DOI: 10.5061/dryad.9zw3r22c5
title: Data from: How do habitat amount and habitat fragmentation drive time-delayed responses of biodiversity to land-use change?

description: Land-use change is a root cause of the extinction crisis, but links
 between habitat change and biodiversity loss are not fully understood.
 While there is evidence that habitat loss is an important extinction
 driver, the relevance of habitat fragmentation remains debated. Moreover,
 while time-delays of biodiversity responses to habitat transformation are
 well-documented, time-delayed effects have been ignored in the habitat
 loss vs. fragmentation debate. Here, using a hierarchical Bayesian multi-
 species occupancy framework, we systematically tested for time-delayed
 responses of bird and mammal communities to habitat loss and to habitat
 fragmentation. We focused on the Argentine Chaco, where deforestation has
 been widespread recently. We used an extensive field dataset on birds and
 mammals, along with a time series of annual woodland maps from 1985-2016
 covering recent and historical habitat transformations. Contemporary
 habitat amount explained bird and mammal occupancy better than past
 habitat amount. However, occupancy was affected more by past rather than
 recent fragmentation, indicating a time-delayed response to fragmentation.
 Considering past landscape patterns is therefore crucial for understanding
 current biodiversity patterns. Not accounting for land-use history ignores
 the possibility of extinction debt and can thus obscure impacts of
 fragmentation, potentially explaining contrasting findings of habitat loss
 vs. fragmentation studies.
description: <strong>Biodiversity data:</strong>
 Birds were recorded at 233 sites during three field surveys
 between 2009 and 2014, with a mean distance of 4.7-km between sites
 (standard deviation: SD=6.5-km). We conducted point counts at each site
 (two to nine point counts per site). Here, we only considered species that
 use woodland as their main habitat, as this is by far the dominant natural
 vegetation in the area and we wanted to test for time-delayed responses to
 woodland loss and fragmentation. We discarded migrant species to avoid
 seasonal effects and species associated with the Andean Cloud forest
 (i.e., Yungas) that were only recorded in the Chaco-Yungas
 ecotone.<br> Mammals were surveyed during two field surveys between
 2013 and 2016, using a total of 198 camera-trap stations. The mean
 distance between adjacent sites was 1.44-km (SD=1.74). We set cameras off
 trail where possible, to reduce detection bias associated with targeted
 sampling. Cameras were active between 14 and 84 trapping days (mean=39.8
 days), with a total sampling effort of 7,883 trapping days. We only
 considered woodland-dependent mammal species. 
 <strong>Landscape predictors:</strong>
 We calculated landscape-scale metrics of habitat amount and
 fragmentation, meaning that they described the spatial characteristics of
 entire landscapes, not individual patches. We extracted predictors for
 circular landscapes centered around each sampling site. Based on
 sensitivity analyses, we used a 4-km radius for birds, and a 2-km radius
 for mammals. We calculated one landscape predictor representing habitat
 amount: percentage of woodland. To characterize fragmentation, we
 calculated three predictors: percentage of edge, patch density and
 cohesion index.  To define the contemporary landscape
 predictors, we related each site to the landscape predictors of the year
 when biodiversity was sampled (e.g., sites sampled in 2015 were related to
 the predictors from 2015). We then derived a time series of past landscape
 predictors 24 years back in time (i.e., landscape patterns from 1 year
 prior to sampling, 2 years prior to sampling, etc.). We used a maximum
 time period of 24 years because this is the time span between the oldest
 Landsat-based woodland map (1985) and the oldest biodiversity sampling
 (2009) in our dataset.<br>