Angela Maria Gómez-García ◽  
Maria Laura Gomez Dacal ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Geophysical Methods ◽  
Receiver Functions ◽  
Research Centre ◽  
Small Scale ◽  
Gravity And Magnetic ◽  
Structural Density ◽  
Scale Models

<p>We introduce a modelling concept for the construction of 3-D data-constrained subsurface structural density models at different spatial scales: from large-scale models (thousands of square km) to regional (hundreds of square km) and small-scale (tens of square km) models used in applied geophysics. These models are important for understanding the drivers of geohazards, for efficient and sustainable extraction of resources from sedimentary basins such as groundwater, hydrocarbons or deep geothermal energy, as well as for investigation of capabilities of long-term underground storage of gas and radioactive materials.</p><p>The modelling concept involves interactive fitting of potential fields (gravity and magnetics) and their derivatives within IGMAS+ (Interactive Gravity and Magnetic Application System), a well-known software tool with almost 40 years of development behind it. The core of IGMAS+ is the analytical solution of the volume integral for gravity and magnetic effects of homogeneous bodies, bounded by polyhedrons of triangulated model interfaces. The backbone model is constrained by interdisciplinary data, e.g. geological maps, seismic reflection and refraction profiles, structural signatures obtained from seismic receiver functions, local surveys etc. The software supports spherical geometries to resolve the first-order effects related to the curvature of the Earth, which is especially important for large-scale models.</p><p>Currently being developed and maintained at the Helmholtz Centre Potsdam – GFZ German Research Centre, IGMAS+ has a cross-platform implementation with parallelization of computations and optimized storage. The powerful graphical interface makes the interactive modelling and geometry modification process user-friendly and robust. Historically IGMAS+ is free for research and education purposes and has a long-term plan to remain so.</p><p>IGMAS+ has been used in various tectonic settings and we demonstrate its flexibility and usability on several lithospheric-scale case studies in South America and Europe.</p><p>Both science and industry are close to the goal of treating all available geoscientific data and geophysical methods inside a single subsurface model that aims to integrate most of the interdisciplinary measurement-based constraints and essential structural trends coming from geology. This approach presents challenges for both its implementation within the modelling software and the usability and plausibility of generated results, requiring a modelling concept that integrates the data methods in a feasible way together with recent advances in data science methods. As such, we present the future outlook of our modelling concept in regards to these challenges.</p>

scholarly journals Prototyping a Methodology for Long-Term (1680–2100) Historical-to-Future Landscape Modeling for the Conterminous United States

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 536
Author(s):  
Jordan Dornbierer ◽  
Steve Wika ◽  
Charles Robison ◽  
Gregory Rouze ◽  
Terry Sohl
Keyword(s):  
United States ◽  
Land Cover ◽  
River Basin ◽  
Landscape Change ◽  
Spatial Scales ◽  
The United States ◽  
Modeling Framework ◽  
Delaware River ◽  
Future Landscape

Land system change has been identified as one of four major Earth system processes where change has passed a destabilizing threshold. A historical record of landscape change is required to understand the impacts change has had on human and natural systems, while scenarios of future landscape change are required to facilitate planning and mitigation efforts. A methodology for modeling long-term historical and future landscape change was applied in the Delaware River Basin of the United States. A parcel-based modeling framework was used to reconstruct historical landscapes back to 1680, parameterized with a variety of spatial and nonspatial historical datasets. Similarly, scenarios of future landscape change were modeled for multiple scenarios out to 2100. Results demonstrate the ability to represent historical land cover proportions and general patterns at broad spatial scales and model multiple potential future landscape trajectories. The resulting land cover collection provides consistent data from 1680 through 2100, at a 30-m spatial resolution, 10-year intervals, and high thematic resolution. The data are consistent with the spatial and thematic characteristics of widely used national-scale land cover datasets, facilitating use within existing land management and research workflows. The methodology demonstrated in the Delaware River Basin is extensible and scalable, with potential applications at national scales for the United States.

On large-scale dynamics and community structure in forest birds: lessons from some eucalypt forests of southeastern Australia

1995 ◽  
Vol 350 (1334) ◽  
pp. 369-379 ◽  
Keyword(s):  
Large Scale ◽  
Necessary Conditions ◽  
Spatial Scales ◽  
Bird Species ◽  
Sympatric Species ◽  
Bird Communities ◽  
Individual Species ◽  
Ecological Communities ◽  
Individual Bird ◽  
Southeastern Australia

Models of ecological communities, including coevolved patterns of resource use among sympatric species (for example, ‘resource partitioning’), are poor or inadequate representations of natural systems despite intense theoretical effort for many years. Some of these difficulties are due to a failure to recognize the necessary conditions for community patterns to develop, which are largely controlled by the dynamic characteristics of individual species. In continental bird communities — examples of which are considered here - these necessary conditions often will not be met owing to the mobility of most species. Here I document the degrees to which the large-scale dynamics (over hundreds of km) of individual bird species are expressed in community terms in five forest-habitat types throughout the year. These data demonstrate that continental bird communities are so dynamic that the conditions for the development of definite structure are unlikely to be met in either proximate or evolutionary time. The failure of community theories to account for and predict structure probably reflects too much concentration on mechanisms at inappropriate spatial scales.

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