scholarly journals Ecosystem-based adaptation in Lake Victoria Basin; synergies and trade-offs

2021 ◽  
Vol 8 (6) ◽  
pp. 201847
Author(s):  
Dorice Agol ◽  
Hannah Reid ◽  
Florence Crick ◽  
Hausner Wendo
Keyword(s):  
Climate Change ◽  
Lake Victoria ◽  
Spatial Scales ◽  
Analytical Framework ◽  
Lake Victoria Basin ◽  
Adaptation To Climate Change ◽  
Group Discussions ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Trade Offs

Healthy ecosystems such as forests and wetlands have a great potential to support adaptation to climate change and are the foundation of sustainable livelihoods. Ecosystem-based adaptation (EbA) can help to protect and maintain healthy ecosystems providing resilience against the impacts of climate change. This paper explores the role of EbA in reconciling socio-economic development with the conservation and restoration of nature in Lake Victoria Basin, Kenya, East Africa. Using selected ecosystems in the Lake region, the paper identifies key EbA approaches and explores trade-offs and synergies at spatial and temporal scales and between different stakeholders. The research methods used for this study include site visits, key informant interviews, focus group discussions, participatory workshops and literature reviews. An analytical framework is applied to advance the understanding of EbA approaches and how they lead to synergies and trade-offs between ecosystem services provision at spatial and temporal scales and multiple stakeholders. Our results show that EbA approaches such as ecosystem restoration have the potential to generate multiple adaptation benefits as well as synergies and trade-offs occurring at different temporal and spatial scales and affecting various stakeholder groups. Our paper underscores the need to identify EbA trade-offs and synergies and to explore the ways in which they are distributed in space and time and between different stakeholders to design better environmental and development programmes.

Comparison of different statistical downscaling methods for climate change rainfall projections over the Lake Victoria basin considering CMIP3 and CMIP5

2016 ◽  
Vol 12 ◽  
pp. 31-45 ◽  
Author(s):  
Charles Onyutha ◽  
Hossein Tabari ◽  
Agnieszka Rutkowska ◽  
Paul Nyeko-Ogiramoi ◽  
Patrick Willems
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Lake Victoria ◽  
Lake Victoria Basin

Robust modelling to address UPH19 to predict future hydrological responses for water resources adaptation under climate change

2021 ◽  
Author(s):  
Francis Chiew ◽  
Hongxing Zheng ◽  
Jai Vaze
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Accurate Estimate ◽  
Severe Drought ◽  
Hydrological Models ◽  
Adaptation To Climate Change ◽  
Projected Range ◽  
Trade Offs ◽  
Eastern Australia ◽  
Robust Modelling

<p>This paper addresses the implications of UPH19 in extrapolating hydrological models to predict the future and assessing water resources adaptation to climate change. Many studies have now shown that traditional application of hydrological models calibrated against past observations will underestimate the range in the projected future hydrological impact, that is, it will underestimate the decline in runoff where a runoff decrease is projected, and underestimate the increase in runoff where a runoff increase is projected. This study opportunistically uses data from south-eastern Australia which recently experienced a long and severe drought lasting more than ten years and subsequent partial hydrological recovery from the drought. The paper shows that a more robust calibration of rainfall-runoff models to produce good calibration metrics in both the dry periods and wet periods, at the expense of the best calibration over the entire data period, can produce a more accurate estimate of the uncertainty in the projected future runoff, but cannot entirely eliminate the modelling limitation of underestimating the projected range in future runoff. This is because of the need to consider trade-offs between the calibration objectives, particularly in simulating the dry periods, versus enhanced bias that results from the consideration. Hydrological models must therefore also need to be adapted to reflect the non-stationary nature of catchment and vegetation responses in a changing climate under warmer conditions, higher CO<sub>2</sub> and changed precipitation patterns. This is an active area of research in UPH19, and some ideas relevant to this region will be presented.</p>

Community Ecology of Stream Fishes: Concepts, Approaches, and Techniques

2010 ◽  
Keyword(s):  
Great Plains ◽  
Life Histories ◽  
Environmental Heterogeneity ◽  
Environmental Variability ◽  
Spatial Scales ◽  
Stream Fish ◽  
Metapopulation Dynamics ◽  
Stream Fishes ◽  
Spatial And Temporal Scales ◽  
Trade Offs

<em>Abstract</em>.—Stream fishes carry out their life histories across broad spatial and temporal scales, leading to spatially structured populations. Therefore, incorporating metapopulation dynamics into models of stream fish populations may improve our ability to understand mechanisms regulating them. First, we reviewed empirical research on metapopulation dynamics in the stream fish ecology literature and found 31 papers that used the metapopulation framework. The majority of papers applied no specific metapopulation model, or included space only implicitly. Although parameterization of spatially realistic models is challenging, we suggest that stream fish ecologists should incorporate space into models and recognize that metapopulation types may change across scales. Second, we considered metacommunity theory, which addresses how trade-offs among dispersal, environmental heterogeneity, and biotic interactions structure communities across spatial scales. There are no explicit tests of metacommunity theory using stream fishes to date, so we used data from our research in a Great Plains stream to test the utility of these paradigms. We found that this plains fish metacommunity was structured mainly by spatial factors related to dispersal opportunity and, to a lesser extent, by environmental heterogeneity. Currently, metacommunity models are more heuristic than predictive. Therefore, we propose that future stream fish metacommunity research should focus on developing testable hypotheses that incorporate stream fish life history attributes, and seasonal environmental variability, across spatial scales. This emerging body of research is likely to be valuable not only for basic stream fish ecological research, but also multispecies conservation and management.

scholarly journals Adaptive Multiscale Symbolic-Dynamics Entropy for Condition Monitoring of Rotating Machinery

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1138
Author(s):  
Chunhong Dou ◽  
Jinshan Lin
Keyword(s):  
Symbolic Dynamics ◽  
Spatial Scales ◽  
Approximate Entropy ◽  
Rotating Machinery ◽  
Temporal Scale ◽  
Permutation Entropy ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Vibration Data ◽  
Temporal Statistics

Vibration data from rotating machinery working in different conditions display different properties in spatial and temporal scales. As a result, insights into spatial- and temporal-scale structures of vibration data of rotating machinery are fundamental for describing running conditions of rotating machinery. However, common temporal statistics and typical nonlinear measures have difficulties in describing spatial and temporal scales of data. Recently, statistical linguistic analysis (SLA) has been pioneered in analyzing complex vibration data from rotating machinery. Nonetheless, SLA can examine data in spatial scales but not in temporal scales. To improve SLA, this paper develops symbolic-dynamics entropy for quantifying word-frequency series obtained by SLA. By introducing multiscale analysis to SLA, this paper proposes adaptive multiscale symbolic-dynamics entropy (AMSDE). By AMSDE, spatial and temporal properties of data can be characterized by a set of symbolic-dynamics entropy, each of which corresponds to a specific temporal scale. Afterward, AMSDE is employed to deal with vibration data from defective gears and rolling bearings. Moreover, the performance of AMSDE is benchmarked against five common temporal statistics (mean, standard deviation, root mean square, skewness and kurtosis) and three typical nonlinear measures (approximate entropy, sample entropy and permutation entropy). The results suggest that AMSDE performs better than these benchmark methods in characterizing running conditions of rotating machinery.

scholarly journals Variable Urbanization Warming Effects across Metropolitans of China and Relevant Driving Factors

2020 ◽  
Vol 12 (9) ◽  
pp. 1500 ◽  
Author(s):  
Qiang Zhang ◽  
Zixuan Wu ◽  
Huiqian Yu ◽  
Xiudi Zhu ◽  
Zexi Shen
Keyword(s):  
Remote Sensing ◽  
Spatial Scales ◽  
River Delta ◽  
Driving Factors ◽  
Landsat 8 ◽  
Temporal Scales ◽  
Linear Relations ◽  
Urban Agglomerations ◽  
Spatial And Temporal Scales ◽  
Urbanized Region

Urbanization is mainly characterized by the expansion of impervious surface (IS) and hence modifies hydrothermal properties of the urbanized areas. This process results in rising land surface temperature (LST) of the urbanized regions, i.e., urban heat island (UHI). Previous studies mainly focused on relations between LST and IS over individual city. However, because of the spatial heterogeneity of UHI from individual cities to urban agglomerations and the influence of relevant differences in climate background across urban agglomerations, the spatial-temporal scale independence of the IS-LST relationship still needs further investigation. In this case, based on Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat 8 OLI/TIRS) remote sensing image and multi-source remote sensing data, we extracted IS using VrNIR-BI (Visible red and NIR-based built-up Index) and calculated IS density across three major urban agglomerations across eastern China, i.e., the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) to investigate the IS-LST relations on different spatial and temporal scales and clarify the driving factors of LST. We find varying warming effects of IS on LST in diurnal and seasonal sense at different time scales. Specifically, the IS has stronger impacts on increase of LST during daytime than during nighttime and stronger impacts on increase of LST during summer than during winter. On different spatial scales, more significant enhancing effects of IS on LST can be observed across individual city than urban agglomerations. The Pearson correlation coefficient (r) between IS and LST at the individual urbanized region can be as high as 0.94, indicating that IS can well reflect LST changes within individual urbanized region. However, relationships between IS and LST indicate nonlinear effects of IS on LST. Because of differences in spatial scales, latitudes, and local climates, we depicted piecewise linear relations between IS and LST across BTH when the IS density was above 10% to 17%. Meanwhile, linear relations still stand between IS density and LST across YRD and PRD. Besides, the differences in the IS-LST relations across urban agglomeration indicate more significant enhancing effects of IS on LST across PRD than YRD and BTH. These findings help to enhance human understanding of the warming effects of urbanization or UHI at different spatial and temporal scales and is of scientific and practical merits for scientific urban planning.

Measuring temporal and spatial scales of compound events in the United Kingdom

2020 ◽  
Author(s):  
Aloïs Tilloy ◽  
Bruce Malamud ◽  
Hugo Winter ◽  
Amelie Joly-Laugel
Keyword(s):  
Natural Hazards ◽  
Clustering Algorithm ◽  
Spatial Scales ◽  
Wind Gust ◽  
Temporal Scales ◽  
Spatial And Temporal Scales ◽  
Extreme Wind ◽  
Compound Events ◽  
Temporal And Spatial ◽  
The Impact

&lt;p&gt;Multi-hazard events have the potential to cause damages to infrastructures and people that may differ greatly from the associated risks posed by singular hazards. Interrelations between natural hazards also operate on different spatial and temporal scales than single natural hazards. Therefore, the measure of spatial and temporal scales of natural hazard interrelations still remain challenging. The objective of this study is to refine and measure temporal and spatial scales of natural hazards and their interrelations by using a spatiotemporal clustering technique. To do so, spatiotemporal information about natural hazards are extracted from the ERA5 climate reanalysis. We focus here on the interrelation between two natural hazards (extreme precipitation and extreme wind gust) during the period 1969-2019 within a region including Great Britain and North-West France. The characteristics of our input data (i.e. important size, high noise level) and the absence of assumption about the shape of our hazard clusters guided the choice of a clustering algorithm toward the DBSCAN clustering algorithm. To create hazard clusters, we retain only extreme values (above the 99% quantile) of precipitation and wind gust. We analyse the characteristics (eg., size, duration, season, intensity) of single and compound events of rain and wind impacting our study area. We then measure the impact of the spatial and temporal scales defined in this study on the nature of the interrelation between extreme rainfall and extreme wind in the UK. We therefore demonstrate how this methodology can be applied to a different set of natural hazards.&lt;/p&gt;

The Temporal and Spatial Scales of Global Climate Change and the Limits of Individualistic and Rationalistic Ethics

2011 ◽  
Vol 69 ◽  
pp. 101-116 ◽  
Author(s):  
J. Baird Callicott
Keyword(s):  
Climate Change ◽  
Environmental Ethics ◽  
Moral Philosophy ◽  
Global Climate Change ◽  
Global Climate ◽  
Spatial Scales ◽  
Environmental Ethic ◽  
Original Position ◽  
Temporal Scales ◽  
Temporal And Spatial

Here I argue that the hyper-individualistic and rationalistic ethical paradigms – originating in the late eighteenth century and dominating moral philosophy, in various permutations, ever since – cannot capture the moral concerns evoked by the prospect of global climate change. Those paradigms are undone by the temporal and spatial scales of climate change. To press my argument, I deploy two famous philosophical tropes – John Rawls's notion of the original position and Derek Parfit's paradox – and another that promises to become famous: Dale Jamieson's six little ditties about Jack and Jill. I then go on to argue that the spatial and especially the temporal scales of global climate change demand a shift in moral philosophy from a hyper-individualistic ontology to a thoroughly holistic ontology. It also demands a shift from a reason-based to a sentiment-based moral psychology. Holism in environmental ethics is usually coupled with non-anthropocentrism in theories constructed to provide moral considerability for transorganismic entities – such as species, biotic communities, and ecosystems. The spatial and temporal scales of climate, however, render non-anthropocentric environmental ethics otiose, as I more fully explain. Thus the environmental ethic here proposed to meet the moral challenge of global climate change is holistic but anthropocentric. I start with Jamieson's six little ditties about Jack and Jill.

scholarly journals Social tipping processes for sustainability: An analytical framework

2021 ◽  
Author(s):  
Ricarda Winkelmann ◽  
Jonathan F. Donges ◽  
E. Keith Smith ◽  
Manjana Milkoreit ◽  
Christina Eder ◽  
...  
Keyword(s):  
Climate Change ◽  
Analytical Framework ◽  
Expert Elicitation ◽  
Social Transformations ◽  
Distinctive Features ◽  
Spatial And Temporal Scales ◽  
Development Goals ◽  
Small Change ◽  
Institutional Network

&lt;p&gt;Societal transformations are necessary to address critical global challenges, such as mitigation of anthropogenic climate change and reaching UN sustainable development goals. Recently, social tipping processes have received increased attention, as they present a form of social change whereby a small change can shift a sensitive social system into a qualitatively different state due to strongly self-amplifying (mathematically positive) feedback mechanisms. Social tipping processes have been suggested as key drivers of sustainability transitions emerging in the fields of technological and energy systems, political mobilization, financial markets and sociocultural norms and behaviors.&lt;/p&gt;&lt;p&gt;Drawing from expert elicitation and comprehensive literature review, we develop a framework to identify and characterize social tipping processes critical to facilitating rapid social transformations. We find that social tipping processes are distinguishable from those of already more widely studied climate and ecological tipping dynamics. In particular, we identify human agency, social-institutional network structures, different spatial and temporal scales and increased complexity as key distinctive features underlying social tipping processes. Building on these characteristics, we propose a formal definition for social tipping processes and filtering criteria for those processes that could be decisive for future trajectories to global sustainability in the Anthropocene. We illustrate this definition with the European political system as an example of potential social tipping processes, highlighting the potential role of the FridaysForFuture movement. Accordingly, this analytical framework for social tipping processes can be utilized to illuminate mechanisms for necessary transformative climate change mitigation policies and actions.&amp;#160;&lt;/p&gt;

scholarly journals Using iNaturalist observations to detect disease in Red Mangroves (Rhizophora mangle)

2017 ◽  
Author(s):  
Ryann E Rossi
Keyword(s):  
Citizen Science ◽  
Passive Sampling ◽  
Spatial Scales ◽  
Disease Detection ◽  
Temporal Scales ◽  
Disease Symptoms ◽  
Foliar Disease ◽  
Spatial And Temporal Scales ◽  
Red Mangrove ◽  
Disease Surveys

Detection of disease over broad spatial scales is important to managing the spread of many diseases. One way to do this is to work with citizen scientists to collect data over broad spatial and temporal scales. Citizen science observations are becoming more widely available through web and app interfaces such as iNaturalist.org. iNaturalist.org provides passive sampling of organisms through photographs with a geolocation. These observations are often used to examine biodiversity and species monitoring, but, disease detection is also possible. Here, I demonstrate the utility of using iNaturlist.org observations of red mangrove to detect foliar disease symptoms such as lesions. I downloaded observations of red mangrove from iNaturalist.org, filtered them and examined images for foliar disease symptoms. Out of 153 filtered images, I found that 42% showed no signs of foliar disease while 58% did show foliar disease symptoms. I also found that observations of red mangrove were recorded from 15 countries in total, with 11 countries having at least one observation with foliar disease symptoms present. While small, this study demonstrates the utility of using resources such as iNaturalist.org to obtain preliminary disease observations which can be used to further focus in person disease surveys and sampling.

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