Centre for Research into Ecological & Environmental Modelling (CREEM) Research
https://hdl.handle.net/10023/166
2024-03-28T08:51:53ZSurveying abundance and stand type associations of Formica aquilonia and F. lugubris (Hymenoptera: Formicidae) nest mounds over an extensive area : Trialing a novel method
https://hdl.handle.net/10023/16260
Red wood ants are ecologically important members of woodland communities, and some species are of conservation concern. They occur commonly only in certain habitats in Britain, but there is limited knowledge of their numbers and distribution. This study provided baseline information at a key locality (Abernethy Forest, 37 km2) in the central Highlands of Scotland and trialed a new method of surveying red wood ant density and stand type associations: a distance sampling line transect survey of nests. This method is efficient because it allows an observer to quickly survey a large area either side of transect lines, without having to assume that all nests are detected. Instead, data collected on the distance of nests from the line are used to estimate probability of detection and the effective transect width, using the free software "Distance". Surveys took place in August and September 2003 along a total of 71.2 km of parallel, equally-spaced transects. One hundred and forty-four red wood ant nests were located, comprising 89 F. aquilonia (Yarrow, 1955) and 55 F. lugubris (Zetterstedt, 1838) nests. Estimated densities were 1.13 nests per hectare (95% CI 0.74-1.73) for F. aquilonia and 0.83 nests per hectare (95% CI 0.32-2.17) for F. lugubris. These translated to total estimated nest numbers of 4,200 (95% CI 2,700-6,400) and 3,100 (95% CI 1,200-8,100), respectively, for the whole forest. Indices of stand selection indicated that F. aquilonia had some positive association with old-growth and F. lugubris with younger stands (stem exclusion stage). No nests were found in areas that had been clear-felled, and ploughed and planted in the 1970s-1990s. The pattern of stand type association and hence distribution of F. aquilonia and F. lugubris may be due to the differing ability to disperse (F. lugubris is the faster disperser) and compete (F. aquilonia is competitively superior). We recommend using line transect sampling for extensive surveys of ants that construct nest mounds to estimate abundance and stand type association.
2012-01-03T00:00:00ZBorkin, KerrySummers, RonThomas, LenRed wood ants are ecologically important members of woodland communities, and some species are of conservation concern. They occur commonly only in certain habitats in Britain, but there is limited knowledge of their numbers and distribution. This study provided baseline information at a key locality (Abernethy Forest, 37 km2) in the central Highlands of Scotland and trialed a new method of surveying red wood ant density and stand type associations: a distance sampling line transect survey of nests. This method is efficient because it allows an observer to quickly survey a large area either side of transect lines, without having to assume that all nests are detected. Instead, data collected on the distance of nests from the line are used to estimate probability of detection and the effective transect width, using the free software "Distance". Surveys took place in August and September 2003 along a total of 71.2 km of parallel, equally-spaced transects. One hundred and forty-four red wood ant nests were located, comprising 89 F. aquilonia (Yarrow, 1955) and 55 F. lugubris (Zetterstedt, 1838) nests. Estimated densities were 1.13 nests per hectare (95% CI 0.74-1.73) for F. aquilonia and 0.83 nests per hectare (95% CI 0.32-2.17) for F. lugubris. These translated to total estimated nest numbers of 4,200 (95% CI 2,700-6,400) and 3,100 (95% CI 1,200-8,100), respectively, for the whole forest. Indices of stand selection indicated that F. aquilonia had some positive association with old-growth and F. lugubris with younger stands (stem exclusion stage). No nests were found in areas that had been clear-felled, and ploughed and planted in the 1970s-1990s. The pattern of stand type association and hence distribution of F. aquilonia and F. lugubris may be due to the differing ability to disperse (F. lugubris is the faster disperser) and compete (F. aquilonia is competitively superior). We recommend using line transect sampling for extensive surveys of ants that construct nest mounds to estimate abundance and stand type association.Assessing the utility and limitations of accelerometers and machine learning approaches in classifying behaviour during lactation in a phocid seal
https://hdl.handle.net/10023/16253
Background: Classifying behaviour with animal-borne accelerometers is quickly becoming a popular tool for remotely observing behavioural states in a variety of species. Most accelerometry work in pinnipeds has focused on classifying behaviour at sea often quantifying behavioural trade-offs associated with foraging and diving in income breeders. Very little work to date has been done to resolve behaviour during the critical period of lactation in a capital breeder. Capital breeding phocids possess finite reserves that they must allocate appropriately to maintain themselves and their new offspring during their brief nursing period. Within this short time, fine-scale behavioural trade-offs can have significant fitness consequences for mother and offspring and must be carefully managed. Here, we present a case study in extracting and classifying lactation behaviours in a wild, breeding pinniped, the grey seal (Halichoerus grypus). Results: Using random forest models, we were able to resolve 4 behavioural states that constitute the majority of a female grey seals’ activity budget during lactation. Resting, alert, nursing, and a form of pup interaction were extracted and classified reliably. For the first time, we quantified the potential confounding variance associated with individual differences in a wild context as well as differences due to sampling location in a largely inactive model species. Conclusions: At this stage, the majority of a female grey seal’s activity budget was classified well using accelerometers, but some rare and context-dependent behaviours were not well captured. While we did find significant variation between individuals in behavioural mechanics, individuals did not differ significantly within themselves; inter-individual variability should be an important consideration in future efforts. These methods can be extended to other efforts to study grey seals and other pinnipeds who exhibit a capital breeding system. Using accelerometers to classify behaviour during lactation allows for fine-scale assessments of time and energy trade-offs for species with fixed stores.
Funding for this work was provided by the Durham Doctoral Studentship scheme at Durham University and supported by Natural Environment Research Council’s core funding to the Sea Mammal Research Unit at the University of St. Andrews.
2018-10-16T00:00:00ZSchuert, CourtneyPomeroy, PatrickTwiss, SeanBackground: Classifying behaviour with animal-borne accelerometers is quickly becoming a popular tool for remotely observing behavioural states in a variety of species. Most accelerometry work in pinnipeds has focused on classifying behaviour at sea often quantifying behavioural trade-offs associated with foraging and diving in income breeders. Very little work to date has been done to resolve behaviour during the critical period of lactation in a capital breeder. Capital breeding phocids possess finite reserves that they must allocate appropriately to maintain themselves and their new offspring during their brief nursing period. Within this short time, fine-scale behavioural trade-offs can have significant fitness consequences for mother and offspring and must be carefully managed. Here, we present a case study in extracting and classifying lactation behaviours in a wild, breeding pinniped, the grey seal (Halichoerus grypus). Results: Using random forest models, we were able to resolve 4 behavioural states that constitute the majority of a female grey seals’ activity budget during lactation. Resting, alert, nursing, and a form of pup interaction were extracted and classified reliably. For the first time, we quantified the potential confounding variance associated with individual differences in a wild context as well as differences due to sampling location in a largely inactive model species. Conclusions: At this stage, the majority of a female grey seal’s activity budget was classified well using accelerometers, but some rare and context-dependent behaviours were not well captured. While we did find significant variation between individuals in behavioural mechanics, individuals did not differ significantly within themselves; inter-individual variability should be an important consideration in future efforts. These methods can be extended to other efforts to study grey seals and other pinnipeds who exhibit a capital breeding system. Using accelerometers to classify behaviour during lactation allows for fine-scale assessments of time and energy trade-offs for species with fixed stores.Occurrence, distribution and abundance of cetaceans in Onslow Bay, North Carolina, USA
https://hdl.handle.net/10023/7772
In this paper the occurrence, distribution and abundance of cetaceans in offshore waters of Onslow Bay, North Carolina, USA is described. Between June 2007 and June 2010 monthly aerial and shipboard line-transect surveys were conducted along ten 74km transects placed perpendicular to the shelf break. In total 42,676km of aerial trackline (218 sightings) and 5,209km of vessel trackline (100 sightings) were observed. Seven species of cetaceans were observed, but the fauna was dominated strongly by common bottlenose and Atlantic spotted dolphins. Both species were present year-round in the study area. Using photo-identification techniques, five bottlenose dolphins and one spotted dolphin were resighted during the three-year period. In general, the abundance of cetaceans in Onslow Bay was low and too few sightings were made to estimate monthly abundances for species other than bottlenose and spotted dolphins. Maximum monthly abundances of bottlenose and spotted dolphins were 4,100 (95% CI: 1,300–9,400) in May 2010 and 6,000 (95% CI: 2,500–17,400) in March 2009, respectively. Bottlenose dolphins were found throughout the study area, although they were encountered most frequently just off the shelf break. In contrast, spotted dolphins exhibited a strong preference for waters over the continental shelf and were not encountered beyond the shelf break.
2014-01-01T00:00:00ZRead, Andrew, J.Barco, S.Bell, J.Borchers, David LouisBurt, M LouiseCummings, E.W.Dunn, J.Fougeres, J.Hazen, L.Williams-Hodge, L.E.Laura, A-M.McAlarney, R.J.Nilsson, P.Pabst, D.A.Paxton, Charles G. M.Schneider, S.Z.Urian, KimWaples, D.M.McLellan, W.A.In this paper the occurrence, distribution and abundance of cetaceans in offshore waters of Onslow Bay, North Carolina, USA is described. Between June 2007 and June 2010 monthly aerial and shipboard line-transect surveys were conducted along ten 74km transects placed perpendicular to the shelf break. In total 42,676km of aerial trackline (218 sightings) and 5,209km of vessel trackline (100 sightings) were observed. Seven species of cetaceans were observed, but the fauna was dominated strongly by common bottlenose and Atlantic spotted dolphins. Both species were present year-round in the study area. Using photo-identification techniques, five bottlenose dolphins and one spotted dolphin were resighted during the three-year period. In general, the abundance of cetaceans in Onslow Bay was low and too few sightings were made to estimate monthly abundances for species other than bottlenose and spotted dolphins. Maximum monthly abundances of bottlenose and spotted dolphins were 4,100 (95% CI: 1,300–9,400) in May 2010 and 6,000 (95% CI: 2,500–17,400) in March 2009, respectively. Bottlenose dolphins were found throughout the study area, although they were encountered most frequently just off the shelf break. In contrast, spotted dolphins exhibited a strong preference for waters over the continental shelf and were not encountered beyond the shelf break.Predicting future European breeding distributions of British seabird species under climate change and unlimited/no dispersal scenarios
https://hdl.handle.net/10023/7735
Understanding which traits make species vulnerable to climatic change and predicting future distributions permits conservation efforts to be focused on the most vulnerable species and the most appropriate sites. Here, we combine climate envelope models with predicted bioclimatic data from two emission scenarios leading up to 2100, to predict European breeding distributions of 23 seabird species that currently breed in the British Isles. Assuming unlimited dispersal, some species would be “winners” (increase the size of their range), but over 65% would lose range, some by up to 80%. These “losers” have a high vulnerability to low prey availability, and a northerly distribution meaning they would lack space to move into. Under the worst-case scenario of no dispersal, species are predicted to lose between 25% and 100% of their range, so dispersal ability is a key constraint on future range sizes. More globally, the results indicate, based on foraging ecology, which seabird species are likely to be most affected by climatic change. Neither of the emissions scenarios used in this study is extreme, yet they generate very different predictions for some species, illustrating that even small decreases in emissions could yield large benefits for conservation.
We thank the European Bird Census Council for their data on European seabird distributions. DJFR was supported by NERC UKPopNet.
2015-11-02T00:00:00ZRussell, Deborah Jill FraserWanless, SarahCollingham, Yvonne C.Huntley, BrianHamer, Keith C.Understanding which traits make species vulnerable to climatic change and predicting future distributions permits conservation efforts to be focused on the most vulnerable species and the most appropriate sites. Here, we combine climate envelope models with predicted bioclimatic data from two emission scenarios leading up to 2100, to predict European breeding distributions of 23 seabird species that currently breed in the British Isles. Assuming unlimited dispersal, some species would be “winners” (increase the size of their range), but over 65% would lose range, some by up to 80%. These “losers” have a high vulnerability to low prey availability, and a northerly distribution meaning they would lack space to move into. Under the worst-case scenario of no dispersal, species are predicted to lose between 25% and 100% of their range, so dispersal ability is a key constraint on future range sizes. More globally, the results indicate, based on foraging ecology, which seabird species are likely to be most affected by climatic change. Neither of the emissions scenarios used in this study is extreme, yet they generate very different predictions for some species, illustrating that even small decreases in emissions could yield large benefits for conservation.Pelagic movements of pacific leatherback turtles (Dermochelys coriacea) reveal the complex role of prey and ocean currents
https://hdl.handle.net/10023/4356
Background: Leatherback turtles are renowned for their trans-oceanic migrations. However, despite numerous movement studies, the precise drivers of movement patterns in leatherbacks remain elusive. Many previous studies of leatherback turtles as well as other diving marine predators have analyzed surface movement patterns using only surface covariates. Since turtles and other marine predators spend the vast majority of their time diving under water, an analysis of movement patterns at depth should yield insight into what drives their movements. Results: We analyzed the movement paths of 15 post-nesting adult female Pacific leatherback turtles, which were caught and tagged on three nesting beaches in Mexico. The temporal length of the tracks ranged from 32 to 436 days, and the spatial distance covered ranged from 1,532 km to 13,097 km. We analyzed these tracks using a movement model designed to yield inference on the parameters driving movement. Because the telemetry data included diving depths, we extended an earlier version of the model that examined surface only movements, and here analyze movements in 3-dimensions. We tested the effect of dynamic environmental covariates from a coupled biophysical oceanographic model on patch choice in diving leatherback turtles, and compared the effects of parameters measured at the surface and at depth. The covariates included distance to future patch, temperature, salinity, meridional current velocity (current in the north–south direction), zonal current velocity (current in the east–west direction), phytoplankton density, diatom density, micro-plankton density, and meso-zooplankton density. We found significant, i.e. non-zero, correlation between movement and the parameters for oceanic covariates in 8 of the tracks. Of particular note, for one turtle we observed a lack of correlation between movements and a modeled index of zooplankton at the surface, but a significant correlation between movements and zooplankton at depth. Two of the turtles express a preference for patches at depth with elevated diatoms, and 2 turtles prefer patches with higher mezozooplankton values at depth. In contrast, 4 turtles expressed a preference for elevated zooplankton patches at the surface, but not at depth. We suggest that our understanding of a marine predator’s response to the environment may change significantly depending upon the analytical frame of reference, i.e. whether relationships are examined at the surface, at depth, or at different temporal resolutions. Lastly, we tested the effects of accounting for ocean currents on the movement patterns and found that for 13 of the 15 turtles, the parameter governing distance to the next patch decreased. Conclusions: Our results suggest that relationships derived from the analysis of surface tracks may not entirely explain movement patterns of this highly migratory species. Accounting for choices in the water column has shown that for certain individual turtles, what appears to be favourable habitat at depth is quantitatively different from that at the surface. This has implications for the analysis of the movements and diving behaviour of any top marine predator. The leatherback turtle is a deep diving reptile, and it is important to understand the subsurface variables that influence their movements if we are to precisely map the spatial dimensions of favorable leatherback habitat. These results present a new view into the drivers of diving patterns in turtles, and in particular represent a way of analyzing movements at depth that can be extended to other diving species.
APC paid through BIS OA funds.
2013-11-20T00:00:00ZSchick, Robert SchillingRoberts, JasonEckert, ScottClark, JamesBailey, HelenChai, FeiShi, LiHalpin, PatrickBackground: Leatherback turtles are renowned for their trans-oceanic migrations. However, despite numerous movement studies, the precise drivers of movement patterns in leatherbacks remain elusive. Many previous studies of leatherback turtles as well as other diving marine predators have analyzed surface movement patterns using only surface covariates. Since turtles and other marine predators spend the vast majority of their time diving under water, an analysis of movement patterns at depth should yield insight into what drives their movements. Results: We analyzed the movement paths of 15 post-nesting adult female Pacific leatherback turtles, which were caught and tagged on three nesting beaches in Mexico. The temporal length of the tracks ranged from 32 to 436 days, and the spatial distance covered ranged from 1,532 km to 13,097 km. We analyzed these tracks using a movement model designed to yield inference on the parameters driving movement. Because the telemetry data included diving depths, we extended an earlier version of the model that examined surface only movements, and here analyze movements in 3-dimensions. We tested the effect of dynamic environmental covariates from a coupled biophysical oceanographic model on patch choice in diving leatherback turtles, and compared the effects of parameters measured at the surface and at depth. The covariates included distance to future patch, temperature, salinity, meridional current velocity (current in the north–south direction), zonal current velocity (current in the east–west direction), phytoplankton density, diatom density, micro-plankton density, and meso-zooplankton density. We found significant, i.e. non-zero, correlation between movement and the parameters for oceanic covariates in 8 of the tracks. Of particular note, for one turtle we observed a lack of correlation between movements and a modeled index of zooplankton at the surface, but a significant correlation between movements and zooplankton at depth. Two of the turtles express a preference for patches at depth with elevated diatoms, and 2 turtles prefer patches with higher mezozooplankton values at depth. In contrast, 4 turtles expressed a preference for elevated zooplankton patches at the surface, but not at depth. We suggest that our understanding of a marine predator’s response to the environment may change significantly depending upon the analytical frame of reference, i.e. whether relationships are examined at the surface, at depth, or at different temporal resolutions. Lastly, we tested the effects of accounting for ocean currents on the movement patterns and found that for 13 of the 15 turtles, the parameter governing distance to the next patch decreased. Conclusions: Our results suggest that relationships derived from the analysis of surface tracks may not entirely explain movement patterns of this highly migratory species. Accounting for choices in the water column has shown that for certain individual turtles, what appears to be favourable habitat at depth is quantitatively different from that at the surface. This has implications for the analysis of the movements and diving behaviour of any top marine predator. The leatherback turtle is a deep diving reptile, and it is important to understand the subsurface variables that influence their movements if we are to precisely map the spatial dimensions of favorable leatherback habitat. These results present a new view into the drivers of diving patterns in turtles, and in particular represent a way of analyzing movements at depth that can be extended to other diving species.Maximum likelihood estimation of mark-recapture-recovery models in the presence of continuous covariates
https://hdl.handle.net/10023/4073
We consider mark-recapture-recovery (MRR) data of animals where the model parameters are a function of individual time-varying continuous covariates. For such covariates, the covariate value is unobserved if the corresponding individual is unobserved, in which case the survival probability cannot be evaluated. For continuous-valued covariates, the corresponding likelihood can only be expressed in the form of an integral that is analytically intractable, and, to date, no maximum likelihood approach that uses all the information in the data has been developed. Assuming a first-order Markov process for the covariate values, we accomplish this task by formulating the MRR setting in a state-space framework and considering an approximate likelihood approach which essentially discretizes the range of covariate values, reducing the integral to a summation. The likelihood can then be efficiently calculated and maximized using standard techniques for hidden Markov models. We initially assess the approach using simulated data before applying to real data relating to Soay sheep, specifying the survival probability as a function of body mass. Models that have previously been suggested for the corresponding covariate process are typically of the form of di.usive random walks. We consider an alternative non-di.usive AR(1)-type model which appears to provide a significantly better fit to the Soay sheep data.
Supplementary material: R code for model fitting. Sample R code for simulating MRR data and fitting the corresponding model using the HMM-based approach (with MRR model as described in Section 3). Digital Object Identifier: doi:10.1214/13-AOAS644SUPP
2013-01-01T00:00:00ZLangrock, RolandKing, RuthWe consider mark-recapture-recovery (MRR) data of animals where the model parameters are a function of individual time-varying continuous covariates. For such covariates, the covariate value is unobserved if the corresponding individual is unobserved, in which case the survival probability cannot be evaluated. For continuous-valued covariates, the corresponding likelihood can only be expressed in the form of an integral that is analytically intractable, and, to date, no maximum likelihood approach that uses all the information in the data has been developed. Assuming a first-order Markov process for the covariate values, we accomplish this task by formulating the MRR setting in a state-space framework and considering an approximate likelihood approach which essentially discretizes the range of covariate values, reducing the integral to a summation. The likelihood can then be efficiently calculated and maximized using standard techniques for hidden Markov models. We initially assess the approach using simulated data before applying to real data relating to Soay sheep, specifying the survival probability as a function of body mass. Models that have previously been suggested for the corresponding covariate process are typically of the form of di.usive random walks. We consider an alternative non-di.usive AR(1)-type model which appears to provide a significantly better fit to the Soay sheep data.A first survey of the global population size and distribution of the Scottish Crossbill Loxia scotica
https://hdl.handle.net/10023/1957
A survey of Scottish Crossbills Loxia scotica was carried out in 3,506 km2 of conifer woodland in northern Scotland during January to April 2008 to provide the first estimate of the global population size for this endemic bird. Population estimates were also made for Common Crossbills L. curvirostra and Parrot Crossbills L. pytyopsittacus within this range. Crossbills were lured to systematically selected survey points for counting, sexing and recording their calls for later call-type (species) identification from sonograms. Crossbills were located at 451 of the 852 survey points, and adequate tape-recordings made at 387 of these. The Scottish Crossbill had a disjunct distribution, occurring largely within the eastern part of the study area, but also in the northwest. Common Crossbills had a mainly westerly distribution. The population size of postjuvenile Scottish Crossbills was estimated as 13,600 (95%C.I. 8,130–22,700), which will approximate to 6,800 (4,065–11,350) pairs. Common Crossbills were more abundant within this range (27,100, 95% C.I. 14,700–38,400) and Parrot Crossbills rare (about 100). The sex ratio was not significantly different from parity for Scottish Crossbills. The modal number at survey points was two but numbers were larger in January than later in the survey. The numbers and distribution of all crossbill species are likely to vary between years, depending upon the size of the cone crops of the different conifers: all were coning in 2008. Common Crossbill and Parrot Crossbill numbers will also be affected by irruptions from continental Europe. A monitoring scheme is required to detect any population trend, and further work on their habitat requirement (e.g. conifer selection at different seasons) is needed to inform habitat management of native and planted conifer forests to ensure a secure future for this endemic bird.
"The survey was part-financed by Scottish Natural Heritage"
2011-06-01T00:00:00ZSummers, Ron WBuckland, Stephen TerrenceA survey of Scottish Crossbills Loxia scotica was carried out in 3,506 km2 of conifer woodland in northern Scotland during January to April 2008 to provide the first estimate of the global population size for this endemic bird. Population estimates were also made for Common Crossbills L. curvirostra and Parrot Crossbills L. pytyopsittacus within this range. Crossbills were lured to systematically selected survey points for counting, sexing and recording their calls for later call-type (species) identification from sonograms. Crossbills were located at 451 of the 852 survey points, and adequate tape-recordings made at 387 of these. The Scottish Crossbill had a disjunct distribution, occurring largely within the eastern part of the study area, but also in the northwest. Common Crossbills had a mainly westerly distribution. The population size of postjuvenile Scottish Crossbills was estimated as 13,600 (95%C.I. 8,130–22,700), which will approximate to 6,800 (4,065–11,350) pairs. Common Crossbills were more abundant within this range (27,100, 95% C.I. 14,700–38,400) and Parrot Crossbills rare (about 100). The sex ratio was not significantly different from parity for Scottish Crossbills. The modal number at survey points was two but numbers were larger in January than later in the survey. The numbers and distribution of all crossbill species are likely to vary between years, depending upon the size of the cone crops of the different conifers: all were coning in 2008. Common Crossbill and Parrot Crossbill numbers will also be affected by irruptions from continental Europe. A monitoring scheme is required to detect any population trend, and further work on their habitat requirement (e.g. conifer selection at different seasons) is needed to inform habitat management of native and planted conifer forests to ensure a secure future for this endemic bird.Distance software: design and analysis of distance sampling surveys for estimating population size
https://hdl.handle.net/10023/817
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 pre-requisite 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: CDS (conventional distance sampling), which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; MCDS (multiple covariate distance sampling), which allows covariates in addition to distance; and MRDS (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 DSM (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 practicing ecologists.
2010-01-01T00:00:00ZThomas, LenBuckland, Stephen TerrenceRexstad, EricLaake, J LStrindberg, SHedley, S LBishop, J R BMarques, Tiago A.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 pre-requisite 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: CDS (conventional distance sampling), which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; MCDS (multiple covariate distance sampling), which allows covariates in addition to distance; and MRDS (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 DSM (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 practicing ecologists.The importance of analysis method for breeding bird survey population trend estimates
https://hdl.handle.net/10023/685
Population trends from the Breeding Bird Survey are widely used to focus conservation efforts on species thought to be in decline and to test preliminary hypotheses regarding the causes of these declines. A number of statistical methods have been used to estimate population trends, but there is no consensus us to which is the most reliable. We quantified differences in trend estimates or different analysis methods applied to the same subset of Breeding Bird Survey data. We estimated trends for 115 species in British Columbia using three analysis methods: U.S. National Biological Service route regression, Canadian Wildlife Service route regression, and nonparametric rank-trends analysis. Overall, the number of species estimated to be declining was similar among the three methods, but the number of statistically significant declines was not similar (15, 8, and 29 respectively). In addition, many differences existed among methods in the trend estimates assigned to individual species. Comparing the two route regression methods, Canadian Wildlife Service estimates had a greater absolute magnitude on average than those of the U.S. National Biological Service method. U.S. National Biological Service estimates were on average more positive than the Canadian Wildlife Service estimates when the respective agency's data selection criteria were applied separately. These results imply that our ability to detect population declines and to prioritize species of conservation concern depend strongly upon the analysis method used. This highlights the need for further research to determine how best to accurately estimate trends from the data. We suggest a method for evaluating the performance of the analysis methods by using simulated Breeding Bird Survey data.
1996-01-01T00:00:00ZThomas, LenMartin, KathyPopulation trends from the Breeding Bird Survey are widely used to focus conservation efforts on species thought to be in decline and to test preliminary hypotheses regarding the causes of these declines. A number of statistical methods have been used to estimate population trends, but there is no consensus us to which is the most reliable. We quantified differences in trend estimates or different analysis methods applied to the same subset of Breeding Bird Survey data. We estimated trends for 115 species in British Columbia using three analysis methods: U.S. National Biological Service route regression, Canadian Wildlife Service route regression, and nonparametric rank-trends analysis. Overall, the number of species estimated to be declining was similar among the three methods, but the number of statistically significant declines was not similar (15, 8, and 29 respectively). In addition, many differences existed among methods in the trend estimates assigned to individual species. Comparing the two route regression methods, Canadian Wildlife Service estimates had a greater absolute magnitude on average than those of the U.S. National Biological Service method. U.S. National Biological Service estimates were on average more positive than the Canadian Wildlife Service estimates when the respective agency's data selection criteria were applied separately. These results imply that our ability to detect population declines and to prioritize species of conservation concern depend strongly upon the analysis method used. This highlights the need for further research to determine how best to accurately estimate trends from the data. We suggest a method for evaluating the performance of the analysis methods by using simulated Breeding Bird Survey data.Retrospective power analysis
https://hdl.handle.net/10023/679
Many papers have appeared in the recent biological literature encouraging us to incorporate statistical power analysis into our hypothesis testing protocol (Peterman 1990; Fairweather 1991; Muller & Benignus 1992; Taylor & Gerrodette 1993; Searcy-Bernal 1994; Thomas & Juanes 1996). The importance of doing a power analysis before beginning a study (prospective power analysis) is universally accepted: such analyses help us to decide how many samples are required to have a good chance of getting unambiguous results. In contrast, the role of power analysis after the data are collected and analyzed (retrospective power analysis) is controversial, as is evidenced by the papers of Reed and Blaustein (1995) and Hayes and Steidl (1997). The controversy is over the use of information from the sample data in retrospective power calculations. As I will show, the type of information used has fundamental implications for the value of such analyses. I compare the approaches to calculating retrospective power, noting the strengths and weaknesses of each, and make general recommendations as to how and when retrospective power analyses should be conducted.
The pdf contains the article; the ASCII file contains SAS code to calculate power and confidence limits for simple linear regression, as detailed in the article appendix.
1997-01-01T00:00:00ZThomas, LenMany papers have appeared in the recent biological literature encouraging us to incorporate statistical power analysis into our hypothesis testing protocol (Peterman 1990; Fairweather 1991; Muller & Benignus 1992; Taylor & Gerrodette 1993; Searcy-Bernal 1994; Thomas & Juanes 1996). The importance of doing a power analysis before beginning a study (prospective power analysis) is universally accepted: such analyses help us to decide how many samples are required to have a good chance of getting unambiguous results. In contrast, the role of power analysis after the data are collected and analyzed (retrospective power analysis) is controversial, as is evidenced by the papers of Reed and Blaustein (1995) and Hayes and Steidl (1997). The controversy is over the use of information from the sample data in retrospective power calculations. As I will show, the type of information used has fundamental implications for the value of such analyses. I compare the approaches to calculating retrospective power, noting the strengths and weaknesses of each, and make general recommendations as to how and when retrospective power analyses should be conducted.A unified framework for modelling wildlife population dynamics
https://hdl.handle.net/10023/678
This paper proposes a unified framework for defining and fitting stochastic, discrete-time, discrete-stage population dynamics models. The biological system is described by a state–space model, where the true but unknown state of the population is modelled by a state process, and this is linked to survey data by an observation process. All sources of uncertainty in the inputs, including uncertainty about model specification, are readily incorporated. The paper shows how the state process can be represented as a generalization of the standard Leslie or Lefkovitch matrix. By dividing the state process into subprocesses, complex models can be constructed from manageable building blocks. The paper illustrates the approach with a model of the British Grey Seal metapopulation, using sequential importance sampling with kernel smoothing to fit the model.
The pdf document contains the full article text; program code (in S-PLUS 6.1) for the example analysis is in the three text files; data is available from the Sea Mammal Research Unit (http://www.smru.st-and.ac.uk)
2005-01-01T00:00:00ZThomas, LenBuckland, Stephen T.Newman, KBHarwood, JohnThis paper proposes a unified framework for defining and fitting stochastic, discrete-time, discrete-stage population dynamics models. The biological system is described by a state–space model, where the true but unknown state of the population is modelled by a state process, and this is linked to survey data by an observation process. All sources of uncertainty in the inputs, including uncertainty about model specification, are readily incorporated. The paper shows how the state process can be represented as a generalization of the standard Leslie or Lefkovitch matrix. By dividing the state process into subprocesses, complex models can be constructed from manageable building blocks. The paper illustrates the approach with a model of the British Grey Seal metapopulation, using sequential importance sampling with kernel smoothing to fit the model.WinBUGS for population ecologists: Bayesian modeling using Markov Chain Monte Carlo methods.
https://hdl.handle.net/10023/677
The computer package WinBUGS is introduced. We first give a brief introduction to Bayesian theory and its implementation using Markov chain Monte Carlo (MCMC) algorithms. We then present three case studies showing how WinBUGS can be used when classical theory is difficult to implement. The first example uses data on white storks from Baden Württemberg, Germany, to demonstrate the use of mark-recapture models to estimate survival, and also how to cope with unexplained variance through random effects. Recent advances in methodology and also the WinBUGS software allow us to introduce (i) a flexible way of incorporating covariates using spline smoothing and (ii) a method to deal with missing values in covariates. The second example shows how to estimate population density while accounting for detectability, using distance sampling methods applied to a test dataset collected on a known population of wooden stakes. Finally, the third case study involves the use of state-space models of wildlife population dynamics to make inferences about density dependence in a North American duck species. Reversible Jump MCMC is used to calculate the probability of various candidate models. For all examples, data and WinBUGS code are provided.
This paper was presented at the EURING 2007 Technical Meeting, January 14-21, Dunedin, New Zealand. It has been submitted for publication in the conference proceedings, which will appear as a special issue of Environmental and Ecological Statistics.; The zip file contains accompanying code in WinBUGS
2008-01-01T00:00:00ZGiminez, OBonner, S JKing, RuthParker, R ABrooks, S PJamieson, L EGrosbois, VMorgan, B J TThomas, LenThe computer package WinBUGS is introduced. We first give a brief introduction to Bayesian theory and its implementation using Markov chain Monte Carlo (MCMC) algorithms. We then present three case studies showing how WinBUGS can be used when classical theory is difficult to implement. The first example uses data on white storks from Baden Württemberg, Germany, to demonstrate the use of mark-recapture models to estimate survival, and also how to cope with unexplained variance through random effects. Recent advances in methodology and also the WinBUGS software allow us to introduce (i) a flexible way of incorporating covariates using spline smoothing and (ii) a method to deal with missing values in covariates. The second example shows how to estimate population density while accounting for detectability, using distance sampling methods applied to a test dataset collected on a known population of wooden stakes. Finally, the third case study involves the use of state-space models of wildlife population dynamics to make inferences about density dependence in a North American duck species. Reversible Jump MCMC is used to calculate the probability of various candidate models. For all examples, data and WinBUGS code are provided.