Automated Author Profile

Blum, Michael J.

Current S-Index

63.4

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.3

Average Dataset Index per dataset

Total Datasets

49

Total datasets for this author

Average FAIR Score

64.6%

Average FAIR Score per dataset

Total Citations

3

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Urban rat races: spatial population genomics of brown rats (Rattus norvegicus) compared across multiple cities (Version: 1)

<b>Abstract</b><br/>Urbanization often substantially influences animal movement and gene flow. However, few studies to date have examined gene flow of the same species across multiple cities. In this study, we examine brown rats (Rattus norvegicus) to test hypotheses about the repeatability of neutral evolution across four cities: Salvador, Brazil; New Orleans, USA; Vancouver, Canada; New York City, USA. At least 150 rats were sampled from each city and genotyped for a minimum of 15,000 genome-wide SNPs. Levels of genome-wide diversity were similar across cities, but varied across neighborhoods within cities. All four populations exhibited high spatial autocorrelation at the shortest distance classes (< 500 m) due to limited dispersal. Coancestry and evolutionary clustering analyses identified genetic discontinuities within each city that coincided with a resource desert in New York City, major waterways in New Orleans, and roads in Salvador and Vancouver. Such replicated studies are crucial to assessing the generality of predictions from urban evolution, and have practical applications for pest management and public health. Future studies should include a range of global cities in different biomes, incorporate multiple species, and examine the impact of specific characteristics of the built environment and human socioeconomics on gene flow.

Authors

  • Combs, Matthew ;
  • Byers, Kaylee A. ;
  • Ghersi, Bruno M. ;
  • Blum, Michael J. ;
  • Caccone, Adalgisa ;
  • Costa, Federico ;
  • Himsworth, Chelsea G. ;
  • Richardson, Jonathan L. ;
  • Munshi-South, Jason
0 Citations0 Mentions42% FAIR1.0 Dataset Index
10.14288/1.0397575January 2020

Data from: Soil erodibility differs according to heritable trait variation and nutrient-induced plasticity in the salt marsh engineer Spartina alterniflora (Version: 1)

Use of landform engineers for habitat restoration has often resulted in unanticipated outcomes. It is possible that departures from expectation arise because applications do not adequately account for the influence of heritable and non-heritable phenotypic variation on ecosystem attributes. In this study, we performed a common garden greenhouse experiment to determine whether soil shear strength—a characteristic linked to erosion resistance—varies according to heritable and plastic trait expression in Spartina alterniflora grown under contrasting nutrient regimes. We detected heritable variation across a broad spectrum of functional traits, including nutrient uptake. We also found that S. alterniflora exhibited trait-specific differences in nutrient-induced phenotypic plasticity. Heritable trait differences and plasticity together explained approximately 70% of the observed variation in soil shear strength. Soil shear strength increased when plants received more nutrients, but the influence of heritable variation on soil shear strength was equal to or larger than that of nutrient-induced plasticity. These findings illustrate that heritable and non-heritable trait expression can potentially govern the fate of marsh ecosystems, which suggests that consideration should be given to both factors when deploying landform engineers for coastal restoration.

Authors

  • Bernik, Brittany M. ;
  • Pardue, John H. ;
  • Blum, Michael J. ;
  • Bernik, BM ;
  • Blum, MJ ;
  • Pardue, JH
1 Citation0 Mentions77% FAIR2.2 Dataset Index
10.5061/dryad.898t03gAugust 2019

Bernik-et-al-2018_S-alt-Greenhouse-GenoXNutrients-ShootSubsampleData.csv

No description available

Authors

  • Bernik, Brittany M. ;
  • Pardue, John H. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR1.9 Dataset Index
10.5061/dryad.898t03g/2January 2018

Bernik-et-al-2018_S-alt-Greenhouse-GenoXNutrients-Trait-Soil-Data.csv

No description available

Authors

  • Bernik, Brittany M. ;
  • Pardue, John H. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR1.9 Dataset Index
10.5061/dryad.898t03g/1January 2018

Gulf_MSA_summaryoutput

No description available

Authors

  • Summers, Jennifer L. ;
  • Bernik, Brittany ;
  • Saunders, Colin J. ;
  • McLachlan, Jason S. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5061/dryad.c76q3t7/5January 2018

Atlantic_MSA_summaryoutput

No description available

Authors

  • Summers, Jennifer L. ;
  • Bernik, Brittany ;
  • Saunders, Colin J. ;
  • McLachlan, Jason S. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5061/dryad.c76q3t7/4January 2018

Chesapeake_MSA_summaryoutput

No description available

Authors

  • Summers, Jennifer L. ;
  • Bernik, Brittany ;
  • Saunders, Colin J. ;
  • McLachlan, Jason S. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5061/dryad.c76q3t7/3January 2018

sample_id_names

No description available

Authors

  • Summers, Jennifer L. ;
  • Bernik, Brittany ;
  • Saunders, Colin J. ;
  • McLachlan, Jason S. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5061/dryad.c76q3t7/1January 2018

SERC_KirkpatrickMarsh_MSA_summaryoutput

No description available

Authors

  • Summers, Jennifer L. ;
  • Bernik, Brittany ;
  • Saunders, Colin J. ;
  • McLachlan, Jason S. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR0.4 Dataset Index
10.5061/dryad.c76q3t7/2January 2018

Bernik-et-al-2018_S-alt-Greenhouse-MicrosatelliteGenotypeData.csv

No description available

Authors

  • Bernik, Brittany M. ;
  • Pardue, John H. ;
  • Blum, Michael J.
0 Citations0 Mentions77% FAIR1.9 Dataset Index
10.5061/dryad.898t03g/3January 2018