Last updated: 2021-10-03

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Anthropogenic impacts in Isfjorden

  • What can we currently say about local anthropogenic effects on Isfjorden?
    • With a specific focus on social science data
  • Keep in mind this analysis is just an example to stimulate thought about real analyses
    • These then are to be used for the review paper

Isfjorden data

Figure 1: High level overview of the data available for Isfjorden. The acronyms for the variable groups seen throughout the figure are: bio = biology, chem = chemistry, cryo = cryosphere, phys = physical, soc = social (currently there are no social data for Isfjorden). A) Metadata showing the range of values available within the data. B) Spatial summary of data available per ~1 km grouping. Note that there are some important moorings outside of this bounding box that are included in the data counts. C) Temporal summary of available data. D) Summmary of data available by depth. Note that all of the data summaries are log10 transformed. For C) and D) the log10 transformation is applied before the data are stacked by category, which gives the impression that there are much more data are than there are."


Human presence in Svalbard

Pop

Tourists

Nights

Nutrients

ChlA

Vader et al. (In prep)

ChlA vs. Pop

Cryosphere data

Shifts in phenology

Population vs. nutrients

  • For the analysis:
    • Get the number of inhabitants of Longyearbyen over time and relate that to nutrient concentration
    • Also want to look at relationships with ice cover and any sort of physical phenology


Summary

  • The aggregated data products showcased in this talk are intended to be used by other FACE-IT members for their research as well as to be used for a review of change in the FACE-IT study sites
  • The review paper is designed to be a collaborative process for many members of FACE-IT
    • Co-authorship requires contribution of data, text, figures, ideas etc.
    • Site coordinators will be contacted first
  • Timeline:
    • Data collection (underway)
    • Analyses (April, 2022)
    • Writing up (September, 2022)
    • Manuscript submitted for review (October, 2022)

R version 4.1.1 (2021-08-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_CA.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=en_CA.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=en_CA.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.7       whisker_0.4      knitr_1.34       magrittr_2.0.1  
 [5] workflowr_1.6.2  R6_2.5.1         rlang_0.4.11     fastmap_1.1.0   
 [9] fansi_0.5.0      stringr_1.4.0    tools_4.1.1      xfun_0.26       
[13] utf8_1.2.2       git2r_0.28.0     jquerylib_0.1.4  htmltools_0.5.2 
[17] ellipsis_0.3.2   rprojroot_2.0.2  yaml_2.2.1       digest_0.6.28   
[21] tibble_3.1.4     lifecycle_1.0.0  crayon_1.4.1     later_1.3.0     
[25] sass_0.4.0       vctrs_0.3.8      promises_1.2.0.1 fs_1.5.0        
[29] glue_1.4.2       evaluate_0.14    rmarkdown_2.11   stringi_1.7.4   
[33] bslib_0.3.0      compiler_4.1.1   pillar_1.6.2     jsonlite_1.7.2  
[37] httpuv_1.6.3     pkgconfig_2.0.3