While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral ...hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.
In the marine realm, the tropics host an extraordinary diversity of taxa but the drivers underlying the global distribution of marine organisms are still under scrutiny and we still lack an accurate ...global predictive model. Using a spatial database for 6336 tropical reef fishes, we attempted to predict species richness according to geometric, biogeographical and environmental explanatory variables. In particular, we aimed to evaluate and disentangle the predictive performances of temperature, habitat area, connectivity, mid-domain effect and biogeographical region on reef fish species richness. We used boosted regression trees, a flexible machine-learning technique, to build our predictive model and structural equation modeling to test for potential ‘mediation effects’ among predictors. Our model proved to be accurate, explaining 80% of the total deviance in fish richness using a cross-validated procedure. Coral reef area and biogeographical region were the primary predictors of reef fish species richness, followed by coast length, connectivity, mid-domain effect and sea surface temperature, with interactions between the region and other predictors. Important indirect effects of water temperature on reef fish richness, mediated by coral reef area, were also identified. The relationship between environmental predictors and species richness varied markedly among biogeographical regions. Our analysis revealed that a few easily accessible variables can accurately predict reef fish species richness. They also highlight concerns regarding ongoing environmental declines, with region-specific responses to variation in environmental conditions predicting a variable response to anthropogenic impacts.
Although coral reefs support the largest concentrations of marine biodiversity worldwide, the extent to which the global system of marine-protected areas (MPAs) represents individual species and the ...breadth of evolutionary history across the Tree of Life has never been quantified. Here we show that only 5.7% of scleractinian coral species and 21.7% of labrid fish species reach the minimum protection target of 10% of their geographic ranges within MPAs. We also estimate that the current global MPA system secures only 1.7% of the Tree of Life for corals, and 17.6% for fishes. Regionally, the Atlantic and Eastern Pacific show the greatest deficit of protection for corals while for fishes this deficit is located primarily in the Western Indian Ocean and in the Central Pacific. Our results call for a global coordinated expansion of current conservation efforts to fully secure the Tree of Life on coral reefs.
Coral reefs are experiencing declines due to climate change and local human impacts. While at a local scale these impacts induce biodiversity loss and shifts in community structure, previous ...biogeographical analyses recorded consistent taxonomic structure of fish communities across global coral reefs. This suggests that regional communities represent a random subset of the global species and traits pool, whatever their species richness. Using distributional data on 3586 fish species and latest advances in species distribution models, we show marked gradients in the prevalence of size classes and diet categories across the biodiversity gradient. This divergence in trait structure is best explained by reef isolation during past unfavourable climatic conditions, with large and piscivore fishes better represented in isolated areas. These results suggest the risk of a global community re-organization if the ongoing climate-induced reef fragmentation is not halted.
Coral reefs are among the most species-rich and threatened ecosystems on Earth, yet the extent to which human stressors determine species occurrences, compared with biogeography or environmental ...conditions, remains largely unknown. With ever-increasing human-mediated disturbances on these ecosystems, an important question is not only how many species can inhabit local communities, but also which biological traits determine species that can persist (or not) above particular disturbance thresholds. Here we show that human pressure and seasonal climate variability are disproportionately and negatively associated with the occurrence of large-bodied and geographically small-ranging fishes within local coral reef communities. These species are 67% less likely to occur where human impact and temperature seasonality exceed critical thresholds, such as in the marine biodiversity hotspot: the Coral Triangle. Our results identify the most sensitive species and critical thresholds of human and climatic stressors, providing opportunity for targeted conservation intervention to prevent local extinctions.
The host specificity of a parasite is not merely a function of how many host species it can exploit, but also of how closely related these host species are to each other. Here, a new index of host ...specificity is proposed, one that takes into account the average taxonomic or phylogenetic distance between pairs of host species used by a parasite. The index is derived from measures of taxonomic distinctness used in biodiversity studies. It is easy to compute and interpret, ranging from a minimum value of 1 when all host species are members of the same genus, to a maximum of 5, when all host species belong to different classes. The variance of this measure can also be computed, and provides additional information on the taxonomic or phylogenetic structure of the host assemblage. Using data on helminth parasites of Canadian freshwater fishes, we show that the new index, unlike the mere number of known host species, is independent of study effort i.e. the number of published records of a parasite. Although the index and the number of known hosts are not entirely independent statistically, each captures a different aspect of host specificity. For instance, although acanthocephalans infect significantly more host species than trematodes, cestodes or nematodes, there is no difference in the average index value among these 4 helminth taxa, suggesting that the average taxonomic distances between the host species of a parasite do not vary among these higher taxa. We recommend the use of our new index in future comparative studies of host specificity, in particular when the focus is on the evolutionary history of parasites and of their past colonizations of host lineages.
Restricted dispersal in a sea of gene flow Benestan, L; Fietz, K; Loiseau, N ...
Proceedings - Royal Society. Biological sciences/Proceedings - Royal Society. Biological Sciences,
05/2021, Letnik:
288, Številka:
1951
Journal Article
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How far do marine larvae disperse in the ocean? Decades of population genetic studies have revealed generally low levels of genetic structure at large spatial scales (hundreds of kilometres). Yet ...this result, typically based on discrete sampling designs, does not necessarily imply extensive dispersal. Here, we adopt a continuous sampling strategy along 950 km of coast in the northwestern Mediterranean Sea to address this question in four species. In line with expectations, we observe weak genetic structure at a large spatial scale. Nevertheless, our continuous sampling strategy uncovers a pattern of isolation by distance at small spatial scales (few tens of kilometres) in two species. Individual-based simulations indicate that this signal is an expected signature of restricted dispersal. At the other extreme of the connectivity spectrum, two pairs of individuals that are closely related genetically were found more than 290 km apart, indicating long-distance dispersal. Such a combination of restricted dispersal with rare long-distance dispersal events is supported by a high-resolution biophysical model of larval dispersal in the study area, and we posit that it may be common in marine species. Our results bridge population genetic studies with direct dispersal studies and have implications for the design of marine reserve networks.
Ecological theory suggests that spatial distribution of biodiversity is strongly driven by community assembly processes. Thus the study of diversity patterns combined with null model testing has ...become increasingly common to infer assembly processes from observed distributions of diversity indices. However, results in both empirical and simulation studies are inconsistent. The aim of our study is to determine with simulated data which facets of biodiversity, if any, may unravel the processes driving its spatial patterns, and to provide practical considerations about the combination of diversity indices that would produce significant and congruent signals when using null models. The study is based on simulated species' assemblages that emerge under various landscape structures in a spatially explicit individual-based model with contrasting, predefined assembly processes. We focus on four assembly processes (species-sorting, mass effect, neutral dynamics and competition colonization trade-off) and investigate the emerging species' distributions with varied diversity indices (alpha, beta and gamma) measured at different spatial scales and for different diversity facets (taxonomic, functional and phylogenetic). We find that 1) the four assembly processes result in distinct spatial distributions of species under any landscape structure, 2) a broad range of diversity indices allows distinguishing between communities driven by different assembly processes, 3) null models provide congruent results only for a small fraction of diversity indices and 4) only a combination of these diversity indices allows identifying the correct assembly processes. Our study supports the inference of assembly processes from patterns of diversity only when different types of indices are combined. It highlights the need to combine phylogenetic, functional and taxonomic diversity indices at multiple spatial scales to effectively infer underlying assembly processes from diversity patterns by illustrating how combination of different indices might help disentangling the complex question of coexistence.
Host specificity has 2 independent facets: the extent to which different host species are used by a parasite, and the phylogenetic distances among these hosts. Although the number of host species ...exploited by a parasite commonly is used as a measure of host specificity, it fails to capture ecological and phylogenetic differences among hosts. Here, a new index of host specificity, STD*, is developed and illustrated. This index measures the average taxonomic distinctness among the host species used by a parasite, weighted for the parasite's prevalence in the different hosts. For a given number of host species, the index approaches its minimum value when a parasite achieves high prevalence in a few closely related host species, and the index approaches its highest value when a parasite reaches its highest prevalence values in distantly related host species. Simple hypothetical examples are used to demonstrate the index's computation and some of its properties. The new index is influenced independently both by the taxonomic (or phylogenetic) affinities of a set of host species and by the distribution of prevalence values among these hosts. A single value cannot truly capture all the nuances of a phenomenon as complex as host specificity; nevertheless, the proposed index incorporates the features of specificity that are most relevant to parasitologists and will be a useful tool for comparative studies.
The challenges of Reproducibility and Replicability (R & R) in computer science experiments have become a focus of attention in the last decade, as efforts to adhere to good research practices have ...increased. However, experiments using Deep Learning (DL) remain difficult to reproduce due to the complexity of the techniques used. Challenges such as estimating poverty indicators (e.g., wealth index levels) from remote sensing imagery, requiring the use of huge volumes of data across different geographic locations, would be impossible without the use of DL technology. To test the reproducibility of DL experiments, we report a review of the reproducibility of three DL experiments which analyze visual indicators from satellite and street imagery. For each experiment, we identify the challenges found in the data sets, methods and workflows used. As a result of this assessment we propose a checklist incorporating relevant FAIR principles to screen an experiment for its reproducibility. Based on the lessons learned from this study, we recommend a set of actions aimed to improve the reproducibility of such experiments and reduce the likelihood of wasted effort. We believe that the target audience is broad, from researchers seeking to reproduce an experiment, authors reporting an experiment, or reviewers seeking to assess the work of others.
Plain Language Summary
This paper aims to help researchers understand the challenges of reproducing Deep Learning (DL) publications, mitigate reproducibility gaps, and make their own work more reproducible. We build on the work of others and add recommendations organized by (a) the quality of the data set (and associated metadata), (b) the DL methodology, (c) the implementation methodology, and the infrastructure used. To our knowledge, this is the first initiative of its kind to address the problem of reproducibility in remote sensing imagery and DL problems for real‐world tasks. We hope this paper lowers the barrier to entry for the DL community to improve research. Following the lifecycle mantra: reproduce!, then replicate! With the goal of improving reproducibility!
Key Points
We discuss the reproducibility challenges faced in research by Deep Learning approaches using Big Data
We provide advice for pre‐screening papers (before experiments) to avoid poorly invested effort
We present a recipe with a set of mitigation strategies to address common errors users (researchers, authors, reviewers) may encounter
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