Species richness and identity both determine the biomass of global reef fish communities

A comprehensive review and evaluation of species richness estimation

MOTIVATION

The statistical problem of estimating the total number of distinct species in a population (or distinct elements in a multiset), given only a small sample, occurs in various areas, ranging from the unseen species problem in ecology to estimating the diversity of immune repertoires. Accurately estimating the true richness from very small samples is challenging, in particular for highly diverse populations with many rare species. Depending on the application, different estimation strategies have been proposed that incorporate explicit or implicit assumptions about either the species distribution or about the sampling process. These methods are scattered across the literature, and an extensive overview of their assumptions, methodology, and performance is currently lacking.

RESULTS

We comprehensively review and evaluate a variety of existing methods on real and simulated data with different compositions of rare and abundant species. Our evaluation shows that, depending on species composition, different methods provide the most accurate richness estimates. Simple methods based on the observed number of singletons yield accurate asymptotic lower bounds for several of the tested simulated species compositions, but tend to underestimate the true richness for heterogeneous populations and small samples containing 1% to 5% of the population. When the population size is known, upsampling (extrapolating) estimators such as PreSeq and RichnEst yield accurate estimates of the total species richness in a sample that is up to 10 times larger than the observed sample.

AVAILABILITY

Source code for data simulation and richness estimation is available at https://gitlab.com/rahmannlab/speciesrichness.

Neighbourhood benthic configuration reveals hidden co-occurrence social diversity

Ecological interactions among benthic communities are crucial for shaping marine ecosystems. Understanding these interactions is essential for predicting how ecosystems will respond to environmental changes, invasive species, and conservation management. However, determining the prevalence of species interactions at the community scale is challenging. To overcome this challenge, we employ tools from social network analysis, specifically exponential random graph modelling (ERGM). Our approach explores the relationships among animal and plant organisms within their neighbourhoods. Inspired by companion planting in agriculture, we use spatiotemporal co-occurrence as a measure of mixed species interaction. In other words, the variety of community interactions based on co-occurrence defines what we call 'co-occurrence social diversity'. Our objective is to use ERGM to quantify the proportion of interactions at both the simple paired level and the more complex triangle level, enabling us to measure and compare co-occurrence social diversity. Applying our approach to the Spanish coastal zone across eight sites, five depths, and sunlit/shaded aspects, we discover that 80% of sessile communities, consisting of over a hundred species, exhibit co-occurrence social diversity, with 5% of species consistently forming associations with other species. These organism-level interactions probably have a significant impact on the overall character of the site. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Understanding the transmission of bacterial agents of sapronotic diseases using an ecosystem-based approach: A first spatially realistic metacommunity model

Pathogens such as bacteria, fungi and viruses are important components of soil and aquatic communities, where they can benefit from decaying and living organic matter, and may opportunistically infect human and animal hosts. One-third of human infectious diseases is constituted by sapronotic disease agents that are natural inhabitants of soil or aquatic ecosystems. They are capable of existing and reproducing in the environment outside of the host for extended periods of time. However, as ecological research on sapronosis is infrequent and epidemiological models are even rarer, very little information is currently available. Their importance is overlooked in medical and veterinary research, as well as the relationships between free environmental forms and those that are pathogenic. Here, using dynamical models in realistic aquatic metacommunity systems, we analyze sapronosis transmission, using the human pathogen Mycobacterium ulcerans that is responsible for Buruli ulcer. We show that the persistence of bacilli in aquatic ecosystems is driven by a seasonal upstream supply, and that the attachment and development of cells to aquatic living forms is essential for such pathogen persistence and population dynamics. Our work constitutes the first set of metacommunity models of sapronotic disease transmission, and is highly flexible for adaptation to other types of sapronosis. The importance of sapronotic agents on animal and human disease burden needs better understanding and new models of sapronosis disease ecology to guide the management and prevention of this important group of pathogens.

Low human interest for the most at-risk reef fishes worldwide

Human interest in biodiversity is essential for effective conservation action but remains poorly quantified at large scales. Here, we investigated human interest for 2408 marine reef fishes using data obtained from online public databases and social media, summarized in two synthetic dimensions, research effort and public attention. Both dimensions are mainly related to geographic range size. Research effort is also linked to fishery importance, while public attention is more related to fish aesthetic value and aquarium trade importance. We also found a strong phylogenetic bias, with certain fish families receiving disproportional research effort and public attention. Most concerningly, species at the highest risk of extinction and those most vulnerable to future climate change tend to receive less research effort and public attention. Our results provide a lens through which examining the societal attention that species garner, with the ultimate goals to improve conservation strategies, research programs, and communication plans.

Marine protected areas promote stability of reef fish communities under climate warming

Protection from direct human impacts can safeguard marine life, yet ocean warming crosses marine protected area boundaries. Here, we test whether protection offers resilience to marine heatwaves from local to network scales. We examine 71,269 timeseries of population abundances for 2269 reef fish species surveyed in 357 protected versus 747 open sites worldwide. We quantify the stability of reef fish abundance from populations to metacommunities, considering responses of species and functional diversity including thermal affinity of different trophic groups. Overall, protection mitigates adverse effects of marine heatwaves on fish abundance, community stability, asynchronous fluctuations and functional richness. We find that local stability is positively related to distance from centers of high human density only in protected areas. We provide evidence that networks of protected areas have persistent reef fish communities in warming oceans by maintaining large populations and promoting stability at different levels of biological organization.

Identifying microbiota community patterns important for plant protection using synthetic communities and machine learning

Plant-associated microbiomes contribute to important ecosystem functions such as host resistance to biotic and abiotic stresses. The factors that determine such community outcomes are inherently difficult to identify under complex environmental conditions. In this study, we present an experimental and analytical approach to explore microbiota properties relevant for a microbiota-conferred host phenotype, here plant protection, in a reductionist system. We screened 136 randomly assembled synthetic communities (SynComs) of five bacterial strains each, followed by classification and regression analyses as well as empirical validation to test potential explanatory factors of community structure and composition, including evenness, total commensal colonization, phylogenetic diversity, and strain identity. We find strain identity to be the most important predictor of pathogen reduction, with machine learning algorithms improving performances compared to random classifications (94-100% versus 32% recall) and non-modelled predictions (0.79-1.06 versus 1.5 RMSE). Further experimental validation confirms three strains as the main drivers of pathogen reduction and two additional strains that confer protection in combination. Beyond the specific application presented in our study, we provide a framework that can be adapted to help determine features relevant for microbiota function in other biological systems.

Habitat type drives the spatial distribution of Australian fish chorus diversitya)

Fish vocalize in association with life functions with many species calling en masse to produce choruses. Monitoring the distribution and behavior of fish choruses provides high-resolution data on fish distribution, habitat use, spawning behavior, and in some circumstances, local abundance. The purpose of this study was to use long-term passive acoustic recordings to obtain a greater understanding of the patterns and drivers of Australian fish chorus diversity at a national scale. This study detected 133 fish choruses from year-long recordings taken at 29 Australian locations with the highest fish chorus diversity identified at a site in the country's northern, tropical waters. A linear model fitted with a generalized least squares regression identified geomorphic feature type, benthic substrate type, and northness (of slope) as explanatory variables of fish chorus diversity. Geomorphic feature type was identified as the significant driver of fish chorus diversity. These results align with broad-scale patterns reported previously in fish biodiversity, fish assemblages, and fish acoustic diversity. This study has highlighted that passive acoustic monitoring of fish chorus diversity has the potential to be used as an indicator of fish biodiversity and to highlight habitats of ecological importance.

Biodiversity-ecosystem function relationships change in sign and magnitude across the Hill diversity spectrum

Motivated by accelerating anthropogenic extinctions, decades of biodiversity-ecosystem function (BEF) experiments show that ecosystem function declines with species loss from local communities. Yet, at the local scale, changes in species' total and relative abundances are more common than species loss. The consensus best biodiversity measures are Hill numbers, which use a scaling parameter, ℓ, to emphasize rarer versus more common species. Shifting that emphasis captures distinct, function-relevant biodiversity gradients beyond species richness. Here, we hypothesized that Hill numbers that emphasize rare species more than richness does may distinguish large, complex and presumably higher-functioning assemblages from smaller and simpler ones. In this study, we tested which values of ℓ produce the strongest BEF relationships in community datasets of ecosystem functions provided by wild, free-living organisms. We found that ℓ values that emphasized rare species more than richness does most often correlated most strongly with ecosystem functions. As emphasis shifted to more common species, BEF correlations were often weak and/or negative. We argue that unconventional Hill diversities that shift emphasis towards rarer species may be useful for describing biodiversity change, and that employing a wide spectrum of Hill numbers can clarify mechanisms underlying BEF relationships. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Assembly rules of coral reef fish communities along the depth gradient

Coral reefs are home to some of the most studied ecological assemblages on the planet. However, differences in large-scale assembly rules have never been studied using empirical quantitative data stratified along the depth gradient of reefs. Consequently, little is known about the small- and regional-scale effects of depth on coral reef assemblages. Using a large dataset of underwater surveys, we observed that the influence of classic biogeographic drivers on the species richness of coral reef fishes changes significantly with depth, shaping distinct assemblages governed by different rules in mesophotic coral ecosystems. We show that a general pattern of decreased taxonomic and functional richness of reef fish assemblages with depth results from convergent filtering of species composition and trophic strategies on deeper reefs across ocean basins and that at smaller scales deep-reef communities are less influenced by regional factors than shallower reefs.

Foundational biodiversity effects propagate through coastal food webs via multiple pathways

Relatively few studies have attempted to resolve the pathways through which the effects of biodiversity on ecosystem functioning cascade from one trophic level to another. Here, we manipulated the richness of habitat-forming seaweeds in a western Atlantic estuary to explore how changes in foundation species diversity affect the structure and functioning of the benthic consumer communities that they support. Structural equation modeling revealed that macroalgal richness enhanced invertebrate abundance, biomass, and diversity, both directly by changing the quality and palatability of the foundational substrate and indirectly by increasing the total biomass of available habitat. Consumer responses were largely driven by a single foundational seaweed, although stronger complementarity among macroalgae was observed for invertebrate richness. These findings with diverse foundational phyla extend earlier inferences from terrestrial grasslands by showing that biodiversity effects can simultaneously propagate through multiple independent pathways to maintain animal foodwebs. Our work also highlights the potential ramifications of human-induced changes in marine ecosystems.