Population density modelling of mixed polymorphic phenotypes: an application of spatial mark‐resight models

2021 ◽  
Author(s):  
A. Harihar ◽  
D. Lahkar ◽  
A. Singh ◽  
S. Kumar Das ◽  
M. F. Ahmed ◽  
...  
Keyword(s):  
Population Density ◽  
Density Modelling

Quantifying imperfect camera-trap detection probabilities: implications for density modelling

2020 ◽  
Vol 47 (2) ◽  
pp. 177 ◽  
Author(s):  
T. McIntyre ◽  
T. L. Majelantle ◽  
D. J. Slip ◽  
R. G. Harcourt
Keyword(s):  
Population Density ◽  
Surface Temperature ◽  
Ambient Temperature ◽  
Population Level ◽  
Camera Trap ◽  
Camera Traps ◽  
Imperfect Detection ◽  
Detection Rates ◽  
Detection Probabilities ◽  
Density Modelling

Abstract ContextData obtained from camera traps are increasingly used to inform various population-level models. Although acknowledged, imperfect detection probabilities within camera-trap detection zones are rarely taken into account when modelling animal densities. AimsWe aimed to identify parameters influencing camera-trap detection probabilities, and quantify their relative impacts, as well as explore the downstream implications of imperfect detection probabilities on population-density modelling. MethodsWe modelled the relationships between the detection probabilities of a standard camera-trap model (n=35) on a remotely operated animal-shaped soft toy and a series of parameters likely to influence it. These included the distance of animals from camera traps, animal speed, camera-trap deployment height, ambient temperature (as a proxy for background surface temperatures) and animal surface temperature. We then used this detection-probability model to quantify the likely influence of imperfect detection rates on subsequent population-level models, being, in this case, estimates from random encounter density models on a known density simulation. Key resultsDetection probabilities mostly varied predictably in relation to measured parameters, and decreased with an increasing distance from the camera traps and speeds of movement, as well as heights of camera-trap deployments. Increased differences between ambient temperature and animal surface temperature were associated with increased detection probabilities. Importantly, our results showed substantial inter-camera (of the same model) variability in detection probabilities. Resulting model outputs suggested consistent and systematic underestimation of true population densities when not taking imperfect detection probabilities into account. ConclusionsImperfect, and individually variable, detection probabilities inside the detection zones of camera traps can compromise resulting population-density estimates. ImplicationsWe propose a simple calibration approach for individual camera traps before field deployment and encourage researchers to actively estimate individual camera-trap detection performance for inclusion in subsequent modelling approaches.

Settlement Mapping for Population Density Modelling in Disease Risk Spatial Analysis

2021 ◽  
Author(s):  
Mirza Alim Mutasodirin ◽  
Rafi Dwi Rizqullah ◽  
Andie Setiyoko ◽  
Aniati Murni Arymurthy
Keyword(s):  
Spatial Analysis ◽  
Population Density ◽  
Disease Risk ◽  
Density Modelling

Population density modelling in support of disaster risk assessment

2015 ◽  
Vol 13 ◽  
pp. 334-341 ◽  
Author(s):  
Patrizia Tenerelli ◽  
Javier F. Gallego ◽  
Daniele Ehrlich
Keyword(s):  
Risk Assessment ◽  
Population Density ◽  
Disaster Risk ◽  
Disaster Risk Assessment ◽  
Density Modelling

Population density of migratory and resident brown trout (Salmo trutta) in relation to altitude: evidence for a migration cost

2001 ◽  
Vol 70 (1) ◽  
pp. 112-121 ◽  
Author(s):  
T. Bohlin ◽  
J. Pettersson ◽  
E. Degerman
Keyword(s):  
Population Density ◽  
Brown Trout ◽  
Salmo Trutta ◽  
Migration Cost ◽  
Brown Trout Salmo Trutta

Mouse population eruptions in New Zealand forests: the role of population density and seedfall

2000 ◽  
Vol 69 (6) ◽  
pp. 1058-1070 ◽  
Author(s):  
David Choquenot ◽  
Wendy A. Ruscoe
Keyword(s):  
New Zealand ◽  
Population Density ◽  
Mouse Population

Convergence of regional population density in Russia over 120 years

2020 ◽  
pp. 133-158
Author(s):  
K. A. Kholodilin ◽  
Y. I. Yanzhimaeva
Keyword(s):  
Population Density ◽  
Spatial Dependence ◽  
Population Distribution ◽  
Regional Level ◽  
Capital City ◽  
County Level ◽  
Spatial Effects ◽  
Russian Regions ◽  
Regional Population ◽  
Regional Population Density

A relative uniformity of population distribution on the territory of the country is of importance from socio-economic and strategic perspectives. It is especially important in the case of Russia with its densely populated West and underpopulated East. This paper considers changes in population density in Russian regions, which occurred between 1897 and 2017. It explores whether there was convergence in population density and what factors influenced it. For this purpose, it uses the data both at county and regional levels, which are brought to common borders for comparability purposes. Further, the models of unconditional and conditional β-convergence are estimated, taking into account the spatial dependence. The paper concludes that the population density equalization took place in 1897-2017 at the county level and in 1926—1970 at the regional level. In addition, the population density increase is shown to be influenced not only by spatial effects, but also by political and geographical factors such as climate, number of GULAG camps, and the distance from the capital city.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

Community based design approach as initial stage to promote urban composting from a Hill Station of the Philippines

2019 ◽  
Author(s):  
Marcelino Jr Lunag ◽  
Jessie C. Elauria ◽  
Juanito D. Burguillos
Keyword(s):  
Population Density ◽  
Community Involvement ◽  
The Philippines ◽  
Design Stage ◽  
High Population Density ◽  
Community Based ◽  
Hill Station ◽  
Initial Stage ◽  
Household Members ◽  
Community Based Design

This study confirms that lack of space due to high population density restricts household members and the barangay to comply with the existing law regarding composting. With these, community involvement in the design stage of compost bin as initial stage was done accordingly. The participants were voluntarily interviewed and were given questionnaires, which was endorsed and approved by barangay committee.

Integrated Assessment of Socio-Economic Development of Rural Areas, Taking into Account Differences in Population Density

2020 ◽  
pp. 76-83
Author(s):  
N.N. Balashova ◽  
◽  
D.A. Korobeynikov ◽  
S.A. Popova ◽  
◽  
...  
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Population Density ◽  
Rural Areas ◽  
Rural Population ◽  
Integrated Assessment ◽  
Russian Regions ◽  
Socio Economic Development

Typologization of rural areas, taking into account differences in population density and level of socio-economic development, is necessary to identify “growth points” and strategic sustainability benchmarks. The method of integrated assessment of the level of socio-economic development of rural territories is proposed, according to which the grouping of Russian regions is carried out. Applying data on rural population density to the results of calculations allowed us to identify 12 typological groups, in the context of which unified recommendations on sustainable development of territories should be formed.

Sign in / Sign up

Export Citation Format

Share Document