scholarly journals Mapping of nutrient regulating ecosystem service supply and demand on different scales in Schleswig-Holstein, Germany

One Ecosystem ◽  
2018 ◽  
Vol 3 ◽  
pp. e22509 ◽  
Author(s):  
Sabine Bicking ◽  
Benjamin Burkhard ◽  
Marion Kruse ◽  
Felix Müller
Keyword(s):  
Land Management ◽  
Ecosystem Service ◽  
Large Scale ◽  
Spatial Information ◽  
Spatial Scales ◽  
Supply And Demand ◽  
Regional Scale ◽  
Federal State ◽  
Nutrient Regulation ◽  
Large Scale Data

This study deals with one of the regulating ecosystem services, nutrient regulation. In order to guarantee sustainable land management, it is of great relevance to gain spatial information on this ecosystem service. Unsustainable land management with regard to nutrient regulation may, for example, result in eutrophication which has been identified as a major threat for the environmental state of our water bodies. In the first step of research, the potential supplies and demands of/for nutrient regulation were assessed and mapped at two different spatial scales: The German federal state of Schleswig-Holstein (regional scale) and the Bornhöved Lakes District (local scale). The assessment was undertaken for nitrogen, as an exemplary nutrient. Subsequently, potential supply and demand, combined with the nitrate leaching potential and the groundwater nitrate concentration, were incorporated into a correlation analysis. The data was statistically analysed with varying pre-processing and spatial resolutions. The statistical analysis reveals that large scale data with low resolution leads to more uncertain results. Decreasing the spatial scale and increasing the resolution of the data through a spatially more explicit assessment, leads to more explicit results. It is striking that the study reveals a spatial mismatch between the potential supply and demand for the ecosystem service nutrient regulation, which denotes unsustainable land management in the study areas.

scholarly journals Regional-scale lateral carbon transport and CO<sub>2</sub> evasion in temperate stream catchments

2017 ◽  
Vol 14 (21) ◽  
pp. 5003-5014 ◽  
Author(s):  
Katrin Magin ◽  
Celia Somlai-Haase ◽  
Ralf B. Schäfer ◽  
Andreas Lorke
Keyword(s):  
Catchment Area ◽  
Large Scale ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Regional Scale ◽  
Stream Network ◽  
Carbon Export ◽  
Data Set ◽  
Catchment Areas ◽  
Temperate Stream

Abstract. Inland waters play an important role in regional to global-scale carbon cycling by transporting, processing and emitting substantial amounts of carbon, which originate mainly from their catchments. In this study, we analyzed the relationship between terrestrial net primary production (NPP) and the rate at which carbon is exported from the catchments in a temperate stream network. The analysis included more than 200 catchment areas in southwest Germany, ranging in size from 0.8 to 889 km2 for which CO2 evasion from stream surfaces and downstream transport with stream discharge were estimated from water quality monitoring data, while NPP in the catchments was obtained from a global data set based on remote sensing. We found that on average 13.9 g C m−2 yr−1 (corresponding to 2.7 % of terrestrial NPP) are exported from the catchments by streams and rivers, in which both CO2 evasion and downstream transport contributed about equally to this flux. The average carbon fluxes in the catchments of the study area resembled global and large-scale zonal mean values in many respects, including NPP, stream evasion and the carbon export per catchment area in the fluvial network. A review of existing studies on aquatic–terrestrial coupling in the carbon cycle suggests that the carbon export per catchment area varies in a relatively narrow range, despite a broad range of different spatial scales and hydrological characteristics of the study regions.

scholarly journals Regional-scale lateral carbon transport and CO<sub>2</sub> evasion in temperate stream catchments

2017 ◽  
Author(s):  
Katrin Magin ◽  
Celia Somlai-Haase ◽  
Ralf B. Schäfer ◽  
Andreas Lorke
Keyword(s):  
Large Scale ◽  
Net Primary Production ◽  
Spatial Scales ◽  
Regional Scale ◽  
Water Quality Monitoring ◽  
Stream Network ◽  
Data Set ◽  
Mean Values ◽  
Catchment Areas ◽  
Temperate Stream

Abstract. Inland waters play an important role in regional to global scale carbon cycling by transporting, processing and emitting substantial amounts of carbon, which originate mainly from their catchments. In this study, we analyzed the relationship between terrestrial net primary production (NPP) and the rate at which carbon is exported from the catchments in a temperate stream network. The analysis included more than 200 catchment areas in southwest Germany, ranging in size from 0.8 to 889 km2 for which CO2 evasion from stream surfaces and downstream transport with stream discharge were estimated from water quality monitoring data, while NPP in the catchments was obtained from a global data set based on remote sensing. We found that on average 2.7 % of terrestrial NPP (13.9 g C m2 yr−1) are exported from the catchments by streams and rivers, in which both CO2 evasion and downstream transport contributed about equally to this flux. The average carbon fluxes in the catchments of the study area resembled global and large-scale zonal mean values in many respects, including NPP, stream evasion as well as the catchment-specific total export rate of carbon in the fluvial network. A review of existing studies on aquatic-terrestrial coupling in the carbon cycle suggests that the catchment-specific carbon export varies in a relatively narrow range, despite a broad range of different spatial scales and hydrological characteristics of the study regions.

Applying the climatic water balance to the Volta basin as an accounting framework to aid policy makers in understanding climate pressures on the water-energy-food (W-E-F) nexus

2020 ◽  
Author(s):  
Nathan Forsythe ◽  
David Pritchard ◽  
Hayley Fowler
Keyword(s):  
Sustainable Development ◽  
Water Balance ◽  
Land Management ◽  
Large Scale ◽  
Management Practices ◽  
Spatial Scales ◽  
Policy Makers ◽  
Volta Basin ◽  
Trade Offs ◽  
Moisture Supply

&lt;p&gt;The multinational FutureDAMS consortium -- funded by the UK's Global Challenges Research Fund -- is working to improve the design, selection and operation of dams to support sustainable development. Existing and planned large water storage infrastructure systems have the potential to make a significant contribution towards achieving the Sustainable Development Goals and Paris climate change commitments. But maximising the benefits while minimising the negative social and environmental impacts of large-scale infrastructure in the river basins comprising the multifunctional cores of the Water-Energy-Food (WEF) nexus remains a challenge. One critical aspect of this challenge is the difficulty of achieving uptake of scientific guidance by policy makers and other influential stakeholders.&lt;/p&gt;&lt;p&gt;The climatic water balance (CWB), i.e. precipitation minus potential evapotranspiration, provides a methodological framework for understanding moisture supply-demand equilibrium at a range of spatial scales including those relevant to land management &amp;#8211; administrative districts and tributary watersheds &amp;#8211; within basins. The CWB framework understood as an accounting analogy &amp;#8211; i.e. rainfall as income, evapotranspiration as expenditure &amp;#8211; can be comprehensible to scientific lay persons and help to understand the climate pressures which constrain WEF resource management. Viewed through a CWB framework, rural lands are critical both as determinants of rainfall partitioning between runoff and infiltration as well as areas of consumptive water usage for food production. Runoff entering engineered river systems becomes available for satisfying water supply and (hydropower) energy demands. As a transboundary river basin in a region experiencing substantial demographic growth and with strong aspirations for rapid economic development, inter-sectoral tensions are likely as Volta basin decision makers and economic actors seek to satisfy elements of the W-E-F nexus. By quantifying spatiotemporal moisture supply-demand balance conditions the CWB can provide valuable information to quantify trade-offs and potential synergies resulting from land management practices, infrastructure development and water allocation policies.&lt;/p&gt;&lt;p&gt;In this work we will examine point/site-based values and spatial aggregates of CWB for a range of locations and scales within the larger Volta basin. For each case we will identify key WEF issues which are influenced by the CWB as well as stakeholders whose decision-making processes could be informed by insights derived from the CWB (accounting) framework.&lt;/p&gt;

scholarly journals Emergent Behavior and Uncertainty in Multimodel Climate Projections of Precipitation Trends at Small Spatial Scales

2006 ◽  
Vol 19 (21) ◽  
pp. 5554-5569 ◽  
Author(s):  
P. Good ◽  
J. Lowe
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Scale Effects ◽  
Spatial Scales ◽  
Regional Scale ◽  
Emergent Behavior ◽  
Small Scale ◽  
Climate Projections ◽  
New Methods ◽  
Precipitation Trends

Abstract Aspects of model emergent behavior and uncertainty in regional- and small-scale effects of increasing CO2 on seasonal (June–August) precipitation are explored. Nineteen different climate models are studied. New methods of comparing multiple climate models reveal a clearer and more impact-relevant view of precipitation projections for the current century. First, the importance of small spatial scales in multimodel projections is demonstrated. Local trends can be much larger than or even have an opposing sign to the large-scale regional averages used in previous studies. Small-scale effects of increasing CO2 and natural internal variability both play important roles here. These small-scale features make multimodel comparisons difficult for precipitation. New methods that allow information from small spatial scales to be usefully compared across an ensemble of multiple models are presented. The analysis philosophy of this study works with statistical distributions of small-scale variations within climatological regions. A major result of this work is a set of emergent relationships coupling the small- and regional-scale effects of CO2 on precipitation trends. Within each region, a single relationship fits the ensemble of 19 different climate models. Using these relationships, a surprisingly large part of the intermodel variance in small-scale effects of CO2 is explainable simply by the intermodel variance in the regional mean (a form of pattern scaling). Different regions show distinctly different relationships. These relationships imply that regional mean results are still useful, as long as the interregional variation in their relationship with impact-relevant extreme trends is recognized. These relationships are used to present a clear but rich picture of an aspect of model uncertainty, characterized by the intermodel spread in seasonal precipitation trends, including information from small spatial scales.

scholarly journals Tree-Based and Optimum Cut-Based Origin-Destination Flow Clustering

2019 ◽  
Vol 8 (11) ◽  
pp. 477 ◽  
Author(s):  
Xiang ◽  
Wu
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Similarity Criterion ◽  
Human Beings ◽  
Travel Patterns ◽  
Self Similarity ◽  
Large Scale Data ◽  
Spatiotemporal Clustering ◽  
Maximum Spanning Tree ◽  
Low Efficiency

Data about the movements of diverse objects, including human beings, animals, and commodities, are collected in growing amounts as location-aware technologies become pervasive. Clustering has become an increasingly important analytical tool for revealing travel patterns from large-scale movement datasets. Most existing methods for origin-destination (OD) flow clustering focus on the geographic properties of an OD flow but ignore the temporal information preserved in the OD flow, which reflects the dynamic changes in the travel patterns over time. In addition, most methods require some predetermined parameters as inputs and are difficult to adjust considering the changes in the users’ demands. To overcome such limitations, we present a novel OD flow clustering method, namely, TOCOFC (Tree-based and Optimum Cut-based Origin-Destination Flow Clustering). A similarity measurement method is proposed to quantify the spatial similarity relationship between OD flows, and it can be extended to measure the spatiotemporal similarity between OD flows. By constructing a maximum spanning tree and splitting it into several unrelated parts, we effectively remove the noise in the flow data. Furthermore, a recursive two-way optimum cut-based method is utilized to partition the graph composed of OD flows into OD flow clusters. Moreover, a criterion called CSSC (Child tree/Child graph Self-Similarity Criterion) is formulated to determine if the clusters meet the output requirements. By modifying the parameters, TOCOFC can obtain clustering results for different time scales and spatial scales, which makes it possible to study movement patterns from a multiscale perspective. However, TOCOFC has the disadvantages of low efficiency and large memory consumption, and it is not conducive to quickly handling large-scale data. Compared with previous works, TOCOFC has a better clustering performance, which is reflected in the fact that TOCOFC can guarantee a balance between clusters and help to fully understand the corresponding patterns. Being able to perform the spatiotemporal clustering of OD flows is also a highlight of TOCOFC, which will help to capture the differences in the patterns at different times for a deeper analysis. Extensive experiments on both artificial spatial datasets and real-world spatiotemporal datasets have demonstrated the effectiveness and flexibility of TOCOFC.

Opposite effects of ocean temperature on survival rates of 120 stocks of Pacific salmon (Oncorhynchus spp.) in northern and southern areas

2002 ◽  
Vol 59 (3) ◽  
pp. 456-463 ◽  
Author(s):  
Franz J Mueter ◽  
Randall M Peterman ◽  
Brian J Pyper
Keyword(s):  
Large Scale ◽  
Pacific Salmon ◽  
Spatial Scales ◽  
Regional Scale ◽  
Survival Rates ◽  
Climatic Changes ◽  
Sea Surface ◽  
Ocean Temperature ◽  
Climate Anomalies ◽  
The Pacific

To improve the understanding of linkages between ocean conditions and salmon productivity, we estimated effects of ocean temperature on survival rates of three species of Pacific salmon (Oncorhynchus spp.) across 120 stocks. This multistock approach permitted more precise estimates of effects than standard single-stock analyses. The estimated effects were opposite in sign between northern and southern stocks and were quite consistent across stocks within species and areas. Warm anomalies in coastal temperatures were associated with increased survival rates for stocks in Alaska and decreased survival rates in Washington and British Columbia, suggesting that different mechanisms determine survival rates in the two areas. Regional-scale sea surface temperatures (SST, within several hundred kilometres of a stock's ocean entry point) were a much better predictor of survival rates than large-scale climate anomalies associated with the Pacific Decadal Oscillation (PDO), suggesting that survival rates are primarily linked to environmental conditions at regional spatial scales. With appropriate cautions, these results may be used to predict the potential effects of climatic changes on salmon productivity in different areas of the Northeast Pacific.

scholarly journals An Unsupervised Deep Learning System for Acoustic Scene Analysis

2020 ◽  
Vol 10 (6) ◽  
pp. 2076
Author(s):  
Mou Wang ◽  
Xiao-Lei Zhang ◽  
Susanto Rahardja
Keyword(s):  
Spectral Clustering ◽  
Large Scale ◽  
Spatial Information ◽  
Learning System ◽  
Scene Analysis ◽  
Acoustic Feature ◽  
Large Scale Data ◽  
Unsupervised Deep Learning ◽  
Audio Data ◽  
Low Dimensional

Acoustic scene analysis has attracted a lot of attention recently. Existing methods are mostly supervised, which requires well-predefined acoustic scene categories and accurate labels. In practice, there exists a large amount of unlabeled audio data, but labeling large-scale data is not only costly but also time-consuming. Unsupervised acoustic scene analysis on the other hand does not require manual labeling but is known to have significantly lower performance and therefore has not been well explored. In this paper, a new unsupervised method based on deep auto-encoder networks and spectral clustering is proposed. It first extracts a bottleneck feature from the original acoustic feature of audio clips by an auto-encoder network, and then employs spectral clustering to further reduce the noise and unrelated information in the bottleneck feature. Finally, it conducts hierarchical clustering on the low-dimensional output of the spectral clustering. To fully utilize the spatial information of stereo audio, we further apply the binaural representation and conduct joint clustering on that. To the best of our knowledge, this is the first time that a binaural representation is being used in unsupervised learning. Experimental results show that the proposed method outperforms the state-of-the-art competing methods.

scholarly journals Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

2016 ◽  
Vol 113 (42) ◽  
pp. 11889-11894 ◽  
Author(s):  
Roland A. Knapp ◽  
Gary M. Fellers ◽  
Patrick M. Kleeman ◽  
David A. W. Miller ◽  
Vance T. Vredenburg ◽  
...  
Keyword(s):  
Sierra Nevada ◽  
Large Scale ◽  
Multiple Stressors ◽  
Spatial Scales ◽  
Large Fraction ◽  
Regional Scale ◽  
Global Scale ◽  
Amphibian Declines ◽  
Active Management ◽  
Introduced Fish

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

scholarly journals Enhanced Detectability of Added Value in Limited-Area Model Results Separated into Different Spatial Scales

2006 ◽  
Vol 134 (8) ◽  
pp. 2180-2190 ◽  
Author(s):  
Frauke Feser
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Regional Climate ◽  
Regional Scale ◽  
Regional Climate Models ◽  
Added Value ◽  
Limited Area ◽  
Near Surface ◽  
Pattern Correlation

Abstract Regional climate models (RCMs) are a widely used tool to describe regional-scale climate variability and change. However, the added value provided by such models is not well explored so far, and claims have been made that RCMs have little utility. Here, it is demonstrated that RCMs are indeed returning significant added value. Employing appropriate spatial filters, the scale-dependent skill of a state-of-the-art RCM (with and without nudging of large scales) is examined by comparing its skill with that of the global reanalyses driving the RCM. This skill is measured by pattern correlation coefficients of the global reanalyses or the RCM simulation and, as a reference, of an operational regional weather analysis. For the spatially smooth variable air pressure the RCM improves this aspect of the simulation for the medium scales if the RCM is driven with large-scale constraints, but not for the large scales. For the regionally more structured quantity near-surface temperature the added value is more obvious. The simulation of medium-scale 2-m temperature anomaly fields amounts to an increase of the mean pattern correlation coefficient up to 30%.

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.

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