Data from: Do space-for-time assessments underestimate the impacts of logging on tropical biodiversity? An Amazonian case study using dung beetles

Human alteration of the global environment is leading to a pervasive loss
of biodiversity. Most studies evaluating human impacts on biodiversity
occur after the disturbance has taken place using spatially distinct sites
to determine the undisturbed reference condition. This approach is known
as a space-for-time (SFT) substitution. However, SFT substitution could be
underestimating biodiversity loss if spatial controls fail to provide
adequate inferences about pre-disturbance conditions. We compare the SFT
substitution with a before–after control–impact (BACI) approach by
assessing dung beetles before and after a logging exploration in the
Brazilian Amazon. We sampled 34 logging management units, of which 29 were
selectively logged with different intensities after our first collection.
We used dung beetle species richness, species composition and biomass as
our biodiversity response metrics and the gradient of selective logging
intensity as our explanatory metric. Only the BACI approach consistently
demonstrated the negative impacts of logging intensification on all dung
beetle community metrics. Moreover, the BACI approach explained
significantly more of the variance in all the relationships and it doubled
the estimates of species loss along the gradient of logging intensity when
compared to SFT. Synthesis and applications. Our results suggest that
space-for-time (SFT) substitution may greatly underestimate the
consequences on local species diversity and community turnover. These
results have important implications for researchers investigating human
impacts on biodiversity. Incentivizing before–after control–impact (BACI)
approaches will require longer-term funding to gather the data and
stronger links between researchers and landowners. However, BACI
approaches are accompanied by many logistical constraints, making the
continued use of SFT studies inevitable in many cases. We highlight that
non-significant results and weak effects should be viewed with caution.