A global analysis of how human infrastructure squeezes sandy coasts - Scripts & Data

Abstract

Coastal ecosystems provide vital services, but human disturbance causes massive losses. Remaining ecosystems are squeezed between rising seas and human infrastructure development. While shoreline retreat is intensively studied, coastal congestion through infrastructure remains unquantified. Here we analyse 235,469 transects worldwide to show that infrastructure occurs at a median distance of 392 meter from sandy shorelines. Moreover, we find that 33% of sandy shores harbour less than 100m of infrastructure-free space, and that 23–30% of this space may be lost by 2100 due to rising sea levels. Further analyses show that population density and gross domestic product explain 35–39% of observed squeeze variation, emphasizing the intensifying pressure imposed as countries develop and populations grow. Encouragingly, we find that nature reserves relieve squeezing by 4–7 times. Yet, at presentonly 16%of world’s sandy shores have a protected status. We therefore advocate the incorporation of nature protection into spatial planning policies.

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Methods

The analyses rely on the following freely available datasets:

OpenStreetMap - streets: https://www.openstreetmap.org/#map=7/52.154/5.295 

OpenStreetMap - shoreline: https://osmdata.openstreetmap.de/data/land-polygons.html

Global Urban Footprint: https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-9628/16557_read-40454/

World population: https://data.humdata.org/dataset/worldpop-population-counts-for-world/resource/677d30ab-896e-44e5-9a31-05452bc3124b

GDP per capita: https://data.worldbank.org/indicator/NY.GDP.PCAP.CD

Protected areas: https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA

Projected shoreline change: https://data.jrc.ec.europa.eu/dataset/18eb5f19-b916-454f-b2f5-88881931587e

CoastalDEM: https://www.climatecentral.org/coastaldem-v2.1

In addition, we requested the sandy shoreline data from:

Luijendijk et al. (2018) "The State of the World's Beaches", Scientific Reports 8: 6641; https://www.nature.com/articles/s41598-018-24630-6

The deposited folder contains 4 subfolders based on the separate analyses presented in the paper. In each subfolder you find a Matlab script to run and accompanying datasets to load. A readme file is included, which further explains the scripts and datasets.

Source data file

In the data file Source_Data.xlsx, each sheet contains the data for one figure or table of the manuscript.