{'fraction_non_alphanumeric': 0.03750884642604388, 'fraction_numerical': 0.017338995046001414, 'mean_word_length': 5.6674528301886795, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 1, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A needle in the haystack? Applying species co-occurrence frameworks with fish assemblage data to identify species associations and sharpen ecological hypotheses.

Different species can associate or interact in many ways, and methods exist for inferring associations and underlying mechanisms from incidence data (e.g., co-occurrence frameworks). These methods have received much criticism despite their recent resurgence in the literature. However, co-occurrence frameworks for identifying non-randomly associated species pairs (e.g. aggregated or segregated pairs) have value as heuristic tools for sharpening hypotheses concerning fish ecology. Here, I aimed to provide a case study examining species co-occurrence across 33 stream fish assemblages in southeastern Oklahoma, USA, which were sampled twice (1974 & 2014). I sought to determine: 1) which species were non-randomly associated, 2) what processes might have driven these associations, and 3) how consistent were patterns across time? Associations among most pairs of species (24 species; 276 unique pairs) were not significantly different from random (>80%). Among all significant, non-randomly associated species pairs (54 unique pairs), 78% (42 pairs) were aggregated and 22% (12 pairs) segregated. Most of these (28 pairs, 52%) were hypothesized to be driven by non-biotic mechanisms: habitat filtering (20 pairs; 37%), dispersal limitation (2 pairs; 0.4%), or both (6 pairs; 11%). The remaining 26 non-randomly associated pairs (48%) had no detectable signal of spatial or environmental factors involved with the association; therefore, the potential for biotic interaction was not refuted. Only 5 species pairs were consistently associated across both sampling periods: stonerollers Campostoma spp. and orangebelly darter Etheostoma radiosum; red shiner Cyprinella lutrensis and bullhead minnow Pimephales vigilax; bluegill sunfish Lepomis macrochirus and redear sunfish Lepomis microlophus; redfin shiner Lythrurus umbratilis and bluntnose minnow Pimephales notatus; and bigeye shiner Notropis boops and golden shiner Notemigonus crysoleucas. Frameworks for identifying non-randomly associated species pairs can provide insight into broader mechanisms of species assembly and point to potentially interesting species interactions (out of many possible pairs). However, this approach is best applied as a tool for sharpening hypotheses to be investigated further. Rather than a weakness, the heuristic nature is the strength of such methods, and can help guide biologists toward better questions by employing relatively cheap diversity survey data, that are often already in hand, so as to reduce complex interaction networks down to their non-stochastic parts which warrant further investigation. This article is protected by copyright. All rights reserved.