DOI: 10.5061/dryad.905qfttm5
title: A song of wind and ice: increased frequency of marine cold-spells in southwestern Patagonia and their possible effects on giant kelp forests

description: In contrast to other coastal regions of the world, the giant kelp
 (Macrocystis pyrifera)  ecosystem in southwestern Patagonia has
 been persistent in area and associated biodiversity in the last decades.
 In this ecoregion, Sea Surface Temperature (SST) records have consistently
 remained below the upper thermal threshold for kelp survival, however no
 studies have analysed the spatiotemporal variability of SSTs and their
 anomalies across the geographical diversity of the southwestern Patagonian
 coastline. We explored the geographical distribution of extreme warm and
 cold events in this region from latitudes 47° to 56° S in a range
 of 1,000 km, identifying the dates and spatial distribution of
 Marine Heatwaves (MHWs) and Marine Cold-Spells (MCSs) from 1982 to 2020.
 Results show that a peak in the number of MHWs occurred in the great El
 Nino year of 1998. Additionally, the 2014-2019 period has had more severe
 and extreme MCSs than the previous decades. We discuss the origin of these
 events with a focus on three main processes: 1) geographically constrained
 cold events caused by glacier melting, 2) regional cold events caused by
 extreme winds linked to the position of the polar front, and 3) extensive
 SST anomalies linked to planetary-scale events such as El Nino and La
 Nina.  Overall, those processes were conductive to counteract
 global warming trends locally/regionally, highlighting southwestern
 Patagonia as a possible climatic refugium for the giant kelp ecosystem.
 Despite this, the effects of freshwater inputs and storm turbulence on the
 exposed coasts facing the Southern Ocean may cause new kinds of stress on
 this ecosystem.
description: This dataset comprises a list
 of MCS and MCS per marine ecosystem in Southwestern Patagonia, derived
 from daily SST measurements. The list includes events categories II, III
 and IV.  The original daily SST measurements were
 extracted from the NOAA CDR OISST v02r01: Optimum
 Interpolation Sea Surface
 Temperature product (Reynolds et al., 2008; Gorelick et al., 2017). This
 dataset was selected
 per marine ecosystem through zonal statistics,
 with a spatial resolution of 0.25 arc degrees, using
 a Google Earth Engine script.  
 Computations of MHWs and MCSs,
 as well as their categories of intensity according to Hobday et al. (2018), were calculated
 using the ‘heatwaveR’ package in R (Schlegel & Smit, 2018; RCore Team et al., 2021).
 We selected categories II (strong), III (severe), and IV
 (extreme) for our analysis (Hobday et al., 2018; Schlegel et al., 2017). We discarded the use of
 category I (moderate) events because they are generally common (Hobday et al.,
 2018).  The nomenclature of each dataset
 is as follows: BH1= Beagle Ballenero, BH2= Nassau Hornos, C1= Inner
 Channels Kaweskar, CE1= Gulf of Penas, CE2= Offshore Kaweskar, CE3=
 Offshore Magallanes, E1= Eastern Strait, E2= Central Strait, E3 = Bahia
 Inutil Strait, E4= Western Strait. 
description: Files in this
 dataset: <br> 
 Table S1
 (SM_MHW_MCS_March2022.xlsx): List of MCSs (Categories II, III
 and IV); list of MHWs (Categories II, III and IV); Combined list of MCSs
 and MHWs, Categories III and IV. 
 MCS per ecoregion; the
 complete series is in MCS_category_March2022.csv
 MHW  per
 ecoregion; the complete series is in MHW_category_March2022.csv
 SST per ecoregion.  We found a gap of data between 31-Dec-1984 to 01-Sep-1985, and 31-Dec-2020, not included in the analysis. The original shapefile with the marine ecosystems used in this study is from Rovira, J., & Herreros, J.    (2016).    Clasificacion de ecosistemas marinos chilenos de la zona economica exclusiva [Report]. Departamento de Planificacion y Polıticas en Biodiversidad. Division de Recursos Naturales y Biodiversidad. Ministerio del Medio Ambiente. The MHW and MCS method has been developed by: Robert W. Schlegel and Albertus J. Smit (2018). heatwaveR: A central algorithm for the detection of heatwaves and cold-spells. Journal of Open Source Software, 3(27), 821, https://doi.org/10.21105/joss.00821. The heatwaveR package used in this study is explained here: https://robwschlegel.github.io/heatwaveR/index.html