Despite large efforts, datasets with few sightings are often available for rare species of marine megafauna that typically live at low densities. This paucity of data makes modelling the habitat of ...these taxa particularly challenging. We tested the predictive performance of different types of species distribution models fitted to decreasing numbers of sightings. Generalised additive models (GAMs) with three different residual distributions and the presence only model MaxEnt were tested on two megafauna case studies differing in both the number of sightings and ecological niches. From a dolphin (277 sightings) and an auk (1,455 sightings) datasets, we simulated rarity with a sighting thinning protocol by random sampling (without replacement) of a decreasing fraction of sightings. Better prediction of the distribution of a rarely sighted species occupying a narrow habitat (auk dataset) was expected compared to the distribution of a rarely sighted species occupying a broad habitat (dolphin dataset). We used the original datasets to set up a baseline model and fitted additional models on fewer sightings but keeping effort constant. Model predictive performance was assessed with mean squared error and area under the curve. Predictions provided by the models fitted to the thinned-out datasets were better than a homogeneous spatial distribution down to a threshold of approximately 30 sightings for a GAM with a Tweedie distribution and approximately 130 sightings for the other models. Thinning the sighting data for the taxon with narrower habitats seemed to be less detrimental to model predictive performance than for the broader habitat taxon. To generate reliable habitat modelling predictions for rarely sighted marine predators, our results suggest (1) using GAMs with a Tweedie distribution with presence-absence data and (2) implementing, as a conservative empirical measure, at least 50 sightings in the models.
•Importance of selecting appropriate models for rare species habitat predictions.•Presence-absence models made better predictions than the presence-only model.•GAMs with a Negative Binomial and ...Tweedie distributions better predict the habitats.•Zero-inflated Poisson distributions exhibited less convincing results.•92% zeros in the dataset does not necessarily mean zero-inflation.
When performing habitat models, modellers have to choose between presence-absence and presence-only models to estimate the habitat preferences of a species. Primarily, this choice depends on the data that are available and whether effort data are recorded in parallel to sighting data. For species that are rare or scarce, the models have to address a great number of zeros (i.e., no animal seen) that weakens the ability to make sound ecological inferences. We tested two types of habitat models (presence-absence vs. presence-only) to determine which type best dealt with datasets containing an excess of zeros, and we applied our models to a sighting dataset that included the common (Delphinus delphis) and striped (Stenella coeruleoalba) dolphin (approximately 92% zeros). We used two types of presence-absence models (Generalised Additive models – GAMs, Generalised Linear Model – GLM) and one presence-only model, a MaxEnt model, and we used various criteria to compare these models (i.e., AIC, deviances, rootograms and distribution patterns predicted by the models). Overall, we observed that the presence-absence models made better predictions than the presence-only model. Among the presence-absence models, the GAM with a Negative Binomial distribution was better at predicting small delphinids habitats, even though the GAM with a Tweedie distribution exhibited similar results. However, the zero-inflated Poisson distributions exhibited less convincing results and was contrary to what was expected. Finally, despite 92% zeros, our dataset was not zero-inflated. Our study demonstrates the importance of selecting appropriate models to make reliable predictions of habitat use for species that are rare or scarce.
The use of naturalist mobile applications have dramatically increased during last years, and provide huge amounts of accurately geolocated species presences records. Integrating this novel type of ...data in species distribution models (SDMs) raises specific methodological questions. Presence-only SDM methods require background points, which should be consistent with sampling effort across the environmental space to avoid bias. A standard approach is to use uniformly distributed background points (UB). When multiple species are sampled, another approach is to use a set of occurrences from a Target-Group of species as background points (TGOB). We here investigate estimation biases when applying TGOB and UB to opportunistic naturalist occurrences. We modelled species occurrences and observation process as a thinned Poisson point process, and express asymptotic likelihoods of UB and TGOB as a divergence between environmental densities, in order to characterize biases in species niche estimation. To illustrate our results, we simulated species occurrences with different types of niche (specialist/generalist, typical/marginal), sampling effort and TG species density. We conclude that none of the methods are immune to estimation bias, although the pitfalls are different: For UB, the niche estimate fits tends towards the product of niche and sampling densities. TGOB is unaffected by heterogeneous sampling effort, and even unbiased if the cumulated density of the TG species is constant. If it is concentrated, the estimate deviates from the range of TG density. The user must select the group of species to ensure that they are jointly abundant over the broadest environmental sub-area.
Predicting how climatic variations will affect marine predator populations relies on our ability to assess foraging success, but evaluating foraging success in a marine predator at sea is ...particularly difficult. Dive metrics are commonly available for marine mammals, diving birds and some species of fish. Bottom duration or dive duration are usually used as proxies for foraging success. However, few studies have tried to validate these assumptions and identify the set of behavioral variables that best predict foraging success at a given time scale. The objective of this study was to assess if foraging success in Antarctic fur seals could be accurately predicted from dive parameters only, at different temporal scales. For this study, 11 individuals were equipped with either Hall sensors or accelerometers to record dive profiles and detect mouth-opening events, which were considered prey capture attempts. The number of prey capture attempts was best predicted by descent and ascent rates at the dive scale; bottom duration and descent rates at 30-min, 1-h, and 2-h scales; and ascent rates and maximum dive depths at the all-night scale. Model performances increased with temporal scales, but rank and sign of the factors varied according to the time scale considered, suggesting that behavioral adjustment in response to prey distribution could occur at certain scales only. The models predicted the foraging intensity of new individuals with good accuracy despite high inter-individual differences. Dive metrics that predict foraging success depend on the species and the scale considered, as verified by the literature and this study. The methodology used in our study is easy to implement, enables an assessment of model performance, and could be applied to any other marine predator.
The limited availability of soil information has been recognized as a main limiting factor in digital soil mapping (DSM) studies. It is therefore important to optimize the joint use of the three ...sources of soil data that can be used as inputs of DSM models, namely spatial sets of measured sites, soil maps and soil sensing products.
In this paper, we propose to combine these three inputs, through a cokriging with a categorical external drift (CKCED). This new interpolation technique was applied for mapping seven soil properties over a 24.6km2 area located in the vineyard plain of Languedoc (Southern France), using an hyperspectral imagery product as example of a soil sensing data. Cross-validation results of CKCED were compared with those of five spatial and non-spatial techniques using one of these inputs or a combination of two of them.
The results obtained in the La Peyne Catchment showed i) the utility of soil map and hyperspectral imagery products as auxiliary data for improving soil property predictions ii) the greater added-value of the latter against the former in most situations and iii) the feasibility and the interest of CKCED in a limited number of soil properties and data configurations. Testing CKCED in case study with soil maps of better quality and soil sensing techniques covering more area and depths should be necessary to better evaluate the benefits of this new technique.
•Measured sites, soil maps and soil sensing products are the 3 possible inputs for DSM.•We propose a new interpolation technique (CKCED) for combining these inputs.•Tested against methods combining less inputs for mapping 7 soil properties•CKCED improved predictions for some soil properties and data configurations.•Should be tested with more precise soil maps and more extended soil sensing products
Top predators need to develop optimal strategies of resources and habitats utilization in order to optimize their foraging success. At the individual scale, a predator has to maximize his intake of ...food while minimizing his cost of foraging to optimize his energetic gain. At the ecosystem scale, we hypothesized that foraging strategies of predators also respond to their general energetic constraints. Predators with energetically costly lifestyles may be constrained to select high quality habitats whereas more phlegmatic predators may occupy both low and high quality habitats. The objectives of this study were 1) to investigate predator responses to heterogeneity in habitat quality with reference to their energetic strategies and 2) to evaluate their responses to contemporaneous versus averaged habitat quality. We collected cetacean and seabird data from an aerial survey in the Southwest Indian Ocean, a region characterized by heterogeneous oceanographic conditions. We classified cetaceans and seabirds into energetic guilds and described their habitats using remotely sensed covariates at contemporaneous and time-averaged resolutions and static covariates. We used generalized additive models to predict their habitats at the regional scale. Strategies of habitat utilization appeared in accordance with predators energetic constraints. Cetaceans responded to the heterogeneity in habitat quality, with higher densities predicted in more productive areas. However, the costly Delphininae appeared to be more dependent on habitat quality (showing a 1-to-13 ratio between the lowest and highest density sectors) than the more phlegmatic sperm and beaked whales (showing only a 1-to-3 ratio). For seabirds, predictions primarily reflected colony locations, although the colony effect was stronger for costly seabirds. Moreover, our results suggest that predators may respond better to persistent oceanographic features. To provide a third dimension to habitat quality, cetacean strategies of utilization of the vertical habitat could be related to the distribution of micronekton in the water column.
The biodiversity of the Mediterranean Sea is undergoing important changes. Cetaceans, as top predators, are an important component of marine ecosystems. The seasonal distribution and abundance of ...several cetacean species were studied with a large aerial survey over the North-Western Mediterranean Sea, including the international Pelagos sanctuary, the largest Marine Protected Area (MPA) designed for marine mammals in the Mediterranean. A total of 8 distinct species of cetaceans were identified, and their occurrence within the sanctuary was investigated. Abundance estimates were obtained for three groups of species: the small delphinids (striped dolphins mainly), the bottlenose dolphin and the fin whale. There was a seasonal variation in striped dolphin abundance between winter (57,300 individuals, 95% CI: 34,500–102,000) and summer (130,000, 95% CI: 76,800–222,100). In contrast, bottlenose dolphin winter abundance was thrice that of summer. It was also the only species to exhibit any preference for the Pelagos sanctuary. Fin whale abundance had the reverse pattern with winter abundance (1000 individuals, 95% CI: 500–2500) and summer (2500 individuals, 95% CI: 1500–4300), without any preference for the sanctuary. Risso's dolphins, pilot whales and sperm whales did not exhibit strong seasonal pattern in their abundance. These results provide baseline estimates which can be used to inform conservation policies and instruments such as the Habitats Directive or the recent European Marine Strategy Framework Directive.
Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial ...representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2‐D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within the context of stream ecology. Within this context, we summarise the key innovations of a new family of spatial statistical models that describe spatial relationships in DENs. Finally, we discuss how different network analyses may be combined to address more complex and novel research questions. While our main focus is streams, the taxonomy of network analyses is also relevant anywhere spatial patterns in both network and 2‐D space can be used to explore the influence of multi‐scale processes on biota and their habitat (e.g. plant morphology and pest infestation, or preferential migration along stream or road corridors).
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Premise of the Study
A species distribution model computed with automatically identified plant observations was developed and evaluated to contribute to future ecological studies.
Methods
We used ...deep learning techniques to automatically identify opportunistic plant observations made by citizens through a popular mobile application. We compared species distribution modeling of invasive alien plants based on these data to inventories made by experts.
Results
The trained models have a reasonable predictive effectiveness for some species, but they are biased by the massive presence of cultivated specimens.
Discussion
The method proposed here allows for fine‐grained and regular monitoring of some species of interest based on opportunistic observations. More in‐depth investigation of the typology of the observations and the sampling bias should help improve the approach in the future.
Seabird distributions and the associated seasonal variations remain challenging to investigate, especially in oceanic areas. Recent advances in telemetry have provided considerable information on ...seabird ecology, but still exclude small species, non-breeding birds and individuals from inaccessible colonies from any scientific survey. To overcome this issue and investigate seabird distribution and abundance in the eastern North Atlantic (ENA), large-scale aerial surveys were conducted in winter 2011-12 and summer 2012 over a 375,000km2 area encompassing the English Channel (EC) and the Bay of Biscay (BoB). Seabird sightings, from 15 taxonomic groups, added up to 17,506 and 8263 sightings in winter and summer respectively, along 66,307km. Using geostatistical methods, density maps were provided for both seasons. Abundance was estimated by strip transect sampling. Most taxa showed marked seasonal variations in their density and distribution. The highest densities were recorded during winter for most groups except shearwaters, storm-petrels, terns and large-sized gulls. Subsequently, the abundance in winter nearly reached one million individuals and was 2.5 times larger than in summer. The continental shelf and the slope in the BoB and the EC were identified as key areas for seabird conservation, especially during winter, as birds from northern Europe migrate southward after breeding. This large-scale study provided a synoptic view of the seabird community in the ENA, over two contrasting seasons. Our results highlight that oceanic areas harbour an abundant avifauna. Since most of the existing marine protected areas are restricted to the coastal fringe, the importance of oceanic areas in winter should be considered in future conservation plans. Our work will provide a baseline for the monitoring of seabird distribution at sea, and could inform the EU Marine Strategy Framework Directive.
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