DOI: 10.5061/dryad.xd2547dqx
title: Data from: Joint spatial modeling of cluster size and density for a heavily hunted primate persisting in a heterogeneous landscape

description: Shared landscapes in which humans and wildlife coexist, are increasingly
 recognized as integral to conservation. Fine-scale data on the
 distribution and density of threatened wildlife are therefore critical to
 promote long-term coexistence. Yet, the spatial complexity of habitat,
 anthropic threats and animal behaviour in shared landscapes challenges
 conventional survey techniques. For social wildlife in particular, the
 size of sub-groups or clusters is likely to both vary in space and
 influence detectability, biasing density estimation and spatial
 prediction. Using the R package inlabru, we develop a full-likelihood
 joint log-Gaussian Cox process to simultaneously perform spatial distance
 sampling and model a spatially varying cluster size distribution, which we
 condition upon detection probability to mitigate cluster-size detection
 bias. We accommodate spatial dependencies by incorporating a
 non-stationary Gaussian Markov random field, enabling the explicit
 inclusion of geographical barriers to wildlife dispersal. We demonstrate
 this model using 136 georeferenced detections of Campbell’s monkey
 (Cercopithecus campbelli) clusters, collected with 398.56-km of line
 transects across a shared agroforest landscape mosaic (1067-km2) in
 Guinea-Bissau. We assess a suite of anthropogenic and environmental
 spatial covariates, finding that normalized difference vegetation index
 (NDVI) and proximity to mangroves are both powerful spatial predictors of
 density. We captured strong spatial variation in cluster size, likely
 driven by fission-fusion in response to the complex distribution of
 resources and risk in the landscape. If left unaccounted for under
 existing approaches, such variation may bias density surface estimation.
 We estimate a population of 10,301 (95% CI [7606-14,104]) individuals and
 produce a fine-scale predictive density map, revealing the importance of
 mangrove-habitat interfaces for the conservation of this heavily hunted
 primate. This work demonstrates a powerful, widely applicable approach for
 monitoring socially flexible wildlife and informing evidence-based
 conservation in complex, heterogeneous landscapes moving forward.
description: ## Data context Line transect survey data for Campbell's monkeys
 (*Cercopithecus campbelli*) were collected between January 19th and June
 18th, 2021 by co-authors A.S. and M.J., as part of a recently established
 and ongoing biodiversity monitoring program (BMP). The BMP is implemented
 as part of a Darwin Initiative project (26-018) by the University of
 Exeter and the Institute of Biodiversity and Protected Areas (IBAP) of
 Guinea-Bissau. Following standardised protocols, 64 individual line
 transects approximately 1-km in length were walked up to 6 times each for
 a total of 354 line transect repeats, with a cumulative walked effort of
 398.56-km. Observers moved at a constant pace of 1 to 1.5-km/h along each
 line transect and for each Campbell's monkey cluster detected,
 recorded the number of individuals (cluster size), the perpendicular
 distance between the centre of the cluster and the transect line
 (detection distance), and took GPS coordinates. Sampling was conducted
 between the hours of 07:06 and 19:18. To mitigate possible variation in
 detectability related to activity levels, survey start times were
 randomised within this window. GPS coordinates are censored (replaced with
 NA values) in this dataset due to conservation concerns. Please see the
 related article for more information and to request access to an
 uncensored geo-referenced version of this survey dataset. ## File
 description Survey data are provided as a comma-separated value (CSV) text
 file (censored_data.csv) as follows: "transect" is a unique
 transect identifier; "longitude" and "latitude" are
 censored as NA values; "distance" is the detection distance
 recorded in metres; "cluster" is the cluster size or number of
 individuals per observation; "date" is the day, month and year
 of the observation formatted as DD-MMM-YY; and "time" is the
 time of day formatted as HH:MM:SS. Transect data are provided as a CSV
 text file (transect.csv) as follows: "transect" is a unique
 transect identifier; "survey1" to "survey6" contain
 the date of a survey (if conducted) during survey occasions 1 to 6,
 formatted as day, month and year DD-MMM-YY; "repeats" is the
 total number of surveys conducted; "length" is the length of the
 transect in kilometres; and "total" is the total length surveyed
 at that transect in kilometres. NULL values indicate that a transect was
 not walked during that particular survey occasion.