Centre for Research into Ecological & Environmental Modelling (CREEM) Masters Theses
http://hdl.handle.net/10023/664
2018-05-22T13:43:10ZEstimating gopher tortoise abundance through design-based and model-based methods
http://hdl.handle.net/10023/1636
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.
2010-01-01T00:00:00ZBal, PayalGopher 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.Designing a shipboard line transect survey to estimate cetacean abundance off the Azores Archipelago, Portugal
http://hdl.handle.net/10023/667
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).
Revised version November 2008. MRes in Marine Mammal Science
2008-01-01T00:00:00ZFaustino, ClĂˇudia Estevinho SantosManagement 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).Behavioural changes of a long-ranging diver in response to oceanographic conditions
http://hdl.handle.net/10023/665
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.
BL 5019 Research project. MRes Environmental Biology
2007-01-01T00:00:00ZPhotopoulos, TheoniThe 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.