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.