http://hdl.handle.net/10023/664 2013-05-23T06:58:06Z http://hdl.handle.net/10023/1636 Abstract: Gopher tortoises are a small land tortoise that inhabit south-eastern United States and are listed as threatened due to habitat loss. They are rather hard to survey, since they occur at low density. This project was based on extensive data from systematic line transect surveys for gopher tortoises at Fort Gordon and Ichauway in Georgia, USA, collected by the Joseph W. Jones Ecological Research Centre. Despite excellent survey designs and field methods, the resulting estimates of abundance have shown high variance. Alternate methods for abundance and variance estimation that could lower the variance were explored. Both, design-based and model-based approaches to abundance estimation were attempted. For the design-based approach, abundance and associated variance estimates were obtained using the CDS/MCDS analysis engines in DISTANCE (Version 6.0). The cluster size estimation technique to scale burrow to tortoise abundance was used. Variance of the encounter rate component, that usually dominates the overall variance estimate for line transect data was originally calculated using the R2 estimator (used in DISTANCE 6.0 as the default) that is suited for random line placement. This was compared against encounter rate variance estimators developed for systematic designs (Fewster et al. 2009). As expected, the latter produced substantially lower variance estimates. For the model-based approach, abundance as well as occupancy was modelled by specifying GAMs using environmental covariates (where available) for the study sites. Resulting predictions were subjected to non-parametric and parametric bootstrapping for variance estimation. Parametric bootstrap suited to the model-based approach did not perform well because the underlying GAMs specified for burrow occupancy were found to be inaccurate. Due to the excellent design of the survey and the lack of sufficient information to model burrow occupancy accurately, design-based methods appeared to do better than the model-based methods for the data. The final estimates for both the study sites and the surface maps (only for Ichauway) produced need to be reviewed and must be considered in conjunction with the accompanying uncertainty. 2010-01-01T00:00:00Z Bal, Payal Gopher tortoises are a small land tortoise that inhabit south-eastern United States and are listed as threatened due to habitat loss. They are rather hard to survey, since they occur at low density. This project was based on extensive data from systematic line transect surveys for gopher tortoises at Fort Gordon and Ichauway in Georgia, USA, collected by the Joseph W. Jones Ecological Research Centre. Despite excellent survey designs and field methods, the resulting estimates of abundance have shown high variance. Alternate methods for abundance and variance estimation that could lower the variance were explored. Both, design-based and model-based approaches to abundance estimation were attempted. For the design-based approach, abundance and associated variance estimates were obtained using the CDS/MCDS analysis engines in DISTANCE (Version 6.0). The cluster size estimation technique to scale burrow to tortoise abundance was used. Variance of the encounter rate component, that usually dominates the overall variance estimate for line transect data was originally calculated using the R2 estimator (used in DISTANCE 6.0 as the default) that is suited for random line placement. This was compared against encounter rate variance estimators developed for systematic designs (Fewster et al. 2009). As expected, the latter produced substantially lower variance estimates. For the model-based approach, abundance as well as occupancy was modelled by specifying GAMs using environmental covariates (where available) for the study sites. Resulting predictions were subjected to non-parametric and parametric bootstrapping for variance estimation. Parametric bootstrap suited to the model-based approach did not perform well because the underlying GAMs specified for burrow occupancy were found to be inaccurate. Due to the excellent design of the survey and the lack of sufficient information to model burrow occupancy accurately, design-based methods appeared to do better than the model-based methods for the data. The final estimates for both the study sites and the surface maps (only for Ichauway) produced need to be reviewed and must be considered in conjunction with the accompanying uncertainty. http://hdl.handle.net/10023/667 Abstract: Management schemes dedicated to the conservation of wildlife populations rely on the effective monitoring of population size, and this requires the accurate and precise estimation of abundance. The accuracy and precision of estimates are determined to a large extent by the survey design. Line transect surveys are commonly applied to wildlife population assessments in which the primary purpose of a survey design is to ensure that the critical distance sampling assumptions are met. Little information is available regarding cetacean abundance in the Archipelago of the Azores (Portugal). This study aims to design a line transect shipboard survey that allows the collection of data required to provide abundance estimates for such species. Several aspects must be taken into consideration when designing a survey to estimate cetacean abundance. This is an iterative process, and there is a constant trade off between the logistic constraints and the desired statistical robustness. Information on this process is provided to aid policy makers and environmental managers, such as the criteria used for the choices made when defining the elements of a survey design. Three survey effort scenarios are provided to illustrate the range of possibilities between statistical robustness and logistic/ management restrictions. A survey is designed for the more economical scenario (L=5000Km), although the second scenario is the one recommended to be implemented (L=17,600Km) given it provides robust estimates of abundance (CV<=0.2). Description: Revised version November 2008. MRes in Marine Mammal Science 2008-01-01T00:00:00Z Faustino, Cláudia Estevinho Santos Management schemes dedicated to the conservation of wildlife populations rely on the effective monitoring of population size, and this requires the accurate and precise estimation of abundance. The accuracy and precision of estimates are determined to a large extent by the survey design. Line transect surveys are commonly applied to wildlife population assessments in which the primary purpose of a survey design is to ensure that the critical distance sampling assumptions are met. Little information is available regarding cetacean abundance in the Archipelago of the Azores (Portugal). This study aims to design a line transect shipboard survey that allows the collection of data required to provide abundance estimates for such species. Several aspects must be taken into consideration when designing a survey to estimate cetacean abundance. This is an iterative process, and there is a constant trade off between the logistic constraints and the desired statistical robustness. Information on this process is provided to aid policy makers and environmental managers, such as the criteria used for the choices made when defining the elements of a survey design. Three survey effort scenarios are provided to illustrate the range of possibilities between statistical robustness and logistic/ management restrictions. A survey is designed for the more economical scenario (L=5000Km), although the second scenario is the one recommended to be implemented (L=17,600Km) given it provides robust estimates of abundance (CV<=0.2). http://hdl.handle.net/10023/665 Abstract: The development of an animal-borne instrument that can record oceanographic measurements (CTD-SRDL) has enabled the collection of oceanographic data at a scale relevant to the counterpart behavioural data, both in time and 3-dimensional space. This has advanced the potential for studies of the behaviour of deep-diving marine animals and the way in which they respond to their environment, yet the nature of the data delivered by CTD-SRDLs presents substantial analytical challenges and places constraints on its biological interpretation. Behavioural and environmental data, collected using CTD-SRDLs deployed on southern elephant seals (Mirounga leonina) from the South Georgia subpopulation in 2004 and 2005, are analysed for 13 females and 4 males (21,015 dives). Compressed dive profiles are used to classify individual dives into six distinct types based on their 2-dimensional time-depth characteristics using random forest classification. The relationship between dive type and environmental variables, derived from oceanographic data recorded on board the animals, is investigated in the context of regression analysis, employing a multinomial model, as well as independently fitted Generalized Linear Models (GLM) and Generalized Additive Models (GAM) for each dive type. Regression is not found to be an appropriate method for analysing abstracted behavioural dive data, and other methods are suggested. We show that functional specializations can be manifested within a dive type, using square bottom dives (SQ) as an example. The usefulness of dive classification is discussed in the context of behavioural interpretation, and validity of the ecological functions attached to each class. Preliminary analyses are important drivers of further research into improving the interpretability of abstracted behavioural data, and developing efficient, standardized methods for widespread application to this type of data, which is obtained in abundance via satellite telemetry. Description: BL 5019 Research project. MRes Environmental Biology 2007-01-01T00:00:00Z Photopoulos, Theoni The development of an animal-borne instrument that can record oceanographic measurements (CTD-SRDL) has enabled the collection of oceanographic data at a scale relevant to the counterpart behavioural data, both in time and 3-dimensional space. This has advanced the potential for studies of the behaviour of deep-diving marine animals and the way in which they respond to their environment, yet the nature of the data delivered by CTD-SRDLs presents substantial analytical challenges and places constraints on its biological interpretation. Behavioural and environmental data, collected using CTD-SRDLs deployed on southern elephant seals (Mirounga leonina) from the South Georgia subpopulation in 2004 and 2005, are analysed for 13 females and 4 males (21,015 dives). Compressed dive profiles are used to classify individual dives into six distinct types based on their 2-dimensional time-depth characteristics using random forest classification. The relationship between dive type and environmental variables, derived from oceanographic data recorded on board the animals, is investigated in the context of regression analysis, employing a multinomial model, as well as independently fitted Generalized Linear Models (GLM) and Generalized Additive Models (GAM) for each dive type. Regression is not found to be an appropriate method for analysing abstracted behavioural dive data, and other methods are suggested. We show that functional specializations can be manifested within a dive type, using square bottom dives (SQ) as an example. The usefulness of dive classification is discussed in the context of behavioural interpretation, and validity of the ecological functions attached to each class. Preliminary analyses are important drivers of further research into improving the interpretability of abstracted behavioural data, and developing efficient, standardized methods for widespread application to this type of data, which is obtained in abundance via satellite telemetry.