Geographic range determinants of two commercially important marine molluscs

Aim We modelled the spatial abundance patterns of two abalone species (Haliotis rubra Donovan 1808 and H. laevigata Leach 1814) inhabiting inshore rocky reefs to better understand the importance of current sea surface temperature (SST) (among other predictors) and, ultimately, the effect of future climate change, on marine molluscs. Location Southern Australia. Methods We used an ensemble species distribution modelling approach that combined likelihood‐based generalized linear models and boosted regression trees. For each modelling technique, a two‐step procedure was used to predict: (1) the current probability of presence, followed by (2) current abundance conditional on presence. The resulting models were validated using an independent, spatially explicit dataset of abalone abundance patterns in Victoria. Results For both species, the presence of reef was the main driver of abalone occurrence, while SST was the main driver of spatial abundance patterns. Predictive maps at c. 1‐km resolution showed maximal abundance on shallow coastal reefs characterized by mild winter SSTs for both species. Main conclusions Sea surface temperature was a major driver of abundance patterns for both abalone species, and the resulting ensemble models were used to build fine‐resolution predictive range maps (c. 1 km) that incorporate measures of habitat suitability and quality in support of resource management. By integrating this output with structured spatial population models, a more robust understanding of the potential impacts of threatening human processes such as climate change can be established.     

Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales

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Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence‐only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km²) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest.     

Floristic patterns of epiphytes in the Brazilian Atlantic Forest,a biodiversity hotspot

To assess the main factors driving epiphytic angiosperm distribution throughout the Brazilian Atlantic Forest, we compiled 57 floristic surveys and analysed species composition under the influence of environmental variables, space and vegetation type using canonical correspondence analysis (CCA), similarity (Sorensen) and Mantel's tests. The indicator value index (IndVal) was used to find indicator species of each Brazilian Atlantic Forest vegetation type. Group sharpness analysis was performed in order to determine the appropriate group partition level. CCA showed a separation of the epiphytic flora reflecting temperature and rainfall gradients. Mantel's test showed that environment and space were highly correlated with floristic similarity. Cluster analysis, indicating floristic similarity, resolved five groups, mainly grouped by region. Clear differentiation of the Brazilian Atlantic Forest epiphytic flora on a north–south axis with a strong correlation with temperature and rainfall gradients was found. The role of space and environment on species composition varied according to distinct epiphytic species groups. In particular, for Bromeliaceae and Orchidaceae, the main factor associated with floristic similarity was space. Indicator species were found for all vegetation types apart from the Seasonal Semideciduous Forest that seemed to represent a subset of a more humid forest type. © 2015 The Linnean Society of London, Botanical Journal of the Linnean Society, 2015, 179 , 587–601.     

Non-additive and non-stationary properties in the spatial distribution of a large marine fish population

Density-independent and density-dependent variables both affect the spatial distributions of species. However, their effects are often separately addressed using different analytical techniques. We apply a spatially explicit regression framework that incorporates localized, interactive and threshold effects of both density-independent (water temperature) and density-dependent (population abundance) variables, to study the spatial distribution of a well-monitored flatfish population in the eastern Bering Sea. Results indicate that when population biomass was beyond a threshold a further increase in biomass-promoted habitat expansion in a non-additive fashion with water temperature. In contrast, during years of low population size, habitat occupancy was affected positively only by water temperature. These results reveal the spatial signature of intraspecific abundance distribution relationships as well as the non-additive and non-stationary responses of species spatial dynamics. Furthermore, these results underscore the importance of implementing analytical techniques that can simultaneously account for density-dependent and density-independent sources of variability when studying geographical distribution patterns.     

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.

     

Stomach temperature telemetry reveals temporal patterns of foraging success in a free-ranging marine mammal

1. We studied feeding frequency in free-ranging grey seals using stomach temperature telemetry to test if previously reported sex differences in the diving, movement and diet were reflected in the temporal pattern of foraging success. 2. Data were retrieved from 21 of 32 grey seals from 1999 to 2001, totalling 343 days and 555 feeding events, with individual record length varying from 2 to 40 days (mean: 16.33 +/- 2.67 days/seal). 3. Seals fed on 57.8 +/- 6.46% of days sampled and had an average of 1.7 +/- 0.26 meals per day, but individual variability was apparent in the temporal distribution of feeding as evidenced by high coefficients of variation (coefficient of variation = 69.0%). 4. Bout analysis of non-feeding intervals of six grey seals suggests that feeding intervals of individuals were varied and probably reflect differences in prey availability. Grey seals tended to have many single feeding events with long periods separating each event, as would be expected for a large carnivore with a batch-reactor digestive system. 5. We found significant sex differences in the temporal distribution of feeding. The number of feeding events per day was greater in males (2.2 +/- 0.4 vs. 1.0 +/- 0.2), as was time associated with feeding per day (56.6 +/- 5.8 min vs. 43.9 +/- 9.4 min). 6. The number of feeding events varied with time of day with the least number occurring during dawn. Feeding event size differed significantly by time of day, with greater meal sizes during the dawn and the smallest meals during the night. 7. The length of time between meals increased with the size of the previous meal, and was significantly less in males (541.4 +/- 63.5 min) than in females (1092.6 +/- 169.9 min). 8. These results provide new insight into the basis of sex differences in diving and diet in this large size-dimorphic marine predator.     

Climate change alters stability and species potential interactions in a large marine ecosystem

We have little empirical evidence of how large‐scale overlaps between large numbers of marine species may have altered in response to human impacts. Here, we synthesized all available distribution data (>1 million records) since 1992 for 61 species of the East Australian marine ecosystem, a global hot spot of ocean warming and continuing fisheries exploitation. Using a novel approach, we constructed networks of the annual changes in geographical overlaps between species. Using indices of changes in species overlap, we quantified changes in the ecosystem stability, species robustness, species sensitivity and structural keystone species. We then compared the species overlap indices with environmental and fisheries data to identify potential factors leading to the changes in distributional overlaps between species. We found that the structure of the ecosystem has changed with a decrease in asymmetrical geographical overlaps between species. This suggests that the ecosystem has become less stable and potentially more susceptible to environmental perturbations. Most species have shown a decrease in overlaps with other species. The greatest decrease in species overlap robustness and sensitivity to the loss of other species has occurred in the pelagic community. Some demersal species have become more robust and less sensitive. Pelagic structural keystone species, predominately the tunas and billfish, have been replaced by demersal fish species. The changes in species overlap were strongly correlated with regional oceanographic changes, in particular increasing ocean warming and the southward transport of warmer and saltier water with the East Australian Current, but less correlated with fisheries catch. Our study illustrates how large‐scale multispecies distribution changes can help identify structural changes in marine ecosystems associated with climate change.     

Trade-offs in covariate selection for species distribution models: a methodological comparison

Species distribution models (SDMs) are a common approach to describing species’ space-use and spatially-explicit abundance. With a myriad of model types, methods and parameterization options available, it is challenging to make informed decisions about how to build robust SDMs appropriate for a given purpose. One key component of SDM development is the appropriate parameterization of covariates, such as the inclusion of covariates that reflect underlying processes (e.g. abiotic and biotic covariates) and covariates that act as proxies for unobserved processes (e.g. space and time covariates). It is unclear how different SDMs apportion variance among a suite of covariates, and how parameterization decisions influence model accuracy and performance. To examine trade-offs in covariation parameterization in SDMs, we explore the attribution of spatiotemporal and environmental variation across a suite of SDMs. We first used simulated species distributions with known environmental preferences to compare three types of SDM: a machine learning model (boosted regression tree), a semi-parametric model (generalized additive model) and a spatiotemporal mixed-effects model (vector autoregressive spatiotemporal model, VAST). We then applied the same comparative framework to a case study with three fish species (arrowtooth flounder, pacific cod and walleye pollock) in the eastern Bering Sea, USA. Model type and covariate parameterization both had significant effects on model accuracy and performance. We found that including either spatiotemporal or environmental covariates typically reproduced patterns of species distribution and abundance across the three models tested, but model accuracy and performance was maximized when including both spatiotemporal and environmental covariates in the same model framework. Our results reveal trade-offs in the current generation of SDM tools between accurately estimating species abundance, accurately estimating spatial patterns, and accurately quantifying underlying species–environment relationships. These comparisons between model types and parameterization options can help SDM users better understand sources of model bias and estimate error.     

Influence of patch size and connectivity on beach and dune species in land-uplift coasts

Background: Land-uplift beaches and adjacent dunes contribute considerably to natural diversity. In such fragmented habitat types, the size and connectivity of a habitat patch are hypothesised to strongly influence the distribution of species, particularly the most habitat-specific ones.

Aims: To test this hypothesis, our study compared the effects of habitat pattern (patch size and connectivity) and local environmental factors on the distribution and richness of beach species.

Methods: We collected extensive observational data on vegetation and environment from beach systems along a 600-km land-uplift gradient on the Baltic Sea coast. The analyses were repeated with three modelling methods to ensure that the results were independent of the selected method.

Results and conclusions: Our results indicate that patch size and connectivity influence the occurrence and richness of habitat specialists, while total beach species richness is less dependent on the habitat pattern. Patch size and connectivity are as influential on beach vegetation as local environmental drivers. Unexpectedly, largest patch size or highest connectivity does not appear to maximise species richness or the probability of species occurrence. Instead, the study highlights species-specific responses and the value of also relatively small and isolated habitat patches. Both the diverse network of habitat patches and local environmental variability should be accounted for to efficiently preserve beach species.     

Abundance and spatial distribution of aphids and scales select for different life histories in their ladybird beetle predators

Abstract:  Life history parameters tend to differ between aphidophagous and coccidophagous ladybird beetles. It seems that the nature of prey, in particular the abundance, number and size of the colonies and their spatial distribution, may have been selected for the evolution of the life histories in these two groups of coccinellids, leading the aphidophagous ladybird beetles to develop at a fast pace and the coccidophagous beetles at a slower pace. To study the abundance, number and size of the colonies and the spatial distribution of aphid and coccid species, 100 sampling plots regularly spaced along four parallel transects were surveyed in the summer of 2004. At each sampling plot, species abundance, and the number and size of colonies of aphid and coccid species were recorded. Iwao's patchiness regression was used to assess the spatial distribution of aphids and coccids. From this study, it was found that coccids are much rarer than aphids but formed more colonies. Whereas aphids display a stonger tendency to crowding, aphid colonies are randomly distributed in space while coccid groups are aggregated. So, it seems that the abundance and spatial distribution of prey distribution may be factors selecting for the evolution of different life histories among aphidophagous and coccidophagous ladybird beetles.     

Modelled spatial distribution of marine fish and projected modifications in the North Atlantic Ocean

The objectives of this work were to examine the past, current and potential influence of global climate change on the spatial distribution of some commercially exploited fish and to evaluate a recently proposed new ecological niche model (ENM) called nonparametric probabilistic ecological niche model (NPPEN). This new technique is based on a modified version of the test called Multiple Response Permutation Procedure (MRPP) using the generalized Mahalanobis distance. The technique was applied in the extratropical regions of the North Atlantic Ocean on eight commercially exploited fish species using three environmental parameters (sea surface temperature, bathymetry and sea surface salinity). The numerical procedure and the model allowed a better characterization of the niche (sensu Hutchinson) and an improved modelling of the spatial distribution of the species. Furthermore, the technique appeared to be robust to incomplete or bimodal training sets. Despite some potential limitations related to the choice of the climatic scenarios (A2 and B2), the type of physical model (ECHAM 4) and the absence of consideration of biotic interactions, modelled changes in species distribution explained some current observed shifts in dominance that occurred in the North Atlantic sector, and particularly in the North Sea. Although projected changes suggest a poleward movement of species, our results indicate that some species may not be able to track their climatic envelope and that climate change may have a prominent influence on fish distribution during this century. The phenomenon is likely to trigger locally major changes in the dominance of species with likely implications for socio‐economical systems. In this way, ENMs might provide a new management tool against which changes in the resource might be better anticipated.     

Plant biodiversity patterns along a climatic gradient and across protected areas in West Africa

Knowledge of spatial patterns of biological diversity is fundamental for ecological and biogeographical analyses and for priority setting in nature conservation, particularly in West Africa where the existing high biodiversity is increasingly threatened by human activities. The maximum entropy approach was used to model the geographic distribution of 3,393 vascular plant species at a spatial resolution of 0.0833°. Species richness decreases along temperature and precipitation gradients with high species numbers in the south and lower numbers towards the north of the transect. All centres of plant species diversity are confined to humid areas in concordance with the high positive correlation between species richness and rainfall which appears to be the most important delimiter for the distribution ranges of many species in the area. The effectiveness of the existing protected areas at regional and national levels is investigated based on the proportion of species covered. Considering the whole study area, 95% of all species are covered by protected areas according to their distribution ranges. However, the proportion of species covered is considerably lower for some countries such as Benin and Togo. Our results could provide guidance for essential land use management interventions to decision‐makers and conservationists in the region.