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Regional GAM Species Counts

Observing Animal Species Abundance and Distribution

@kaggle.thedevastator_regional_gam_species_counts

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About this Dataset

Regional GAM Species Counts


Regional GAM Species Counts

Observing Animal Species Abundance and Distribution

By [source]


About this dataset

This dataset captures detailed information about the abundance and distribution of multiple animal species in different parts of the Regional GAM network. By analyzing this data, researchers gain valuable insight into species trends over time, species population growth or decline, seasonal migration patterns, and other important ecological patterns. Moreover, this dataset helps us to understand risks associated with animal populations and ecosystems; aiding decision-making related to land use for conservation and sustainability initiatives. This data provides an easily accessible resource for monitoring changes in animals' ranges and distributions across the region – enabling powerful analysis which can inform sound management decisions to promote conservation efforts. In sum, this dataset holds great promise for scientists seeking an improved understanding of wildlife dynamics; making it a powerful tool for both monitoring biodiversity in our changing world as well as informing proactive management strategies that will ultimately help keep our planet healthy into the future

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How to use the dataset

This dataset contains information about animal species and their occurrence per site, which can be used to gain insights into species abundance and distribution in the Regional GAM network. This data can help researchers analyze species trends, population growth or decline, animal migrations, and other important ecological factors.

Users of this dataset can analyze the presence or absence of a particular species in different sites across the region, as well as their abundance by counting individual sightings. Additionally, by combining datasets such as those contained in this one with other environmental factors (e.g., water levels), users can gain further insight into animals’ behavior and ecology within any given location over time.

The following steps outline how to use this dataset to analyze animal populations:

  • Download all necessary files from Kaggle for your analysis
  • Use an online tool such as Pandas or RStudio to extract desired data from each file into one unified table
  • Select relevant columns for your analysis (e.g., Species Name, Location/Site Name), specify date ranges if necessary and arrange them in an easily readable manner using sorting tools within the software program you’re using
  • Filter entries related to a certain period of time (e.g., last 7 days), location or unique combination of both if needed 5) Choose appropriate chart or graph types depending on what kind of data you want to present visually 6) Finally plot/display your findings on a map / basis plot / 3D-model / etc…for best clarity

This dataset provides valuable insight into environmental conditions which may affect wildlife behavior. By following these simple steps researchers should be able visualize trends associated with certain areas over periods of time allowing them better understand how animal populations are affected by land-use decisions and climate change among others!

Research Ideas

  • Species Conservation: This data set can be used to assess the health of a species' population in a particular region and how this varies over time. Researchers can use data trends to identify declining populations and areas of conservation needs, allowing them to create appropriate management plans focused on species protection.
  • Wildlife Monitoring: Observing the species count at different sites can provide researchers with an insight into animal behavior, migration patterns and habitat usage which in turn informs wildlife management plans.
  • Climate Change: By assessing population changes over time, researchers can use this dataset to explore how climate change is impacting specific animal populations and inform conservation initiatives accordingly/

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: Dataset multispecies Regional GAM.csv

Column name Description
SPECIES The name of the species being counted. (String)
SITE The location where the species was observed. (String)
YEAR The year when the species was observed. (Integer)
MONTH The month when the species was observed. (Integer)
DAY The day when the species was observed. (Integer)
COUNT The number of individuals of that species observed. (Integer)

File: regional GAM data.csv

Column name Description
SPECIES The name of the species being counted. (String)
SITE The location where the species was observed. (String)
YEAR The year when the species was observed. (Integer)
MONTH The month when the species was observed. (Integer)
DAY The day when the species was observed. (Integer)
COUNT The number of individuals of that species observed. (Integer)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Dataset Multispecies Regional Gam

@kaggle.thedevastator_regional_gam_species_counts.dataset_multispecies_regional_gam
  • 321.54 KB
  • 229473 rows
  • 6 columns
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CREATE TABLE dataset_multispecies_regional_gam (
  "species" VARCHAR,
  "site" VARCHAR,
  "year" VARCHAR,
  "month" VARCHAR,
  "day" VARCHAR,
  "count" VARCHAR
);

Regional Gam Data

@kaggle.thedevastator_regional_gam_species_counts.regional_gam_data
  • 181.42 KB
  • 114736 rows
  • 6 columns
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CREATE TABLE regional_gam_data (
  "species" VARCHAR,
  "site" VARCHAR,
  "year" BIGINT,
  "month" BIGINT,
  "day" BIGINT,
  "count" BIGINT
);

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