DOI: 10.5061/dryad.98sf7m0s6
title: Nest-site fidelity of Arctic Terns (Sterna paradisaea) in a managed environment exposed to benign human activity

description: Human activity near seabird colonies is often equated with disturbance.
 Coping with human disturbance is a critical task in the management of
 seabird colonies where human access is an issue. Nest-site fidelity and
 breeding dispersal were characterised in an Arctic Tern population exposed
 to a high level of benign human activity from resident conservation staff
 and public visitors. The annual return rate of nesting birds was 90% over
 the 10-year study period. Nest-site fidelity was high with most birds
 returning to the same 2 x 2 m square in subsequent years, in particular to
 nest sites that were against walls and exposed to a high level of human
 activity at close range. This indicates that human activity was not a
 deterrent to nesting by Arctic Terns. Breeding dispersal to other nearby
 colonies was low, except when related to colony abandonment. The data
 suggest that benign human activity from resident staff and public visitors
 can be a positive benefit, both within and across years, to Arctic Tern
 colonies. Managed public access could be considered an effective
 management tool for Arctic Tern conservation, as well as seabird colonies
 more widely.   
description: # Nest-site fidelity of Arctic Terns (Sterna paradisaea) in a managed
 environment exposed to benign human activity Raw data for the virtual grid
 analysis are in the file:
 **Arctic_Tern_site_fidelity_Inner-Farne_virtual_grid_recapture_data.csv**
 Each row represents the end point of a capture-recapture event for an
 individual bird. That is, the grid-cell location and type that the bird is
 recaptured in after its previous capture in the virtual grid. Data
 description | Data column | Content | | :---------- |
 :---------------------------------------------------------------------- |
 | SPEC | Species: always Arctic Tern (ARCTE) | | RING | The BTO ring
 number of the individual bird in that row | | PLACE | Location of the
 virtual grid: always Inner Farne (inf) | | RTYPE | Record type: always
 recapture (R) | | DTE | Date and time of recapture event (end point of
 capture-recapture event) | | THL | Total head length of individual (most
 at recapture) in millimetres | | YEAR | Year of recapture (end point of
 capture-recapture event) | | col.num | Virtual grid column at recapture
 (end point of capture-recapture event) | | row\.num | Virtual grid row at
 recapture (end point of capture-recapture event) | | iti.diff | Number of
 grid cells moved between capture and recapture | | iti.int | Interval in
 years between capture and recapture | | dest | Destination grid-cell type:
 nn, dn, nx or dx | | mov.tpe | Movement type: c(ori.cat, dest) | | ori.cat
 | Originating grid-cell type: nn, dn, nx or dx | | s.THL | Scaled (mean =
 0) and standardised (sd = 1) total head length | nn = *nothing special*,
 dn = *‘disturbed’*, nx = *edge*, dx = *‘disturbed’ and edge* where *edge*
 is against a wall or building, and *‘disturbed’* means directly exposed to
 human activity (directly next to a path or boardwalk) Concatenation of
 ori.cat and dest Analysis: Data can be analysed using R 4.4.2 and the
 packages *glmmTMB*
 [https://cran.r-project.org/web/packages/glmmTMB/index.html](https://cran.r-project.org/web/packages/glmmTMB/index.html) or *ordinal* [https://cran.r-project.org/web/packages/ordinal/index.html](https://cran.r-project.org/web/packages/ordinal/index.html) For example: dat &lt;- read.csv("/…directory-path…/Arctic_Tern_site_fidelity_Inner-Farne_virtual_grid_recapture_data.csv", header=T) \#data:   iti.int = interval between capture and recapture in years \#             ori.cat = originating grid-cell type \#             iti.diff = grid cells moved between capture and recapture \#             RING = ring number \# With package glmmTMB (for number of grid cells moved as count data): model &lt;- glmmTMB(iti.diff ~ iti.int + ori.cat + (1| RING), data= dat, family=nbinom2) \#or package ordinal (treating the number of grid cells moved as an ordered factor related to distance): model &lt;- clmm(iti.diff ~ iti.int * ori.cat + (1| RING), data= dat)# default link "logit" \# \# #### Movement of nesting Arctic Terns within the virtual grid on Inner Farne between capture and recapture. code datmf &lt;- read.csv(" ~Arctic_Tern_site_fidelity_Inner-Farne_virtual_grid_recapture_data.csv", header=T) \#data: iti.int = interval between capture and recapture in years \#     ori.cat = originating grid-cell type \#     iti.diff = grid cells moved between capture and recapture \#     s.THL = scaled and standardised total head length \#     RING = ring number m3.2 &lt;- glmmTMB(iti.diff ~ iti.int + ori.cat + (1| RING), data= datmf, family=nbinom2)