Distribution and abundance of bottlenose dolphin ( Tursiops truncatus ) over the French Mediterranean continental shelf

Labach²,

Authier

et al. 2019

Preprint

Self Cite

24 1. A major challenge in applied ecology consists in integrating knowledge from 25 different datasets to produce robust ecological indicators. To estimate species distribution, 26 occupancy models are a flexible framework that can accommodate several datasets obtained 27 from different sampling methods. However, repeating visits at sampling sites is a prerequisite 28 for using standard occupancy models, which may limit their use. Under certain conditions, 29 detection/non-detection data collected during single visit can be analysed with occupancy 30 models. To date however, single-visit occupancy models have never been used to combine 31 several different datasets. 32 2. Here, we developed an approach that combines multi-method and single-visit 33 occupancy models. As a case study, we estimated the distribution of Bottlenose dolphins 34 (Tursiops truncatus) over the North-western Mediterranean Sea by combining 24,624 km of 35 aerial surveys and 21,464 km of at-sea monitoring. We compared the outputs of single-vs. 36 repeated-visit multi-method occupancy models, and that of single-method occupancy models. 37 3. Multi-method models allowed a better sampling coverage in both coasts and high 38 seas and provided a better precision for occupancy estimates than single-method occupancy 39 models using aerial surveys or at-sea surveys in isolation. 40 4. Overall, single-and repeated-visit multi-method occupancy models produced 41 similar inference about the distribution of bottlenose dolphins. This suggests that single-visit 42 occupancy models provide robust occupancy estimates, which open promising perspectives 43 for the use of non-standardized datasets. 44 5. Synthesis and applications: Single-visit multi-method occupancy models can help 45 making the best out of ecological monitoring programs by optimizing cost effectiveness 46 through the formal combination of datasets. 47 48 Keywords 49 Bottlenose dolphins, Ecological monitoring, Integrated species distribution models, Multi-50 method, Occupancy models, Single-visit 51 52 SuppInfo_Lauret_et_al.html 595

Section: Integrated Single-visit Occupancy Models Provide Reliable Ecmentioning

confidence: 76%

Section: Bottlenose Dolphins Case Studymentioning

confidence: 99%

Using single visits into integrated occupancy models to make the most of existing monitoring programs

Labach²,

Authier

et al. 2019

Preprint

Self Cite

“…We divided the duration of the monitoring programs into 8 equal sampling occasions as in Labach et al (2019). We also used DS data that were collected during winter and summer aerial We divided the study area in 4356 contiguous pixel/sites creating a 5'x5' Mardsen grid (WGS 84).…”

Section: Bottlenose Dolphins Case Studymentioning

confidence: 99%

“…We also used DS data that were collected during winter and summer aerial We divided the study area in 4356 contiguous pixel/sites creating a 5'x5' Mardsen grid (WGS 84). To model spatial variation in the inhomogeneous point process, we used bathymetry as an environmental covariate, which is expected to have a positive effect on bottlenose dolphins' occurrence (Bearzi et al 2009;Labach et al 2019). To estimate the sampling effort of aerial and boat surveys, we calculated the transect length (in km) prospected by each monitoring protocol within each site during a time period.…”

Section: Bottlenose Dolphins Case Studymentioning

confidence: 99%

“…We analyzed DS data collected by aerial line-transect surveys over a large area covering coastal and pelagic seas (Laran et al 2017). We also analyzed SCR data collected by a photo-identification monitoring program restricted to coastal waters (Labach et al 2019). We compared the abundance and density of bottlenose dolphins estimated from DS model, SCR model, and SIM to highlight the benefits of the integrated approach in a conservation context.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrated spatial models foster complementarity between monitoring programs in producing large-scale bottlenose dolphin indicators

Labach

Turek

et al. 2021

Preprint

Self Cite

Over the last decades, large-scale conservation projects have emerged that require collecting ecological data over broad spatial and temporal coverage. Yet, obtaining relevant information about large-scale population dynamics from a single monitoring program is challenging, and often several sources of data, possibly heterogeneous, need to be integrated. In this context, spatial integrated models combine multiple data types into a single analysis to quantify population dynamics of a targeted population. Using available information at different spatial or temporal scales, spatial integrated models have the potential to produce detailed ecological estimates that would be difficult to obtain if data were analyzed separately. So far, these models are available for open populations to estimate demographic parameters (survival, recruitment), therefore requiring data collected in long-term monitoring programs. In conservation biology however, we often need to quantify population abundance and density in closed populations. In this paper, we showcase the implementation of spatial integrated models to closed populations in a conservation context. We analyzed spatial capture-recapture data together with distance-sampling data to estimate abundance and density. Focusing on the Mediterranean bottlenose dolphins (Tursiops truncatus) as a case study, we combined 21,464 km of photo-identification boat surveys collecting spatial capture-recapture data with 24,624 km of aerial line-transect following a distance-sampling protocol. We compared the performances of the spatial integrated model, with that of the distance sampling model, and the spatial capture-recapture model separated. We discussed the benefits of using a spatial integrated model in the context of the assessment of French Mediterranean bottlenose dolphin conservation status to inform continental scale public policies. Overall, we emphasize the usefulness of spatial integrated model to make the most of available datasets in a conservation context. Spatial integrated models are widely applicable and relevant to conservation research and biodiversity assessment at large spatial scales.

Using single visits into integrated occupancy models to make the most of existing monitoring programs

Labach

Authier

et al. 2021

Ecology

Self Cite

A major challenge in statistical ecology consists of integrating knowledge from different data sets to produce robust ecological indicators. To estimate species distribution, occupancy models are a flexible framework that can accommodate several data sets obtained from different sampling methods. However, repeating visits at sampling sites is a prerequisite for using standard occupancy models. Occupancy models were recently developed to analyze detection/ non-detection data collected during a single visit. To date, single-visit occupancy models have never been used to integrate several different data sets. Here, we showcase an approach that combines two data sets into an integrated single-visit occupancy model. As a case study, we estimated the distribution of common bottlenose dolphin (Tursiops truncatus) over the northwestern Mediterranean Sea by combining 24,624 km of aerial surveys and 21,464 km of at-sea monitoring. We compared the outputs of single-vs. repeated-visit occupancy models into integrated occupancy models. Integrated models allowed a better sampling coverage of the targeted population, which provided a better precision for occupancy estimates than occupancy models using data sets in isolation. Overall, single-and repeated-visit integrated occupancy models produced similar inference about the distribution of bottlenose dolphins. We suggest that single-visit occupancy models open promising perspectives for the use of existing ecological data sets.