DOI: 10.5061/dryad.8pk0p2nsn
title: A species distribution model of the giant kelp Macrocystis pyrifera: Worldwide changes and a focus on the Southeast Pacific

description: Worldwide climate-driven shifts in the distribution of species is of
 special concern when it involves habitat-forming species. In the coastal
 environment, large Laminarian algae—kelps—form key coastal ecosystems that
   support complex and   diverse food webs. 
 Among kelps, Macrocystis pyrifera is the most widely distributed
 habitat-formingspecies and provides essential ecosystem services. This
 study aimed to establish the main drivers of  future
 distributional changes on a global scale and use them to predict future
 habitat suitability. Using species distribution models (SDM), we examined
 the changes in  global distribution of M. pyrifera under
  different emission scenarios with a focus on the Southeast
 Pacific shores. To constrain the drivers of our simulations to the most
 important factors controlling kelp forest distribution across spatial
 scales, we explored a suite of environmental variables and validated the
 predictions derived from the SDMs. Minimum sea surface temperature was the
 single most important variable explaining the global distribution of
 suitable habitat for M. pyrifera. Under different climate change
 scenarios, we always observed a decrease of suitable habitat at low
 latitudes, while an increase was detected in other regions, mostly at high
 latitudes. Along the Southeast Pacific, we observed an upper range
 contraction of −17.08° S of  latitude for   2090–2100
 under the RCP8.5 scenario, implying a loss of habitat suitability
 throughout the coast of Peru and poleward to −27.83° S in Chile. Along the
 area of  Northern Chile    where  
   a complete habitat loss is  predicted by our model,
 natural stands are under heavy exploitation. The loss of habitat
 suitability will take place worldwide: Significant impacts on marine
 biodiversity and ecosystem functioning are likely. Furthermore, changes in
 habitat suitability are a harbinger of massive impacts in the
 socio-ecological systems of the Southeast Pacific.
description: This dataset contains what is needed to perform the distribution model of
 *Macrocystis pyrifera* with Maxent as described in the methods section of
 the published article (DOI: 10.1002/ece3.10901). The dataset included: 
 1\) Global occurrences of *M. pyrifera* (.csv) extracted from GBIF
 (www.gbif.org) and following the pretreatment procedures outlined in the
 methods section. 2\) Global coastline mask to delimit the study area and
 used to cut all the layers of environmental predictors (.shp). Extracted
 from www.naturalearthdata.com. 3\) Environmental predictor (.asc; SST =
 Sea Surface Temperature). They were extracted from BioOracle. For more
 information on the environmental variables and their origin visit
 www.bio-oracle.org.  * Present model: SST_min (ºC), SST_max (ºC), SST_mean
 (ºC), Salinity, Nitrate (mmol . m-3), Phosphate (mmol . m-3), Calcite
 (mmol . m-3), and Silicate (mmol . m-3).  * Model for 2.6 2090-2100
 scenario: SST_min_2.6 (ºC), SST_max_2.6 (ºC), SST_mean_2.6 (ºC),
 Salinity_2.6. * Model for 8.5 2090-2100 scenario: SST_min_8.5 (ºC),
 SST_max_8.5 (ºC), SST_mean_8.5 (ºC), Salinity_8.5 . These files are
 compatible with any geographic information software, such as QGIS or
 ArcGIS. For the present study, they were specifically utilized in Maxent
 software
 ([https://biodiversityinformatics.amnh.org/open_source/maxent/)](https://biodiversityinformatics.amnh.org/open_source/maxent/\)) to model the distribution of *M. pyrifera*.