A unifying framework for analyzing temporal changes in functional and taxonomic diversity along disturbance gradients

Frameworks exclusively considering functional diversity are gaining popularity, as they complement and extend the information provided by taxonomic diversity metrics, particularly in response to disturbance. Taxonomic diversity should be included in functional diversity frameworks to uncover the functional mechanisms causing species loss following disturbance events. We present and test a predictive framework that considers temporal functional and taxonomic diversity responses along disturbance gradients. Our proposed framework allows us to test different multidimensional metrics of taxonomic diversity that can be directly compared to calculated multidimensional functional diversity metrics. It builds on existing functional diversity-disturbance frameworks both by using a gradient approach and by jointly considering taxonomic and functional diversity. We used previously unpublished stream insect community data collected prior to, and for the two years following, an extreme flood event that occurred in 2013. Using 14 northern Colorado mountain streams, we tested our framework and determined that taxonomic diversity metrics calculated using multidimensional methods resulted in concordance between taxonomic and functional diversity responses. By considering functional and taxonomic diversity together and using a gradient approach, we were able to identify some of the mechanisms driving species losses following this extreme disturbance event.

Methods
We sampled 14 streams across three drainages in summer 2011 prior to the flood for another study (Harrington et al. 2016) and resampled them again post-flood in the summers of 2014 and 2015 to assess species persistence to this extreme event (Poff et al. 2018). Each site received a normalized channel disturbance score, hereafter referred to as channel disturbance. Values across the 14 sites ranged from 0.2 to 1.0 (See Poff et al. 2018 for more complete methods).

In the current work, we use previously unreported community data to test our predictions. The stream insect community was sampled using a 0.01 m2 Hess sampler, a standard method for quantitatively sampling stream insect density (Hauer and Lamberti 2006). In each year, we collected five substrate samples in run/riffle habitat by agitating the substrate to 10 cm depth. Invertebrate samples were stored in 100% ethanol prior to being cleaned of debris to allow invertebrate identification and enumeration in the lab using a dissecting microscope to the lowest practical taxonomic level. All taxa were identified to genus except for the early instars of chloroperlid stoneflies, simuliid blackflies, elmid beetles, and dytiscid beetles, which were all identified to family and assigned traits at the family-level.