Density Surface Models Research Articles

A new insight for monitoring ungulates: density surface modelling of roe deer in a Mediterranean habitat

Ungulates are especially difficult to monitor, and population estimates are challenging to obtain; nevertheless, such information is fundamental for effective management. This is particularly important for expanding species such as roe deer (Capreolus capreolus), whose populations dramatically increased in number and geographic distribution over the last decades. In an attempt to follow population trends and assess species ecology, important methodological advances were recently achieved by combining line or point sampling with geographic information systems (GIS). In this study, we combined density surface modelling (DSM) with line transect survey to predict roe deer density in northeastern Portugal. This was based on modelling pellet group counts as a function of environmental factors while taking into account the probability of detecting pellets and conversion factors to relate pellet density to animal density. We estimated a global density of 3.01 animals/100 ha (95 % CI 0.37–3.51) with a 32.82 % CV. Roe deer densities increased with increasing distance to roads as well as with higher percentage of cover areas and decreased with increasing distance to human populations. This recently developed spatial method can be advantageous to predict density over space through the identification of key factors influencing species abundance. Furthermore, surface maps for subset areas will enable to visually depict abundance distribution of wild populations. This will enable the assessment of areas where ungulate impacts should be minimized, allowing an adaptive management through time.

Spatial patterns of distribution, abundance, and species diversity of small odontocetes estimated using density surface modeling with line transect sampling

Spatial patterns of distribution, abundance, and species diversity of small odontocetes including species in the Delphinidae and Phocoenidae families were investigated using long-term dedicated sighting survey data collected between 1983 and 2006 in the North Pacific. Species diversity indices were calculated from abundance estimated using density surface modeling of line-transect data. The estimated abundance ranged from 19,521 individuals in killer whale to 1,886,022 in pantropical spotted dolphin. The predicted density maps showed that the habitats of small odontocetes corresponded well with distinct oceanic domains. Species richness was estimated to be highest between 30 and 40°N where warm- and cold-water currents converge. Simpson׳s Diversity Index showed latitudinal diversity gradients of decreasing species numbers toward the poles. Higher diversity was also estimated in the coastal areas and the zonal areas around 35–42°N. Coastal–offshore gradients and latitudinal gradients are known for many taxa. The zonal areas around 35°N and 40°N coincide with the Kuroshio Current and its extension and the subarctic boundary, respectively. These results suggest that the species diversity of small odontocetes primarily follows general patterns of latitudinal and longitudinal gradients, while the confluence of faunas originating in distinct water masses increases species diversify in frontal waters around 30–40°N. Population densities tended to be higher for the species inhabiting higher latitudes, but were highest for intermediate latitudes at approximately 35–40°N. According to latitudinal gradients in water temperature and biological productivity, the costs for thermoregulation will decrease in warmer low latitudes, while feeding efficiency will increase in colder high latitudes. These trade-offs could optimize population density in intermediate latitudes.

Abundance estimates for the endangered Green PeafowlPavo muticusin Cambodia: identification of a globally important site for conservation

SummaryThe catastrophic decline of the endangered Green peafowlPavo muticusacross its former range is well known, yet there are only a handful of reliable population estimates for this species from its remaining range, making global assessment challenging. We present the first rigorous population estimates for this species from Cambodia, and model the distribution and the relationships between this species and several environmental covariates from the Core Zone (187,900 ha) of Seima Protection Forest (SPF), eastern Cambodia. Using distance sampling the abundance of Green Peafowl in SPF in 2014 is estimated to be 541 (95% CI [252, 1160]). Density surface modelling was used to predict distribution and relative abundance within the study area, and there was some evidence that the species prefers areas of deciduous forest, non-forest, and to a lesser extent semi-evergreen forest. These results highlight the importance of the central and northern sections of SPF for this species. Furthermore, the analysis suggested that Green Peafowl abundance is higher in closer proximity to water, yet decreases in closer proximity to human settlement.

Behavioral responses affect distribution analyses of bowhead whales in the vicinity of seismic operations

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 549:243-262 (2016) - DOI: https://doi.org/10.3354/meps11665 Behavioral responses affect distribution analyses of bowhead whales in the vicinity of seismic operations Frances C. Robertson1,2,*, William R. Koski2, Andrew W. Trites1 1Department of Zoology and Marine Mammal Research Unit, Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada 2LGL Ltd, Environmental Research Associates, 22 Fisher Street, King City, ON, L7B 1A6, Canada *Corresponding author: f.robertson@fisheries.ubc.ca ABSTRACT: Aerial surveys are sometimes used to assess the densities of wide-ranging whales, as well as changes in their distributions in response to human activity. Such surveys also provide data used to estimate numbers of animals exposed to different received levels of seismic sound, as required by regulators. However, estimates of abundance are often biased because they fail to account for the effects of seismic operations on the surfacing and diving behavior of whales. Our objective was to determine the extent to which analyses of the distribution of bowhead whales Balaena mysticetus are affected by changes in visual ‘availability’ caused by seismic operations. We used aerial survey data collected during seismic operations in the Alaskan Beaufort Sea from late August to early October 2008 and fit spatial density surface models to bowhead sighting data to predict whale density in an ensonified area. We also incorporated availability correction factors to determine the sensitivity of density estimates to changes in surfacing and diving behavior caused by seismic operations. The influence of altered whale behavior was then evaluated by comparing a series of realistic simulated scenarios in which models incorporated undisturbed or seismic disturbance-related correction factors. Results suggest that the numbers of bowhead whales present in the vicinity of seismic operations during the bowhead autumn migration are underestimated if the behavioral effects of seismic operations on whales are ignored. Our study highlights the importance of accounting for changes in whale behavior that can affect sightability when estimating numbers and distribution of whales in the vicinity of industrial activity. KEY WORDS: Bowhead whale · Seismic survey · Distance sampling · Beaufort Sea · Availability · g(0) · Alaska · Spatial models · Behavior · Generalized additive model Full text in pdf format Supplementary material PreviousNextCite this article as: Robertson FC, Koski WR, Trites AW (2016) Behavioral responses affect distribution analyses of bowhead whales in the vicinity of seismic operations. Mar Ecol Prog Ser 549:243-262. https://doi.org/10.3354/meps11665 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 549. Online publication date: May 10, 2016 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2016 Inter-Research.

Horizontal niche partitioning of humpback and fin whales around the West Antarctic Peninsula: evidence from a concurrent whale and krill survey

A dedicated aerial cetacean survey was conducted concurrently to a standardised net trawl survey for krill in order to investigate distribution patterns of large whales and different krill species and to investigate relationships of these. Distance sampling data were used to produce density surface models for humpback (Megaptera novaeangliae) and fin whales (Balaenoptera physalus) around the West Antarctic Peninsula (WAP). Abundance for both species was estimated over two strata in the Bransfield Strait and Drake Passage. Distinct distribution patterns suggest horizontal niche partitioning of the two whale species around the WAP, with fin whales aggregating at the shelf edge of the South Shetland Islands in the Drake Passage and humpback whales in the Bransfield Strait. Krill biomass estimated from the concurrent krill survey was used along with CTD data from the same expedition, bathymetric parameters and satellite data on chlorophyll-a and ice concentration to model krill distribution. Comparisons of the predicted distributions of both whale species with the predicted distributions of Euphausia superba, Euphausia crystallorophias and Thysanoessa macrura suggest a complex relationship rather than a straightforward correlation between krill and whales. However, results indicate that fin whales were feeding in an area dominated by T. macrura, while humpback whales were found in areas of higher E. superba biomass. Our results provide abundance estimates for humpback whales and, for the first time, fin whales in the WAP and contribute important information on feeding ecology and habitat use of these two species in the Southern Ocean.

Echolocation detections and digital video surveys provide reliable estimates of the relative density of harbour porpoises

SummaryRobust estimates of the density or abundance of cetaceans are required to support a wide range of ecological studies and inform management decisions. Considerable effort has been put into the development of line‐transect sampling techniques to obtain estimates of absolute density from aerial‐ and boat‐based visual surveys. Surveys of cetaceans using acoustic loggers or digital cameras provide alternative methods to estimate relative density that have the potential to reduce cost and provide a verifiable record of all detections. However, the ability of these methods to provide reliable estimates of relative density has yet to be established.These methodologies were compared by conducting aerial visual line‐transect surveys (n = 10 days) and digital video strip‐transect surveys (n = 4 days) in the Moray Firth, Scotland. Simultaneous acoustic data were collected from moored echolocation detectors (C‐PODs) at 58 locations across the study site. Density surface modelling (DSM) of visual survey data was used to estimate spatial variation in relative harbour porpoise density on a 4 × 4 km grid.DSMwas also performed on the digital survey data, and the resulting model output compared to that from visual survey data. Estimates of relative density from visual surveys around acoustic monitoring sites were compared with several metrics previously used to characterise variation in acoustic detections of echolocation clicks.There was a strong correlation between estimates of relative density from visual surveys and digital video surveys (Spearman's ρ = 0·85). A correction to account for animals missed on the transect line [previously calculated for visual aerial surveys of harbour porpoise in the North Sea was used to convert relative density from the visual surveys to absolute density. This allowed calculation of the first estimate of a proxy for detection probability in digital video surveys, suggesting that 61% (CV = 0·53) of harbour porpoises were detected. There was also a strong correlation between acoustic detections and density with Spearman's ρ = 0·73 for detection positive hours.These results provide confidence in the emerging use of digital video and acoustic surveys for studying the density of small cetaceans and their responses to environmental and anthropogenic change.

Cost-effective nocturnal distance sampling for landscape monitoring of ungulate populations

Estimating the size of ungulate populations dwelling forested habitats is technically difficult and expensive. In particular, population assessment via conventional distance sampling (CDS) at landscape scales is challenging and often discarded for its high costs. The development of a framework for its methodological optimization is mandatory. To tackle this issue, we used survey simulations. For arbitrary-distributed populations, we compared the following: (i) systematic random transect allocation, (ii) random selection of footpaths, and (iii) two-stage sampling selection of footpaths (2, 5, 10 blocks). The performance of two-stage sampling and random footpath selection estimators was similar. Then, we applied previous results to estimate the size of a red deer (Cervus elaphus) population in the Italian Apennines. Using data from a pilot survey, we estimated density via CDS and density surface modeling (DSM), and we quantified survey costs per unit effort. Considering our deer distribution, we finally simulated and evaluated the cost-effectiveness of the abovementioned designs for a range of realistic efforts (25–65 transects). CDS produced a negatively biased and less precise estimate than the corresponding DSM. For an effort of 65 transects, design (ii) estimates were unbiased (coefficient of variation = 0.31), while design (iii) provided negatively biased estimates (coefficient of variation = 0.27). Two-stage sampling designs with few blocks were less expensive than other designs in attaining the same level of precision, and they emerged as a cost-effective survey design. Our simulation approach thus provided managers a readily available tool to improve the estimate of ungulate abundances at a landscape scale.

Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME) from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO) produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE) to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify “significant concentrations” of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores), and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here and elsewhere.

Mapping seabird sensitivity to offshore wind farms.

We present a Geographic Information System (GIS) tool, SeaMaST (Seabird Mapping and Sensitivity Tool), to provide evidence on the use of sea areas by seabirds and inshore waterbirds in English territorial waters, mapping their relative sensitivity to offshore wind farms. SeaMaST is a freely available evidence source for use by all connected to the offshore wind industry and will assist statutory agencies in assessing potential risks to seabird populations from planned developments. Data were compiled from offshore boat and aerial observer surveys spanning the period 1979–2012. The data were analysed using distance analysis and Density Surface Modelling to produce predicted bird densities across a grid covering English territorial waters at a resolution of 3 km×3 km. Coefficients of Variation were estimated for each grid cell density, as an indication of confidence in predictions. Offshore wind farm sensitivity scores were compiled for seabird species using English territorial waters. The comparative risks to each species of collision with turbines and displacement from operational turbines were reviewed and scored separately, and the scores were multiplied by the bird density estimates to produce relative sensitivity maps. The sensitivity maps reflected well the amassed distributions of the most sensitive species. SeaMaST is an important new tool for assessing potential impacts on seabird populations from offshore development at a time when multiple large areas of development are proposed which overlap with many seabird species’ ranges. It will inform marine spatial planning as well as identifying priority areas of sea usage by marine birds. Example SeaMaST outputs are presented.

Conserving Cuvier’s beaked whales in the Alboran Sea (SW Mediterranean): Identification of high density areas to be avoided by intense man-made sound

Links between atypical mass strandings of beaked whales and military manoeuvres have been demonstrated in several parts of the Mediterranean, including the Alboran Sea. Herein, information on the distribution and abundance of Cuvier’s beaked whales is presented for the Alboran Sea. Such information is of great importance to allow the impacts of mass strandings, entanglements, etc. to be put in a population context and to highlight the most important areas for this species which may be focus for conservation action. Data used for these analyses come from two sources: summers 2008–2009 on board the vessel Alliance; and 1992–2009 surveys under the umbrella of the NGO Alnitak. A detection function was obtained using distance sampling methods and density surface modeling was undertaken. Availability bias correction factors were estimated for different platforms and vessel speeds and applied during the spatial modeling exercise. The final estimate of density (in animals/km2) corrected for the availability bias was 0.0054 (CV=22%). Based on these results, and a comparison with estimates from elsewhere, it is clear that the Alboran Sea supports one of the highest densities of Cuvier’s beaked whales in the world. This information and the proposed management measures are being used by the Spanish Ministry for Agriculture, Food and Environment to assess the possibility of increasing the level of protection of this species by either to promote a proposal for a Marine Protected Area designation or to include Cuvier’s beaked whales in the Spanish catalogue of threatened species in the “Vulnerable” category.

Integrating aerial and ship surveys of marine birds into a combined density surface model: A case study of wintering Common Loons

ABSTRACT Biologists now use a variety of survey platforms to assess the spatial distribution and abundance of marine birds, yet few attempts have been made to integrate data from multiple survey platforms to improve model accuracy or precision. We used density surface models (DSMs) to incorporate data from two survey platforms to predict the distribution and abundance of a diving marine bird, the Common Loon (Gavia immer). We conducted strip transect surveys from a multiengine, fixed-wing aircraft and line surveys from a 28 m ship during winter 2009–2010 in a 3,800 km2 study area off the coast of Rhode Island, USA. We accounted for imperfect detection and availability bias due to Common Loon diving behavior. We incorporated spatially explicit environmental covariates (water depth and latitude) to provide predictions of the spatial distribution and abundance of wintering Common Loons. The combined-platform DSM estimated the highest Common Loon densities (>20 individuals km−2) in nearshore waters <35 m deep...

Identifying realistic recovery targets and conservation actions for tigers in a human‐dominated landscape using spatially explicit densities of wild prey and their determinants

AbstractAimSetting realistic population targets and identifying actions for site and landscape‐level recovery plans are critical for achieving the global target of doubling wild tiger numbers by 2022. Here, we estimate the spatially explicit densities of wild ungulate prey across a gradient of disturbances in two disjunct tiger habitat blocks (THBs) covering 5212 km2, to evaluate landscape‐wide conditions for tigers and identify opportunities and specific actions for recovery.LocationWestern Terai Arc Landscape, India.MethodsData generated from 96 line transects in 15 systematically selected geographical cells (166.5 km2) were used to estimate spatially explicit densities of six wild ungulate prey species at a fine scale (1 km2). Employing distance‐based density surface models, we derived species‐specific estimates within three major forest land management categories (inviolate protected areas (PA),PAs with settlements and multiple‐use forests). By scaling estimated prey densities using an established relationship, we predicted the carrying capacity for tigers within eachTHB.ResultsSpecies‐specific responses of the six wild ungulates to natural‐habitat and anthropogenic covariates indicated the need for targeted prey recovery strategies. InviolatePAs supported the highest prey densities compared withPAs with settlements and multiple‐use forests, and specifically benefited the principal tiger prey species (chitalAxis axisand sambarRusa unicolor). The estimated mean prey density of 35.16 (±5.67) individuals per km2can potentially support 82 (62–106) and 299 (225–377) tigers acrossTHBI andTHB II, which currently support 2 (2–7) and 225 (199–256) tigers, respectively. This suggests a potentialc. 68% increase in population size given existing prey abundances. Finally, whileTHBI represents a potential tiger recovery site given adequate prey,PAs where resettlement of pastoralists is underway represent potential prey recovery sites inTHB II.Main conclusionsThis systematic approach of setting realistic population targets and prioritizing spatially explicit recovery strategies should aid in developing effective landscape conservation plans towards achieving global tiger conservation targets.

Spatial and seasonal dynamic of abundance and distribution of guanaco and livestock: insights from using density surface and null models.

Monitoring species abundance and distribution is a prerequisite when assessing species status and population viability, a difficult task to achieve for large herbivores at ecologically meaningful scales. Co-occurrence patterns can be used to infer mechanisms of community organization (such as biotic interactions), although it has been traditionally applied to binary presence/absence data. Here, we combine density surface and null models of abundance data as a novel approach to analyze the spatial and seasonal dynamics of abundance and distribution of guanacos (Lama guanicoe) and domestic herbivores in northern Patagonia, in order to visually and analytically compare the dispersion and co-occurrence pattern of ungulates. We found a marked seasonal pattern in abundance and spatial distribution of L. guanicoe. The guanaco population reached its maximum annual size and spatial dispersion in spring-summer, decreasing up to 6.5 times in size and occupying few sites of the study area in fall-winter. These results are evidence of the seasonal migration process of guanaco populations, an increasingly rare event for terrestrial mammals worldwide. The maximum number of guanacos estimated for spring (25951) is higher than the total population size (10000) 20 years ago, probably due to both counting methodology and population growth. Livestock were mostly distributed near human settlements, as expected by the sedentary management practiced by local people. Herbivore distribution was non-random; i.e., guanaco and livestock abundances co-varied negatively in all seasons, more than expected by chance. Segregation degree of guanaco and small-livestock (goats and sheep) was comparatively stronger than that of guanaco and large-livestock, suggesting a competition mechanism between ecologically similar herbivores, although various environmental factors could also contribute to habitat segregation. The new and compelling combination of methods used here is highly useful for researchers who conduct counts of animals to simultaneously estimate population sizes, distributions, assess temporal trends and characterize multi-species spatial interactions.

A spatial conservation prioritization approach for protecting marine birds given proposed offshore wind energy development

There are currently no offshore wind energy developments (OWEDs) in North America, although numerous OWEDs have been proposed along the Atlantic Coast. Development pressure has been a catalyst for marine spatial planning (MSP) to identify suitable areas for OWED. However, integrating complex ecological information to guide OWED siting remains a substantial challenge. We developed spatial distribution models of marine birds from aerial surveys that we conducted from 2010 to 2012 throughout a 3800km2 area off the coast of Rhode Island. For seven groups of marine birds, we constructed either a density surface model or a presence–absence model that incorporated relevant environmental covariates. We integrated our spatial models, along with uncertainty, using spatial conservation prioritization (SCP) software. This identified sites with high marine bird conservation priority that aided evaluation of proposed OWED sites. We found that shallow nearshore waters had the highest conservation priority overall, but we also detected key offshore areas of high priority. Hypothetical OWEDs placed in conservation priority areas significantly reduced the overall distribution of focal species. Currently proposed OWED sites are located in areas of relatively low conservation priority and so would not substantially reduce the overall distribution of marine birds. This SCP approach when combined with quantitative models of bird distribution given relevant environmental covariates provides a robust framework that satisfies the principles of ecosystem-based MSP. Thus, this combined SCP-distribution modeling framework should be extremely helpful to decision makers as they evaluate proposed siting locations of OWEDs in the context of a dynamic marine system.

Spatially explicit model of wintering common loons: conservation implications

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 492:273-283 (2013) - DOI: https://doi.org/10.3354/meps10492 Spatially explicit model of wintering common loons: conservation implications Kristopher J. Winiarski1,2,*, David L. Miller1, Peter W. C. Paton1, Scott R. McWilliams1 Department of Natural Resources Science, University of Rhode Island, 1 Greenhouse Road, Kingston, Rhode Island 02881, USA 2Present address: Department of Environmental Conservation, University of Massachusetts, 160 Holdsworth Way, Amherst, Massachusetts 01003, USA *Email: withakri@gmail.com ABSTRACT: Common loons Gavia immer are a conservation concern in New England due to a variety of anthropogenic factors, yet little is known about biotic and abiotic environmental factors determining their wintering distribution and abundance in nearshore and offshore waters. The primary objective of this study was to develop a spatially explicit abundance model of wintering common loons in the maritime waters of southern New England (USA) that could inform decisions about offshore development. Aerial line-transect surveys were conducted throughout a 3800 km2 study area off the coast of Rhode Island during the winters of 2010–2011 and 2011–2012. A density surface model (DSM) approach was used to account for imperfect detection and incorporate spatially explicit environmental covariates. Common loon densities were greatest in waters <35 m deep, with high chl a surface concentrations (>2 mg m-3). The DSM predicted 5047 (95% CI = 3993-6379) common loons in the study area during winter, which suggests this region provides key habitat for this species in eastern North America. This study highlights important areas for common loons in the region, suggests key biotic (primary productivity as measured by long-term chl a surface concentrations) and abiotic covariates (water depth) driving the spatial distribution and abundance of common loons in southern New England, and identifies sites that should be considered for protection from offshore development, including offshore wind facilities. KEY WORDS: Aerial line-transect survey · Chlorophyll a · Density surface model · Distance sampling · Gavia immer · Spatially explicit abundance models Full text in pdf format Supplementary material PreviousNextCite this article as: Winiarski KJ, Miller DL, Paton PWC, McWilliams SR (2013) Spatially explicit model of wintering common loons: conservation implications. Mar Ecol Prog Ser 492:273-283. https://doi.org/10.3354/meps10492 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 492. Online publication date: October 31, 2013 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2013 Inter-Research.

Spatial models for distance sampling data: recent developments and future directions

SummaryOur understanding of a biological population can be greatly enhanced by modelling their distribution in space and as a function of environmental covariates. Such models can be used to investigate the relationships between distribution and environmental covariates as well as reliably estimate abundances and create maps of animal/plant distribution.Density surface models consist of a spatial model of the abundance of a biological population which has been corrected for uncertain detection via distance sampling methods.We review recent developments in the field and consider the likely directions of future research before focussing on a popular approach based on generalized additive models. In particular, we consider spatial modelling techniques that may be advantageous to applied ecologists such as quantification of uncertainty in a two‐stage model and smoothing in areas with complex boundaries.The methods discussed are available in anRpackage developed by the authors (dsm) and are largely implemented in the popular Windows software Distance.

Spatial trends in abundance of long-finned pilot whales, white-beaked dolphins and harbour porpoises in West Greenland

Data from an aerial line transect survey conducted off West Greenland during August–September 2007 were used to estimate the abundance of long-finned pilot whales (Globicephala melas), white-beaked dolphins (Lagenorhynchus albirostris) and harbour porpoises (Phocoena phocoena). The abundance of each species was estimated using mark-recapture distance sampling techniques to correct for perception bias, and correction factors for time spent at the surface were applied. The fully corrected abundance estimates were 8,133 long-finned pilot whales, 11,984 white-beaked dolphins and 33,271 harbour porpoises. Based on density surface modelling methods, a count model with a generalised additive model formulation was used to relate abundance to spatial variables. Response curves indicated that the preferred habitats were deep offshore areas in Midwest Greenland for pilot whales, deep water over steep seabed slopes in South Greenland for white-beaked dolphins and relatively shallow inshore waters in Midwest–South Greenland for harbour porpoises. The abundance estimates and spatial trends for the three species are the first obtained from Greenland.

Ecological and Environmental Modelling Workshops

The Centre for Research into Ecological and Environmental Modelling (CREEM) is hosting three linked workshops in the summer of 2012 in our purpose-built facilities at the University of St Andrews, Scotland. The aim of these workshops is to train participants in the latest methods for design and analysis of distance sampling surveys, including line and point transects. The workshops are taught by leading researchers in the field, using industry-standard software. The first workshop (21–24 August) will run at an introductory level, and will focus on “conventional” distance sampling methods, as described in the standard reference book Introduction to Distance Sampling. The workshop will be a blend of theory and practice, and participants will learn how to use the program “Distance.” Participants will gain a solid grounding in both survey design and methods of analysis for distance sampling surveys. Note that we have moved the “automated survey design” topic out of the advanced workshop into the introductory workshop. The advanced distance sampling workshop (27–30 August) will include advanced treatment of: incorporating covariates in detection function modeling, analyses in which detectability on the transect line is not assumed to be perfect (the so-called g(0) problem) and spatial (or density surface) modeling. The aim of this workshop is to bring participants up to date with the latest developments in distance sampling methods and software. It is also an opportunity for those actively engaged in the design, analysis, and execution of distance sampling surveys to discuss common issues and problems, and set future research directions. The workshop will be a combination of lectures and computer sessions, with considerable time for discussion. In addition, this year we are running a one-day introduction to density estimation from passive acoustic data (25 August). Passive acoustic monitoring is often used to obtain indices of relative abundance, such as number of detections per unit time. However, for many applications, the quantity we really want to estimate is absolute population abundance (i.e., the number of animals in the population) or density (number of animals per unit area). This day-long tutorial will give an insight into methods to achieve this. For all workshops, participants are encouraged to bring their own data sets, and can expect to do some preliminary analyses with their data. Computer sessions take place in our modern computer classroom (attached to the seminar room); participants can use our computers or bring their own laptops. Additional details regarding the workshop can be found at our web site 〈http://www.ruwpa.st-and.ac.uk/distance.workshops/distance2012/workshop_overview.html〉

Spatial distribution, abundance and habitat use of the protected fan mussel Pinna nobilis in Souda Bay, Crete

The spatial distribution and abundance of the endangered fan mussel Pinna nobilis was investigated in Souda Bay, Crete, Greece. A density surface modelling approach using survey data from line transects, integrated with a geographic information system, was applied to estimate the population density and abundance of the fan mussel in the study area. Marked zonation of P. nobilis distribution was revealed with a density peak at a depth of ~15 m and practically zero densities in shallow areas ( 30 m. A hotspot of high density was observed in the south- eastern part of the bay. The highest densities occurred in Caulerpa racemosa and Cymodocea nodosa beds, and the lowest occurred on rocky or unvegetated sandy/muddy bottoms and in Caulerpa pro- lifera beds. The high densities of juvenile fan mussels (almost exclusively of the first age class) observed in dense beds of the invasive alien alga C. racemosa were an indication of either preferen- tial recruitment or reduced juvenile mortality in this habitat type. In C. nodosa beds, mostly large individuals were observed. The total abundance of the species was estimated as 130 900 individuals with a 95% confidence interval of 100 600 to 170 400 individuals. Despite poaching, incidental killing and marine pollution, the fan mussel population of Souda Bay remains of high importance as one of the largest documented in Greece, and protection measures are urgently needed to secure its sustainability. We provide a baseline for the Souda Bay fan mussel population.

Distance software: design and analysis of distance sampling surveys for estimating population size

Summary 1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built‐in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple‐covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state‐of‐the‐art software that implements these methods is described that makes the methods accessible to practising ecologists.