Maximizing the value of forest restoration for tropical mammals by detecting three-dimensional habitat associations

Description:

Species detection data for 28 medium-large mammal species obtained using camera trap methods across a logging-induced degradation gradient. Cameras were deployed using a paired design across 74 sampling locations. Data were used to explore species-habitat associations with LiDAR-derived measures of forest structure.

Project: This dataset was collected as part of the following SAFE research project: Understanding covariation between mammalian diversity and forest carbon across a human-modified tropical landscape

Funding: These data were collected as part of research funded by:

• NERC (Standard grant, NE/K016407/1, http://gotw.nerc.ac.uk/list_full.asp?pcode=NE%2FK016407%2F1&classtype=ENRIs&classification=Biodiversity&cookieConsent=A)

This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.

XML metadata: GEMINI compliant metadata for this dataset is available here

Files: This consists of 1 file: DeereEtAl2020_PNAS.xlsx

DeereEtAl2020_PNAS.xlsx

This file contains dataset metadata and 2 data tables:

1. Site metadata and deployment details (described in worksheet Deployment)

   Description: Details of sampling locations, operational dates and survey effort for each camera trap station (N=126)

   Number of fields: 9

   Number of data rows: 126

   Fields:

   • Site_ID: Unique alphanumeric identifier of the location camera traps were deployed (Field type: location)
   • Habitat_Class: Forest condition relative to logging-indiced degradation. Follows Putz and Redford Classification scheme (Putz, Francis E., and Kent H. Redford. "The importance of defining 'forest': tropical forest degradation, deforestation, long‐term phase shifts, and further transitions." Biotropica 42.1 (2010): 10-20) (Field type: categorical)
   • Latitude: Geographic coordinate of camera trap location (Field type: latitude)
   • Longitude: Geographic coordinate of camera trap location (Field type: longitude)
   • Date_On: Date camera traps were deployed (Field type: date)
   • Time_On: Time camera traps were deployed (Field type: time)
   • Date_Off: Date camera traps were collected (Field type: date)
   • Time_Off: Time camera traps were collected (Field type: time)
   • CTNs: Total survey effort for camera trap station (Field type: numeric)

2. Species detection data (described in worksheet Detection)

   Description: Raw camera trap detection data for 28 medium-large mammal species obtained from 126 camera trap stations deployed using a paired design across 74 sampling locations

   Number of fields: 7

   Number of data rows: 29008

   Fields:

   • Site: Unique alphanumeric identifier of the location camera traps were deployed (Field type: location)
   • common_name: Mammal species identifier (Field type: taxa)
   • Sp_ID: Numeric species identifier, used to coerce dataframe into a 4D array (Field type: id)
   • Site_ID: Numeric site identifier, used to coerce dataframe into a 4D array (Field type: id)
   • Spatial_Rep: Spatial replicate indicative of the number of camera trap stations deployed at a site. Also used to coerce dataframe into a 4d array (Field type: replicate)
   • Temporal_Rep: Temporal replicate, each comprising six camera trap nights (Field type: replicate)
   • Detection: Presence/absence of species during survey period (Field type: abundance)

Date range: 2014-06-20 to 2017-10-09

Latitudinal extent: 4.5536 to 4.8121

Longitudinal extent: 117.4122 to 117.7398

Taxonomic coverage:
All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.