Effects of species’ traits and data characteristics on distribution models of threatened invertebrates

Efectos de las características ecológicas y de los datos sobre los modelos de distribución de invertebrados protegidos La escasez de información sobre la distribución de las especies amenazadas impide el desarrollo de estrategias para su conservación, un problema particularmente importante en el caso de los invertebrados. En este trabajo se evalúan los efectos que las características ecológicas y de los datos ejercen sobre la precisión de los modelos de distribución de 20 especies ibéricas de invertebrados amenazados. Se encontró que la precisión en los modelos predictivos se ve afectada mayoritariamente por las características de los datos. Las especies que obtienen modelos de distribución más precisos son aquellas con mayor tamaño de muestra o menor área de ocurrencia relativa (ROA). Además, las especies relacionadas con hábitats difíciles de detectar mediante SIG, como las especies riparias, tienden a ser más difíciles de predecir. Palabras clave: Características ecológicas, Modelos de distribución de especies, Península ibérica, Precisión del modelo, Rango de distribución geográfica, Tamaño de muestra.The lack of information about the distribution of threatened species inhibits the development of strategies for their conservation. This is a particularly important problem when considering invertebrates. Here we evaluate the effects of species’ traits and data characteristics on the accuracy of species distribution models (SDM) of 20 threatened Iberian invertebrates. We found that the accuracy of the predictions was mostly affected by the characteristics of the data. Species whose distributions were most accurately modelled were those with a greater sample size or smaller relative occurrence area (ROA). Species in habitats that were difficult to detect using GIS data, such as riparian species, tended to be more difficult to predict. Key words: Ecological traits, Geographical distribution range, Iberian peninsula, Predictive accuracy, Sample size, Species distribution modelling.Efectos de las características ecológicas y de los datos sobre los modelos de distribución de invertebrados protegidos La escasez de información sobre la distribución de las especies amenazadas impide el desarrollo de estrategias para su conservación, un problema particularmente importante en el caso de los invertebrados. En este trabajo se evalúan los efectos que las características ecológicas y de los datos ejercen sobre la precisión de los modelos de distribución de 20 especies ibéricas de invertebrados amenazados. Se encontró que la precisión en los modelos predictivos se ve afectada mayoritariamente por las características de los datos. Las especies que obtienen modelos de distribución más precisos son aquellas con mayor tamaño de muestra o menor área de ocurrencia relativa (ROA). Además, las especies relacionadas con hábitats difíciles de detectar mediante SIG, como las especies riparias, tienden a ser más difíciles de predecir. Palabras clave: Características ecológicas, Modelos de distribución de especies, Península ibérica, Precisión del modelo, Rango de distribución geográfica, Tamaño de muestra

Environmental drivers of distribution and reef development of the Mediterranean coral Cladocora caespitosa

Cladocora caespitosa is the only Mediterranean scleractinian similar to tropical reef-building corals. While this species is part of the recent fossil history of the Mediterranean Sea, it is currently considered endangered due to its decline during the last decades. Environmental factors affecting the distribution and persistence of extensive bank reefs of this endemic species across its whole geographic range are poorly understood. In this study, we examined the environmental response of C. caespitosa and its main types of assemblages using ecological niche modeling and ordination analysis. We also predicted other suitable areas for the occurrence of the species and assessed the conservation effectiveness of Mediterranean marine protected areas (MPAs) for this coral. We found that phosphate concentration and wave height were factors affecting both the occurrence of this versatile species and the distribution of its extensive bioconstructions in the Mediterranean Sea. A set of factors (diffuse attenuation coefficient, calcite and nitrate concentrations, mean wave height, sea surface temperature, and shape of the coast) likely act as environmental barriers preventing the species from expansion to the Atlantic Ocean and the Black Sea. Uncertainties in our large-scale statistical results and departures from previous physiological and ecological studies are also discussed under an integrative perspective. This study reveals that Mediterranean MPAs encompass eight of the ten banks and 16 of the 21 beds of C. caespitosa. Preservation of water clarity by avoiding phosphate discharges may improve the protection of this emblematic species.Spanish Ministry of Economy and Competitiveness [CTM2014-57949-R]info:eu-repo/semantics/publishedVersio

Environmental variability in aquatic ecosystems: avenues for future multifactorial experiments

The relevance of considering environmental variability for understanding and predicting biological responses to environmental changes has resulted in a recent surge in variability-focused ecological research. However, integration of findings that emerge across studies and identification of remaining knowledge gaps in aquatic ecosystems remain critical. Here, we address these aspects by: (1) summarizing relevant terms of variability research including the components (characteristics) of variability and key interactions when considering multiple environmental factors; (2) identifying conceptual frameworks for understanding the consequences of environmental variability in single and multi-factorial scenarios; (3) highlighting challenges for bridging theoretical and experimental studies involving transitioning from simple to more complex scenarios; (4) proposing improved approaches to overcome current mismatches between theoretical predictions and experimental observations; and (5) providing a guide for designing integrated experiments across multiple scales, degrees of control, and complexity in light of their specific strengths and limitations

High unexpected genetic diversity of a narrow endemic terrestrial mollusc

The Iberian Peninsula has an extensive record of species displaying strong genetic structure as a result of their survival in isolated pockets throughout the Pleistocene ice ages. We used mitochondrial and nuclear sequence data to analyze phylogeographic patterns in endemic land snails from a valley of central Portugal (Vale da Couda), putatively assigned to Candidula coudensis, that show an exceptionally narrow distributional range. The genetic survey presented here shows the existence of five main mitochondrial lineages in Vale da Couda that do not cluster together suggesting independent evolutionary histories. Our results also indicate a departure from the expectation that species with restricted distributions have low genetic variability. The putative past and contemporary models of geographic distribution of Vale da Couda lineages are compatible with a scenario of species co-existence in more southern locations during the last glacial maximum (LGM) followed by a post-LGM northern dispersal tracking the species optimal thermal, humidity and soil physical conditionsinfo:eu-repo/semantics/publishedVersio

A utilização do ATLANTIS – Tierra 2.0 e de ferramentas SIG para predizer a distribuição espacial e a adequação do habitat de espécies endémicas

O conhecimento da distribuição de espécies raras requer muito esforço devido às dificuldades inerentes à detecção das suas populações. Neste capítulo, apresenta-se um exemplo de modelação da distribuição potencial de espécies endémicas de insectos, que constituem uma preocupação de conservação nos Açores. São analisados dados extraídos da base de dados ATLANTIS com o objectivo de desenvolver mapas preditivos da distribuição de quatro escaravelhos endémicos (Insecta, Coleoptera) na ilha Terceira: Cedrorum azoricus azoricus Borges & Serrano, 1993; Trechus terceiranus Machado, 1988; Trechus terrabravensis Borges, Serrano & Amorim, 2004; e Alestrus dolosus (Crotch, 1867). São usadas duas técnicas amplamente aplicadas nestas situações (BIOCLIM e BioMapper) de forma a desenvolver os mapas de distribuição, mas igualmente a obter a descrição do nicho ecológico de cada espécie. Todas as espécies, excepto T. terceiranus, apresentam grandes restrições de habitat. As outras três espécies parecem estar ambientalmente restringidas a duas áreas espaciais bem definidas, localizadas nas partes oeste (Serra de Santa Bárbara) e central (Terra Brava) da ilha Terceira. Contudo, enquanto A. dolosus estará potencialmente espalhado em ambas as áreas, de acordo com os seus requisitos de habitat, C. azoricus azoricus e T. terrabravensis parecem possuir adaptações ambientais muito mais restritivas. No entanto, como os dados sobre a distribuição conhecida destas espécies se revelaram escassos, a eficácia dos mapas de predição não é propriamente a ideal. Deste modo, é discutida de forma exaustiva a utilidade das técnicas utilizadas, num contexto de gestão da conservação. São igualmente discutidos os problemas surgidos durante o processo de modelação dos dados e como estes podem ser resolvidos. Finalmente são apresentadas sugestões para melhorar a informação a obter da base de dados ATLANTIS.ABSTRACT: Ranges of rare species require great efforts to be mapped due to the low detect ability of their populations. In this chapter, we provide an example focusing on several endemic insect species of conservation concern in the Azores. We explore the use of data extracted from ATLANTIS database to develop predictive maps of the distribution of four endemic beetle species (Insecta, Coleoptera) in Terceira Island: Cedrorum azoricus azoricus Borges & Serrano, 1993; Trechus terceiranus Machado, 1988; Trechus terrabravensis Borges, Serrano & Amorim, 2004; and Alestrus dolosus (Crotch, 1867). We use two widely used methodologies (BIOCLIM and BioMapper) to develop such maps, as well as to provide a description of the niche of these species. All species except for T. terceiranus presented highly restricted habitat requirements. The other three species seem to be environmentally restricted to two spatially well-defined areas, placed in the west (Serra de Santa Bárbara) and the centre of the island (Terra Brava). However, while A. dolosus seems to be potentially widespread in these two areas according to its habitat requirements, C. azoricus azoricus and T. terrabravensis appear to have very restricted environmental adaptations. As data (recorded presences) for these species is scarce, the performance of the predictions was not ideal. Therefore, we discuss extensively the utility of such methodologies in the context of conservation management. We also discuss how the problems arose during this work can be overcome, and how ATLANTIS information could be improved

Palaeoclimatic conditions in the Mediterranean explain genetic diversity of Posidonia oceanica seagrass meadows

Past environmental conditions in the Mediterranean Sea have been proposed as main drivers of the current patterns of distribution of genetic structure of the seagrass Posidonia oceanica, the foundation species of one of the most important ecosystems in the Mediterranean Sea. Yet, the location of cold climate refugia (persistence regions) for this species during the Last Glacial Maximum (LGM) is not clear, precluding the understanding of its biogeographical history. We used Ecological Niche Modelling together with existing phylogeographic data to locate Pleistocene refugia in the Mediterranean Sea and to develop a hypothetical past biogeographical distribution able to explain the genetic diversity presently found in P. oceanica meadows. To do that, we used an ensemble approach of six predictive algorithms and two Ocean General Circulation Models. The minimum SST in winter and the maximum SST in summer allowed us to hindcast the species range during the LGM. We found separate glacial refugia in each Mediterranean basin and in the Central region. Altogether, the results suggest that the Central region of the Mediterranean Sea was the most relevant cold climate refugium, supporting the hypothesis that long-term persistence there allowed the region to develop and retain its presently high proportion of the global genetic diversity of P. oceanica.Fundacao para a Ciencia e a Tecnologia (FCT, Portugal) [SFRH/BPD/85040/2012]; FCT [UID/Multi/04326/2013, FCT-BIODIVERSA/004/2015]; Pew foundation (USA)info:eu-repo/semantics/publishedVersio

A framework for species distribution modelling with improved pseudo-absence generation

Species distribution models (SDMs) are an important tool in biogeography and phylogeography studies, that most often require explicit absence information to adequately model the environmental space on which species can potentially inhabit. In the so called background pseudoabsences approach, absence locations are simulated in order to obtain a complete sample of the environment. Whilst the commonest approach is random sampling of the entire study region, in its multiple variants, its performance may not be optimal, and the method of generation of pseudoabsences is known to have a significant influence on the results obtained. Here, we compare a suite of classic (random sampling) and novel methods for pseudo-absence data generation and propose a generalizable three-step method combining environmental profiling with a new technique for background extent restriction. To this aim, we consider 11 phylogenetic groups of Oak (Quercus sp.) described in Europe. We evaluate the influence of different pseudo-absence types on model performance (area under the ROC curve), calibration (reliability diagrams) and the resulting suitability maps, using a cross-validation approach. Regardless of the modelling algorithm used, randomsampling models were outperformed by the methods that incorporate environmental profiling of the background, stressing the importance of the pseudo-absence generation techniques for the development of accurate and reliable SDMs. We also provide an integrated modelling framework implementing the methods tested in a software package for the open source R environment

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits.We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics.More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species.Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species.Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change

Evidence for rangewide panmixia despite multiple barriers to dispersal in a marine mussel

Oceanographic features shape the distributional and genetic patterns of marine species by interrupting or promoting connections among populations. Although general patterns commonly arise, distributional ranges and genetic structure are species-specific and do not always comply with the expected trends. By applying a multimarker genetic approach combined with Lagrangian particle simulations (LPS) we tested the hypothesis that oceanographic features along northeastern Atlantic and Mediterranean shores influence dispersal potential and genetic structure of the intertidal mussel Perna perna. Additionally, by performing environmental niche modelling we assessed the potential and realized niche of P. perna along its entire native distributional range and the environmental factors that best explain its realized distribution. Perna perna showed evidence of panmixia across > 4,000 km despite several oceanographic breaking points detected by LPS. This is probably the result of a combination of life history traits, continuous habitat availability and stepping-stone dynamics. Moreover, the niche modelling framework depicted minimum sea surface temperatures (SST) as the major factor shaping P. perna distributional range limits along its native areas. Forthcoming warming SST is expected to further change these limits and allow the species to expand its range polewards though this may be accompanied by retreat from warmer areas.Fundacao para a Ciencia e Tecnologia (FCT-MEC, Portugal) [UID/Multi/04326/2013, IF/01413/2014/CP1217/CT0004]; South African Research Chairs Initiative (SARChI) of the Department of Science and Technology; National Research Foundation; South African National Research Foundation (NRF); Portuguese Fundacao para a Ciencia e Tecnologia (FCT) [SFRH/BPD/85040/2012, SFRH/BPD/111003/2015]info:eu-repo/semantics/publishedVersio

Chapter 4. In search of relevant predictors for marine species distribution modelling using the MarineSPEED benchmark dataset

Aim: Ideally, datasets for species distribution modelling (SDM) contain evenly sampled records covering the entire distribution of the species, confirmed absences and auxiliary ecophysiological data allowing informed decisions on relevant predictors. Unfortunately, these criteria are rarely met for marine organisms for which distributions are too often only scantly characterized and absences generally not recorded. Here, we investigate predictor relevance as a function of modelling algorithms and settings for a global dataset of marine species.Location: Global marine.Methods: We selected well-studied and identifiable species from all major marine taxonomic groups. Distribution records were compiled from public sources (e.g., OBIS, GBIF, Reef Life Survey) and linked to environmental data from Bio-ORACLE and MARSPEC. Using this dataset, predictor relevance was analysed under different variations of modelling algorithms, numbers of predictor variables, cross-validation strategies, sampling bias mitigation methods, evaluation methods and ranking methods. SDMs for all combinations of predictors from eight correlation groups were fitted and ranked, from which the top five predictors were selected as the most relevant. Results: We collected two million distribution records from 514 species across 18 phyla. Mean sea surface temperature and calcite are, respectively, the most relevant and irrelevant predictors. A less clear pattern was derived from the other predictors. The biggest differences in predictor relevance were induced by varying the number of predictors, the modelling algorithm and the sample selection bias correction. The distribution data and associated environmental data are made available through the R package marinespeed and at http://marinespeed.org.Main conclusions: While temperature is a relevant predictor of global marine species distributions, considerable variation in predictor relevance is linked to the SDM set-up. We promote the usage of a standardized benchmark dataset (MarineSPEED) for methodological SDM studies