Reindeer movement, habitat preference and road permeability model data

Beyer, Hawthorne (2014): Reindeer movement, habitat preference and road permeability model data. University of Queensland. Dataset. doi:10.14264/uql.2014.80

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beyer_et_al_reindeer_data.zip Reindeer data, zipped (open access) Click to show the corresponding preview/stream application/zip 3.13MB 37

 
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Project name Reindeer movement, habitat preference and road permeability modelling
Project description
1. Impediments to animal movement are ubiquitous and vary widely in both scale and permeability. It is essential to understand how impediments alter ecological dynamics via their influence on animal behavioural strategies governing space use and, for anthropogenic features such as roads and fences, how to mitigate these effects to effectively manage species and landscapes.
2. Here, we focused primarily on barriers to movement, which we define as features that cannot be circumnavigated but may be crossed. Responses to barriers will be influenced by the movement capabilities of the animal, its proximity to the barriers, and habitat preference. We developed a mechanistic modelling framework for simultaneously quantifying the permeability and proximity effects of barriers on habitat preference and
movement.
3. We used simulations based on our model to demonstrate how parameters on movement, habitat preference and barrier permeability can be estimated statistically. We then applied the model to a case study of road effects on wild mountain reindeer summer movements.
4. This framework provided unbiased and precise parameter estimates across a range of strengths of preferences and barrier permeabilities. The quality of permeability estimates, however, was correlated with the number of times the barrier is crossed and the number of locations in proximity to barriers. In the case study we found reindeer avoided areas near roads and that roads are semi-permeable barriers to movement. There was strong avoidance of roads extending up to approximately 1 km for four of five animals, and having to cross roads reduced the probability of movement by 68.6% (range 3.5-99.5%).
5. Human infrastructure has embedded within it the idea of networks: nodes connected by linear features such as roads, rail tracks, pipelines, fences and cables, many of which divide the landscape and limit animal movement. The unintended but potentially profound consequences of infrastructure on animals remain poorly understood. The rigorous framework for simultaneously quantifying movement, habitat preference and barrier permeability developed here begins to address this knowledge gap.
Contact name Hawthorne Beyer
Contact email h.beyer@uq.edu.au
Creator name Beyer, Hawthorne
Creator(s) role Chief Investigator
Dataset name Reindeer movement, habitat preference and road permeability model data
Dataset description
Reindeer movement, habitat preference and road permeability model data

Overview: GPS data for wild reindeer were collected within a larger project in Rondane-South and Rondane-North wild reindeer management areas, a mountainous region of central-southern Norway (10 46’ E, 61 38’ N). We used locations collected from five adult female reindeer every three hours between 1 June to 29 September 2012 (N = 973, 960, 871, 971 and 974 locations, respectively). Around 60% of the area is located above tree-line between 1000 and 1500 m, and is dominated by rocks and lichen heath; lower elevations (above 500 m) are characterised by a mix of meadows, grass and willow communities. The area occupied by the reindeer used in this study extends between ca. 400 and 1900 m, and is fragmented by public and private roads (access to the latter is often restricted, so is characterised by lower traffic volumes than the former).

The data we provide can be used in conjunction with the R code in the Supplementary Materials of the published paper to fit the models presented in that paper.

The zip file contains five R data files corresponding to five reindeer. The files are named "data_" followed by one of the ID numbers of the reindeer (11264, 11265, 9397, 7625, 9406). Each R data (*.RData) file contains an R list object called "fitdata" in R, composed of the following data structures:

Definitions:
N_s = the number of movement "steps" (sequential telemetry locations) for a reindeer
N_a = the number of grid cells in the landscape (all cells falling within 5km of any telemetry point.

(i) fitdata$usehab

A matrix (dimensions: N_s rows, 4 columns) of 'used' habitat types (the habitat value at each telemetry location in the movement path). The four columns are: elevation (km), elevation^2, distance to road (km), distance to road^2. The squared terms are included because the habitat preference model uses quadratic terms to allow for non-linear preference with respect to the two habitat covariates.

(ii) fitdata$availhab

A matrix (dimensions: N_a rows, 4 columns) of 'available' habitat types (the habitat value at each raster grid cell in the spatial domain of the analysis). The four columns are: elevation (km), elevation^2, distance to road (km), distance to road^2.

(iii) fitdata$use.xy

A matrix (dimensions N_s + 1 rows, 2 columns) of the x and y coordinates (km) of the reindeer telemetry locations. This matrix is used to precalculate a large distance matrix ("dm") representing the distances among all use and available points (dimensions: N_s rows, N_a columns). Although this 'dm' matrix is very large, pre-calculating the distance matrix greatly improves the speed of model fitting by eliminating the need to repeatedly re-calculate distances.

(iv) fitdata$stepdst

A vector of length N_s - 1 representing the Euclidean distance (km) between consecutive telemetry locations.

(v) fitdata$avail.xy

A matrix (dimensions N_a rows, 2 columns) of the x and y coordinates (km) of the grid cells forming the 'availability' sample.

(vi) fitdata$use.rdzn

A vector of length N_s containing arbitrary ID numbers corresponding to regions of space that are bounded by a network of roads. This could be conceptualised in GIS terms as forming polygons based on the lines contained in the road network, and assigning an arbitrary unique ID to each of those polygons. Road crossings are indicated by a change in the ID number in this time series. The reason for using this approach to identifying road crossings is computational efficiency, and to avoid the assumption that the straight-line connected two consecutive telemetry locations can be used to calculate road crossings. For example, if this straight line 'clips' a bend in a road then that would indicate 2 crossings, while the animal may in fact have remained in the same region without ever crossing a road.

(vii) fitdata$avail.rdzn

A vector of length N_a containing arbitrary ID numbers corresponding to regions of space that are bounded by a network of roads (see vi) for each grid cell in the availability sample.

Telemetry and habitat data for 5 reindeer over 1 summer; R data objects.

Access conditions Open Access
Licencing and terms of access Creative Commons Attribution (only)

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ANZSRC Field of Research (FoR) Code 060207 Population Ecology
010202 Biological Mathematics
050104 Landscape Ecology
DOI 10.14264/uql.2014.80
Type of data Telemetry and habitat data for 5 reindeer over 1 summer
R data objects
Data Volume 3.1MB
Software required R
Language eng
Collection start date 2012-06-01
Collection end date 2012-09-29
Time coverage start date 2012-06-01
Time coverage end date 2012-09-29
Keyword Reindeer
Movement model
Habitat selection
Geographic co-ordinates

8.497884,60.847504

Collection type Dataset
Publisher University of Queensland
Publication Year 2014
Copyright notice 2014, Norwegian Institute for Nature Research
Additional Notes We kindly request that you inform the Norwegian Institute for Nature Research (NINA, contact: Dr. Olav Strand, olav.strand@nina.no) prior to the reuse of these data for purposes other than replication of the analyses presented in the paper.

Document type: Data Collection
Collections: Research Data Collections
School of Biological Sciences Publications
 
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Created: Wed, 28 May 2014, 12:57:47 EST by Hawthorne Beyer