Climate change: Impacts on outdoor activities in the summer and shoulder seasons

Pröbstl‐Haider, Ulrike; Hödl, Claudia; Ginner, Kathrin; Borgwardt, Florian

doi:10.1016/j.jort.2020.100344

Cited by 50 publications

(30 citation statements)

References 49 publications

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“…Chaparral), or a specific recreational service (e.g. fishing) (Lane et al 2015, Tomczyk et al 2016, Pröbstl-Haider et al 2020, Jaung and Carrasco 2021. Also, within the ecosystem services community, studies have focused on the environmental aspect such as accessibility, forest intactness or naturalness, heritage or touristic sites, and protected areas (Egoh et al 2012).…”

Section: Discussionmentioning

confidence: 99%

Mapping and modeling the impact of climate change on recreational ecosystem services using machine learning and big data

Manley

Egoh

2022

Environ. Res. Lett.

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The use of recreational ecosystem services is highly dependent on the surrounding environmental and climate conditions. Due to this dependency, future recreational opportunities provided by nature are at risk from climate change. To understand how climate change will impact recreation we need to understand current recreational patterns, but traditional data is limited and low resolution. Fortunately, social media data presents an opportunity to overcome those data limitations and machine learning offers a tool to effectively use that big data. We use data from the social media site Flickr as a proxy for recreational visitation and random forest to model the relationships between social, environmental, and climate factors and recreation for the peak season (summer) in California. We then use the model to project how non-urban recreation will change as the climate changes. Our model shows that current patterns are exacerbated in the future under climate change, with currently popular summer recreation areas becoming more suitable and unpopular summer recreation areas becoming less suitable for recreation. Our model results have land management implications as recreation regions that see high visitation consequently experience impacts to surrounding ecosystems, ecosystem services, and infrastructure. This information can be used to include climate change impacts into land management plans to more effectively provide sustainable nature recreation opportunities for current and future generations. Furthermore, our study demonstrates that crowdsourced data and machine learning offer opportunities to better integrate socio-ecological systems into climate impacts research and more holistically understand climate change impacts to human well-being.

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Section: Discussionmentioning

confidence: 99%

Mapping and modeling the impact of climate change on recreational ecosystem services using machine learning and big data

Manley

Egoh

2022

Environ. Res. Lett.

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“…Consequently, the difference between the utilization in normal weather and the plum rain weather is the rough impact on the public bicycle system. Such subjective accounts have been studied by scholars [44,45] through descriptive and inferential statistics for understanding the demographic and socio-economic characteristics of the user. As confirmed by the results of this study, an important issue lies in the selection of the number of cyclists, place semantic, and riding distance as the affected dimensions.…”

Section: Perspectives Selection Of Affected Dimensionsmentioning

confidence: 99%

Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance

Chen

Zhang

Wang

et al. 2021

IJGI

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The effect of the plum rain weather event on cycling trips reflects the climate resilience of the public bicycle system. However, quantitative studies regarding the impact of plum rain on public bicycle users and corresponding spatial heterogeneity have not been paid much attention. This paper explores the spatial pattern of affected levels from the perspective of cyclist number, place semantics and riding distance. Corresponding public bicycle trips in normal weather are predicted by spatial-temporal random forest prediction. GIS neighborhood statistics and clustering algorithms are adapted to analyze and visualize the affected levels using origin-destination data of public bicycle trips and point of interest data of city public facilities. It is proved that there is an obvious spatial difference in affected levels by plum rain from three dimensions. In the dimension of the number of cyclists, the docking stations with different affected levels are distributed across the whole urban area. In the place semantic dimension, the docking stations with high affected levels show a clustered zonal distribution in the city center. In the dimension of cycling distance, the docking stations with high affected levels are mainly distributed in the periphery of the central urban area. The study theoretically expands the impact mechanism of environment and active transport. It is beneficial for the early monitoring, warning and assessment of climate change risks for public bicycle planning and management.

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“…Even if not taking Covid-19 pandemic to the picture, green areas are a very important space for human recreation ( Stigsdotter and Grahn, 2011 ). Use of them may become even more popular due to the climatic changes, leading to prolongation of the warm weather season ( Proebstl-Haider et al., 2021 ), causing people to have more contact with nature and dangers linked to it – like encountering ticks.…”

Section: Alcohol Is Often Consumed In Areas Of Tick Occurrencementioning

confidence: 99%

Similar Trajectories in Current Alcohol Consumption and Tick-Borne Diseases: Only Parallel Changes in Time or Links Between?

Frątczak

Peťko

Śliwowska

et al. 2021

Front. Cell. Infect. Microbiol.

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In a modern world, both tick-borne diseases and alcohol consumption are among major public health threats. In the present opinion article, we pose the question, whether these two health problems: alcohol consumption and tick-borne diseases prevalence can be related. We hypothesize that it is possible due to at least three factors: outdoor places chosen for alcohol consumption, behavioral changes induced by alcohol, and possible stronger attraction of human hosts after alcohol consumption to ticks. Many important clues are coming from social studies about people’s preference of places to consume alcohol and from studies regarding the attraction of people consuming alcohol to mosquitos. These data, however, cannot be directly transferred to the case of alcohol consumption and ticks. Therefore, we suggest that more detailed studies are needed to better understand the possible individual attractiveness of people to ticks and ways alcohol may influence it.

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Climate change: Impacts on outdoor activities in the summer and shoulder seasons

Cited by 50 publications

References 49 publications

Mapping and modeling the impact of climate change on recreational ecosystem services using machine learning and big data

Mapping and modeling the impact of climate change on recreational ecosystem services using machine learning and big data

Understanding Plum Rain’s Effects on Urban Public Bicycle Unavailability Considering Both Place Semantics and Riding Distance

Similar Trajectories in Current Alcohol Consumption and Tick-Borne Diseases: Only Parallel Changes in Time or Links Between?

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