Connecting Community and Citizen Science to Stewardship Action Planning Through Scenarios Storytelling

Community and citizen science on climate change-influenced topics offers a way for participants to actively engage in understanding the changes and documenting the impacts. As in broader climate change education, a focus on the negative impacts can often leave participants feeling a sense of powerlessness. In large scale projects where participation is primarily limited to data collection, it is often difficult for volunteers to see how the data can inform decision making that can help create a positive future. In this paper, we propose and test a method of linking community and citizen science engagement to thinking about and planning for the future through scenarios story development using the data collected by the volunteers. We used a youth focused wild berry monitoring program that spanned urban and rural Alaska to test this method across diverse age levels and learning settings. Using qualitative analysis of educator interviews and youth work samples, we found that using a scenario stories development mini-workshop allowed the youth to use their own data and the data from other sites to imagine the future and possible actions to sustain berry resources for their communities. This process allowed youth to exercise key cognitive skills for sustainability, including systems thinking, futures thinking, and strategic thinking. The analysis suggested that youth would benefit from further practicing the skill of envisioning oneself as an agent of change in the environment. Educators valued working with lead scientists on the project and the experience for youth to participate in the interdisciplinary program. They also identified the combination of the berry data collection, analysis and scenarios stories activities as a teaching practice that allowed the youth to situate their citizen science participation in a personal, local and cultural context. The majority of the youth groups pursued some level of stewardship action following the activity. The most common actions included collecting additional years of berry data, communicating results to a broader community, and joining other community and citizen science projects. A few groups actually pursued solutions illustrated in the scenario stories. The pairing of community and citizen science with scenario stories development provides a promising method to connect data to action for a sustainable and resilient future.

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Intensification of future low-flow events in relation to projected changes in large-scale climate drivers due to climate change

10.5194/egusphere-egu21-15366 ◽

2021 ◽

Author(s):

Pallavi Goswami ◽

Arpita Mondal ◽

Christoph Rüdiger ◽

Tim J. Peterson

Keyword(s):

Climate Change ◽

Large Scale ◽

Linear Models ◽

Southern Oscillation ◽

Value Theory ◽

Extreme Value ◽

Low Flow ◽

Generalised Linear Models ◽

Southeast Australia ◽

The Future

Large-scale climate processes such as the El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Southern Annular Mode (SAM) influence the hydro-climatology of Southeast Australia (SEA). In the present study, we show that low-flow events in many catchments in SEA are significantly influenced by variability in these climate drivers. Extreme value distributions and Generalised Linear Models (GLMs) are used here to model low-flow characteristics such as intensity, duration and frequency with respect to these climate drivers. Further, we study how the future projections of ENSO, IOD and SAM are likely to evolve under climate change by examining the projected values of their representative indices and how they will impact low-flow events in the region. It is found that the future dry phases of these climate drivers are likely to be more dry than those in the historic period. This in turn is expected to lead to intensification of low-flow events in the future, resulting in lower availability of fresh water during occurrences of the dry phases of these climate drivers. Thus, climate change in the future is expected to significantly influence future low-flow events in the region thereby making it even more crucial for water managers to adequately manage and ensure water availability. Keywords: low-flows, ENSO, IOD, SAM, Extreme Value Theory, Generalised Linear Models, Southeast Australia, CMIP5, RCP8.5.

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Design of Microplastics Citizen Science Kit

10.5194/egusphere-egu2020-9176 ◽

2020 ◽

Author(s):

Rachael Hughson-Gill

Keyword(s):

Data Collection ◽

Citizen Science ◽

Large Scale ◽

Positive Impact ◽

Research Process ◽

Freshwater Ecosystems ◽

Freshwater Systems ◽

The Public ◽

Plastic Bags ◽

The Impact

Microplastics are an ever-increasing problem. Every river that was tested in a recent study found the presence of microplastics, with 80% of all plastic in the ocean coming from upstream. Despite this, there is little understanding into the abundance of plastic, its characteristics and the full impact that is it having on marine, freshwater ecosystems and wider ecological systems.&#160;Current fresh water monitoring does not consider the fluid dynamics of rivers, is difficult to use and is inaccessible to the wider public. My project will focus on creating a product that allows for the large-scale data collection of microplastic through citizen science. Allowing groups of people to analyse their local natural environment for the presence and abundance of microplastics within the water. This method of data collection could provide information on a scale that is not possible with traditional methods and would allow for the comparison between freshwater systems. This comparison is fundamental to begin to fill the knowledge gaps around the understanding of microplastics.&#160;Inaccessibility of monitoring to the public is not just through tools but also through the current communication of data with research rarely breaking into the public domain. Citizen science offers not just an improvement in understanding but also offers an opportunity for engagement with the public body. Increasing awareness of the impact of habits round plastic through the sharing of monitoring data can generate the much-needed change on both an individual and policy level to address the problem from the source. This method of change through public opinion can be seen to have an effect on freshwater systems through microbeads ban, plastic bags, plastic straws and industrial pollution regulation.&#160;Through the creation of this product a multidisciplinary approach that blends engineering and design practices is implemented. The wholistic approach to creation is something that is fundamental in the success of tools and therefore the success of the research that is implemented through them. A tool such as this whose function is within the public engagement of its use - increased awareness, as well as the outcome of its use - microplastics data, is required to have an engaging user experience as well as data integrity implemented through engineering design.&#160;This project offers an opportunity to show the importance of the design process within research tools to aid the research process and the positive impact that can come from it.

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Estimating disease vector population size from citizen science data

Journal of The Royal Society Interface ◽

10.1098/rsif.2021.0610 ◽

2021 ◽

Vol 18 (184) ◽

Author(s):

Tam Tran ◽

W. Tanner Porter ◽

Daniel J. Salkeld ◽

Melissa A. Prusinski ◽

Shane T. Jensen ◽

...

Keyword(s):

Data Collection ◽

Citizen Science ◽

Large Scale ◽

Species Abundance ◽

Natural World ◽

Tick Population ◽

Science Data ◽

Tick Abundance ◽

Vector Population ◽

Public Datasets

Citizen science projects have the potential to address hypotheses requiring extremely large datasets that cannot be collected with the financial and labour constraints of most scientific projects. Data collection by the general public could expand the scope of scientific enquiry if these data accurately capture the system under study. However, data collection inconsistencies by the untrained public may result in biased datasets that do not accurately represent the natural world. In this paper, we harness the availability of scientific and public datasets of the Lyme disease tick vector to identify and account for biases in citizen science tick collections. Estimates of tick abundance from the citizen science dataset correspond moderately with estimates from direct surveillance but exhibit consistent biases. These biases can be mitigated by including factors that may impact collector participation or effort in statistical models, which, in turn, result in more accurate estimates of tick population sizes. Accounting for collection biases within large-scale, public participation datasets could update species abundance maps and facilitate using the wealth of citizen science data to answer scientific questions at scales that are not feasible with traditional datasets.

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MODELLING LONG TERM IMPLICATION OF CLIMATE CHANGE PROJECTION ON SHORE MORPHOLOGY OF NORTH NORFOLK, UK, COMBINING TOMAWAC AND SCAPE

Coastal Engineering Proceedings ◽

10.9753/icce.v32.sediment.61 ◽

2011 ◽

Vol 1 (32) ◽

pp. 61 ◽

Cited By ~ 2

Author(s):

Nicolas Chini ◽

Peter Stansby ◽

Mike Walkden ◽

Jim Hall ◽

Judith Wolf ◽

...

Keyword(s):

Climate Change ◽

Global Climate Change ◽

Large Scale ◽

Numerical Models ◽

Global Climate ◽

Stationary Processes ◽

Climate Change Projections ◽

Future Evolution ◽

The Future

Assessment of nearshore response to climatic change is an important issue for coastal management. To predict potential effects of climate change, a framework of numerical models has been implemented which enables the downscaling of global projections to an eroding coastline, based on TOMAWAC for inshore wave propagation input into SCAPE for shoreline modelling. With this framework, components of which have already been calibrated and validated, a set of consistent global climate change projections is used to estimate the future evolution of an un-engineered coastline. The response of the shoreline is sensitive to the future scenarios, underlying the need for long term large scale offshore conditions to be included in the prediction of non-stationary processes.

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Storylines of plausible past and future climates for the July 2019 European heatwave

10.5194/egusphere-egu21-14302 ◽

2021 ◽

Author(s):

Antonio Sánchez Benítez ◽

Thomas Jung ◽

Helge Goessling ◽

Felix Pithan ◽

Tido Semmler

Keyword(s):

Climate Change ◽

Global Warming ◽

Large Scale ◽

Western Europe ◽

Bowen Ratio ◽

Warming Trend ◽

Ocean Model ◽

Temperature Record ◽

Adaptation To Climate Change ◽

The Future

Under the current global warming trend, heatwaves are becoming more intense, frequent, and longer-lasting; and this trend will continue in the future. In this context, the recent 2019 summer was exceptionally hot in large areas of the Northern Hemisphere, with embedded heatwaves, as for example the June and July 2019 European events, redrawing the temperature record map in western Europe. Large-scale dynamics (associated with blockings or subtropical ridges) play a key role in explaining these-large scale events.Conceptually, global warming can be split into two different contributions: Dynamic and thermodynamic changes. Whereas dynamic changes remain highly uncertain, some thermodynamic changes can be quantified with higher confidence. We exploit this concept by studying how these recent European heatwaves would have developed in a pre-industrial climate and how it would develop in the future for 1.5, 2 and 4 &#186;C warmer climates (storyline scenarios). To do so, we employ the spectral nudging technique with AWI-CM (CMIP6 model, a combination of ECHAM6 AGCM + FESOM Sea Ice-Ocean Model). Large-scale dynamics are prescribed by reanalysis data (ERA5). Meanwhile, the model is run for different boundary conditions corresponding to preindustrial and future climates along the SSP370 forcing scenario. This approach can be useful to help understand and communicate what climate change will mean to people&#8217;s life and hence facilitate effective decision-making regarding adaptation to climate change, as we are quantifying how recent outstanding events would be modified by our climate action.&#160;Temperatures during the heatwaves often increase twice as much as global mean temperatures, especially in a future 4 &#186;C warmer climate. In this future climate, maximum temperatures can locally reach 50&#186;C in many western Europe countries. Nighttime temperatures would be similar to the daytime temperatures in a preindustrial world. The global warming amplification can be partly explained by a robust soil drying in the future 4 &#186;C warmer climate (exacerbated due to the June 2019 heatwave) which is transmitted to a robust increase in Bowen ratio. Importantly, by design of our study, this response occurs without any changes in atmospheric circulation.

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Reconstructing the Roman Climate

The Science of Roman History ◽

10.23943/princeton/9780691195988.003.0002 ◽

2019 ◽

pp. 11-52

Author(s):

Kyle Harper ◽

Michael McCormick

Keyword(s):

Climate Change ◽

Large Scale ◽

Historical Change ◽

Proxy Data ◽

Current State ◽

The Future ◽

Paleoclimate Proxy ◽

New Evidence ◽

The Relationship

This chapter frames our current state of knowledge about the physical climate in the period of the Roman Empire's expansion, flourishing, and final fragmentation, at roughly 200 BCE to 600 CE. The emphasis here is on the new evidence of paleoclimate proxy data. The chapter explores what it is starting to tell historians about the timing and nature of large-scale climate change in the centuries of interest. To conclude, the chapter draws together the disparate sources of evidence into a tentative narrative. It highlights the questions that can be asked about the relationship between climate change and historical change and underscores the need for more and better data to fill in such a narrative in the future.

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Climate Change of Tibetan Plateau and its Impact on Water Resources of the Source Region of Yangtze River and Yellow River in the next 30~50 Years

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.171-172.547 ◽

2010 ◽

Vol 171-172 ◽

pp. 547-550

Author(s):

Zhi Gang Cheng ◽

Guang Zhou Fan

Keyword(s):

Climate Change ◽

Tibetan Plateau ◽

Yangtze River ◽

Large Scale ◽

Yellow River ◽

Source Region ◽

Annual Runoff ◽

Climate Data ◽

Average Annual Runoff ◽

The Future

Based on high resolution dynamic downscaling meteorological forcing data, climate change of Tibetan Plateau and possible trends in runoff of the source region of Yangtze River and Yellow River were analyzed by using large-scale distributed hydrology model under future climate warming. The average annual runoff of the source region of Yangtze River and Yellow River will increase by 8.58% and 9.19% in the future 30 to 50 years. Although the annual precipitation will increase up to 4.48%, the average annual runoff of the source of Yellow River will reduce only by 1.98% in the next 30 to 50 years. The variations of runoff in the source area of Yangtze River and Yellow River are analyzed by using the climate data projected for the future 30 to 50 years and the scenario simulations of the land use/cover change. These results indicate that the runoff is the minimum (maximum) at forest land (bare land).

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Deep learning identification for citizen science surveillance of tiger mosquitoes

Scientific Reports ◽

10.1038/s41598-021-83657-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Balint Armin Pataki ◽

Joan Garriga ◽

Roger Eritja ◽

John R. B. Palmer ◽

Frederic Bartumeus ◽

...

Keyword(s):

Deep Learning ◽

Data Collection ◽

Citizen Science ◽

Large Scale ◽

Mosquito Species ◽

Characteristic Curve ◽

Science System ◽

Public Health Agencies ◽

Manual Inspection ◽

Long Run

AbstractGlobal monitoring of disease vectors is undoubtedly becoming an urgent need as the human population rises and becomes increasingly mobile, international commercial exchanges increase, and climate change expands the habitats of many vector species. Traditional surveillance of mosquitoes, vectors of many diseases, relies on catches, which requires regular manual inspection and reporting, and dedicated personnel, making large-scale monitoring difficult and expensive. New approaches are solving the problem of scalability by relying on smartphones and the Internet to enable novel community-based and digital observatories, where people can upload pictures of mosquitoes whenever they encounter them. An example is the Mosquito Alert citizen science system, which includes a dedicated mobile phone app through which geotagged images are collected. This system provides a viable option for monitoring the spread of various mosquito species across the globe, although it is partly limited by the quality of the citizen scientists’ photos. To make the system useful for public health agencies, and to give feedback to the volunteering citizens, the submitted images are inspected and labeled by entomology experts. Although citizen-based data collection can greatly broaden disease-vector monitoring scales, manual inspection of each image is not an easily scalable option in the long run, and the system could be improved through automation. Based on Mosquito Alert’s curated database of expert-validated mosquito photos, we trained a deep learning model to find tiger mosquitoes (Aedes albopictus), a species that is responsible for spreading chikungunya, dengue, and Zika among other diseases. The highly accurate 0.96 area under the receiver operating characteristic curve score promises not only a helpful pre-selector for the expert validation process but also an automated classifier giving quick feedback to the app participants, which may help to keep them motivated. In the paper, we also explored the possibilities of using the model to improve future data collection quality as a feedback loop.

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Urban Forest Health Monitoring: Large-Scale Assessments in the United States

Arboriculture & Urban Forestry ◽

10.48044/jauf.2008.047 ◽

2008 ◽

Vol 34 (6) ◽

pp. 341-346

Author(s):

Anne Cumming ◽

Daniel Twardus ◽

David Nowak

Keyword(s):

Data Collection ◽

Health Monitoring ◽

Large Scale ◽

Urban Forest ◽

Monitoring Program ◽

Forest Health ◽

The United States ◽

Department Of Agriculture ◽

Pilot Studies ◽

Forest Health Monitoring

The U.S. Department of Agriculture, Forest Service (USFS), together with state partners, developed methods to monitor urban forest structure, function, and health at a large statewide scale. Pilot studies have been established in five states using protocols based on USFS Forest Inventory and Analysis and Forest Health Monitoring program data collection standards. Variables and data analysis are described. Advantages of a large-scale monitoring study are discussed and examples of results from Wisconsin are presented. Studies in Indiana, Wisconsin, New Jersey, Tennessee, and Colorado, U.S., have shown that urban forest health monitoring data collection and analysis is feasible and can be implemented nationally.

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