Use of Portable Antennas to Estimate Abundance of PIT-Tagged Fish in Small Streams: Factors Affecting Detection Probability

2010 ◽  
Vol 30 (2) ◽  
pp. 323-336 ◽  
Author(s):  
Matthew J. O'Donnell ◽  
Gregg E. Horton ◽  
Benjamin H. Letcher
Keyword(s):  
Detection Probability ◽  
Factors Affecting ◽  
Small Streams ◽  
Portable Antennas

scholarly journals Population estimates of Antillean manatees in Puerto Rico: an analytical framework for aerial surveys using multi-pass removal sampling

2019 ◽  
Vol 100 (4) ◽  
pp. 1340-1349
Author(s):  
Jaime A Collazo ◽  
Matthew J Krachey ◽  
Kenneth H Pollock ◽  
Francisco J Pérez-Aguilo ◽  
Jan P Zegarra ◽  
...  
Keyword(s):  
Puerto Rico ◽  
Detection Probability ◽  
Analytical Framework ◽  
Population Estimates ◽  
High Concentration ◽  
Imperfect Detection ◽  
Factors Affecting ◽  
Management Actions ◽  
Aerial Surveys ◽  
Population Size Estimates

AbstractEffective management of the threatened Antillean manatee (Trichechus manatus manatus) in Puerto Rico requires reliable estimates of population size. Estimates are needed to assess population responses to management actions, and whether recovery objectives have been met. Aerial surveys have been conducted since 1976, but none adjusted for imperfect detection. We summarize surveys since 1976, report on current distribution, and provide population estimates after accounting for apparent detection probability for surveys between June 2010 and March 2014. Estimates in areas of high concentration (hotspots) averaged 317 ± 101, three times higher than unadjusted counts (104 ± 0.56). Adjusted estimates in three areas outside hotspots also differed markedly from counts (75 ± 9.89 versus 19.5 ± 3.5). Average minimum island-wide estimate was 386 ± 89, similar to the maximum estimate of 360 suggested in 2005, but fewer than the 700 recently suggested by the Puerto Rico Manatee Conservation Center. Manatees were more widespread than previously understood. Improving estimates, locally or island-wide, will require stratifying the island differently and greater knowledge about factors affecting detection probability. Sharing our protocol with partners in nearby islands (e.g., Cuba, Jamaica, Hispaniola), whose populations share genetic make-up, would contribute to enhanced regional conservation through better population estimates and tracking range expansion.El manejo efectivo del manatí antillano amenazado en Puerto Rico requiere estimados de tamaños de poblaciónes confiables. Dichas estimaciones poblacionales son necesarias para evaluar las respuestas a las acciones de manejo, y para determinar si los objetivos de recuperación han sido alcanzados. Se han realizado censos aéreos desde 1976, pero ninguno de ellos han sido ajustados para detecciones imperfectas. Aquí resumimos los censos desde 1976, actualizamos la distribución, y reportamos los primeros estimados poblacionales ajustados para la probabilidad de detección aparente en los censos de Junio 2010 a Marzo 2014. Las estimaciones poblacionales en áreas de mayor concentración del manatí promedió 317 ± 103, tres veces más abundante que los conteos sin ajuste (104 ± 0.56). Las estimaciones poblacionales en tres áreas fuera de las áreas de mayor concentración del manatí también fueron marcadamente diferentes (75 ± 9.89 vs 19.5 ± 3.5). El estimado mínimo poblacional en la isla entera fue de 386 ± 89, similar al estimado máximo de 360 sugerido en el año 2005, pero menor a los 700 sugeridos recientemente por el Centro de Conservación de Manatíes de Puerto Rico. Documentamos que el manatí tiene una distribución más amplia de lo que se sabía con anterioridad. El mejoramiento de los estimados poblacionales locales o a nivel de isla requerirá que se estratifique a la isla en forma diferente y que se investiguen los factores que influencian a la probabilidad de detección. Compartir protocolos como este con colaboradores de islas vecinas (por. ej., Cuba, Jamaica, Española), cuyas poblaciones de manatíes comparten material genético, contribuiría a la conservación regional mediante mejores estimaciones poblacionales y monitoreo de la expansión de su ámbito doméstico.

scholarly journals Using areas of known occupancy to identify sources of variation in detection probability of raptors: taking time lowers replication effort for surveys

2016 ◽  
Vol 3 (10) ◽  
pp. 160368 ◽  
Author(s):  
Campbell Murn ◽  
Graham J. Holloway
Keyword(s):  
Detection Probability ◽  
Spatial Scales ◽  
Survey Methods ◽  
A Priori ◽  
Low Density ◽  
Occupancy Models ◽  
Imperfect Detection ◽  
Factors Affecting ◽  
Sources Of Variation ◽  
Time Of Year

Species occurring at low density can be difficult to detect and if not properly accounted for, imperfect detection will lead to inaccurate estimates of occupancy. Understanding sources of variation in detection probability and how they can be managed is a key part of monitoring. We used sightings data of a low-density and elusive raptor (white-headed vulture Trigonoceps occipitalis ) in areas of known occupancy (breeding territories) in a likelihood-based modelling approach to calculate detection probability and the factors affecting it. Because occupancy was known a priori to be 100%, we fixed the model occupancy parameter to 1.0 and focused on identifying sources of variation in detection probability. Using detection histories from 359 territory visits, we assessed nine covariates in 29 candidate models. The model with the highest support indicated that observer speed during a survey, combined with temporal covariates such as time of year and length of time within a territory, had the highest influence on the detection probability. Averaged detection probability was 0.207 (s.e. 0.033) and based on this the mean number of visits required to determine within 95% confidence that white-headed vultures are absent from a breeding area is 13 (95% CI: 9–20). Topographical and habitat covariates contributed little to the best models and had little effect on detection probability. We highlight that low detection probabilities of some species means that emphasizing habitat covariates could lead to spurious results in occupancy models that do not also incorporate temporal components. While variation in detection probability is complex and influenced by effects at both temporal and spatial scales, temporal covariates can and should be controlled as part of robust survey methods. Our results emphasize the importance of accounting for detection probability in occupancy studies, particularly during presence/absence studies for species such as raptors that are widespread and occur at low densities.

FACTORS AFFECTING DETECTION PROBABILITY OF CALIFORNIA BLACK RAILS

2004 ◽  
Vol 68 (2) ◽  
pp. 360-370 ◽  
Author(s):  
COURTNEY J. CONWAY ◽  
CHRISTINA SULZMAN ◽  
BARBARA E. RAULSTON
Keyword(s):  
Detection Probability ◽  
Factors Affecting

scholarly journals Factors affecting detection probability in plant distribution studies

2009 ◽  
Vol 97 (6) ◽  
pp. 1383-1389 ◽  
Author(s):  
Guoke Chen ◽  
Marc Kéry ◽  
Jinlong Zhang ◽  
Keping Ma
Keyword(s):  
Detection Probability ◽  
Plant Distribution ◽  
Factors Affecting ◽  
Distribution Studies

scholarly journals A Comprehensive Study on the Recent Progress and Trends in Development of Small Hydropower Projects

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2882
Author(s):  
Teegala Srinivasa Kishore ◽  
Epari Ritesh Patro ◽  
V. S. K. V. Harish ◽  
Ali Torabi Haghighi
Keyword(s):  
Power Plants ◽  
Fossil Fuels ◽  
Feasibility Studies ◽  
Renewable Resource ◽  
Primary Objective ◽  
Small Hydropower ◽  
Large Power ◽  
Factors Affecting ◽  
Small Streams ◽  
The World

In terms of fuel resource, hydropower possesses a prominent advantage over any other large power plants which burn fossil fuels to generate electricity. Moreover, due to the abundance in resource availability (as a domestic source in small streams and rivers), small hydropower (SHP) plants are showing prominence all over the world. SHP plants have led to improved access to electricity usage in under-developed and developing nations, thereby contributing to sustainable development goals and social empowerment. SHP, as a technology, is regarded as the largest density renewable resource with high adaptability, and low investment costs. The primary objective of the paper is to study and analyze recent developments in SHP technologies with reporting statistical figures in terms of installed capacity and MW potential in several parts of the world. Methodologies adopted by researchers to conduct techno-economic analysis of SHP projects are reviewed. Various costs involved in conducting pre-feasibility studies—such as constructing, maintaining, and sustainably operating SHP projects—are studied. The results of the study indicate cost and regulatory issues are the major factors affecting the growth of the small hydropower sector in many nations. Major impediments to construction, development and deployment of SHP projects, mutually existing among the nations worldwide, are also reported. Technical hindrances include non-availability of the grid and very limited accessibility to SHP sites, emissions due to storage of water, disruptive technologies with limited manpower and non-technical hindrances include discouragement from local bodies and groups, lack of suitable and precise pathways to accomplish SHP goals of a nation, lack of incentives for encouraging private players to invest in SHP projects, complex approval processes, and many more.

scholarly journals An Evaluation of the Factors Affecting ‘Poacher’ Detection with Drones and the Efficacy of Machine-Learning for Detection

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4074
Author(s):  
Katie E. Doull ◽  
Carl Chalmers ◽  
Paul Fergus ◽  
Steve Longmore ◽  
Alex K. Piel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Detection Probability ◽  
Visible Spectrum ◽  
Time Of Day ◽  
Automated Detection ◽  
Probability Of Detection ◽  
Factors Affecting ◽  
Camera Angle ◽  
Manual Analysis ◽  
Stationary Test

Drones are being increasingly used in conservation to tackle the illegal poaching of animals. An important aspect of using drones for this purpose is establishing the technological and the environmental factors that increase the chances of success when detecting poachers. Recent studies focused on investigating these factors, and this research builds upon this as well as exploring the efficacy of machine-learning for automated detection. In an experimental setting with voluntary test subjects, various factors were tested for their effect on detection probability: camera type (visible spectrum, RGB, and thermal infrared, TIR), time of day, camera angle, canopy density, and walking/stationary test subjects. The drone footage was analysed both manually by volunteers and through automated detection software. A generalised linear model with a logit link function was used to statistically analyse the data for both types of analysis. The findings concluded that using a TIR camera improved detection probability, particularly at dawn and with a 90° camera angle. An oblique angle was more effective during RGB flights, and walking/stationary test subjects did not influence detection with both cameras. Probability of detection decreased with increasing vegetation cover. Machine-learning software had a successful detection probability of 0.558, however, it produced nearly five times more false positives than manual analysis. Manual analysis, however, produced 2.5 times more false negatives than automated detection. Despite manual analysis producing more true positive detections than automated detection in this study, the automated software gives promising, successful results, and the advantages of automated methods over manual analysis make it a promising tool with the potential to be successfully incorporated into anti-poaching strategies.

scholarly journals Spatial and temporal analysis of natural resources degradation in the Likodra River watershed

2016 ◽  
pp. 169-188 ◽  
Author(s):  
Sinisa Polovina ◽  
Boris Radic ◽  
Ratko Ristic ◽  
Vukasin Milcanovic
Keyword(s):  
Natural Resources ◽  
Soil Degradation ◽  
Temporal Analysis ◽  
Potential Method ◽  
Northwestern Part ◽  
Main Stream ◽  
Factors Affecting ◽  
River Watershed ◽  
Erosion Processes ◽  
Small Streams

Soil is an important natural resource whose proper use requires a good knowledge of all endogenous and exogenous factors that cause different types of degradation. Erosion is one of the forms of soil degradation. Erosion processes are characterized by a distinctive complexity and the factors affecting them are dynamics and change in space and time. A complex system degradation requires a multidisciplinary approach to the use of modern methods and techniques. Today, a large number of models are available for the assessment of soil loss through erosion as well as the levels of risk from erosion, today. Most of these are based on the logics of GIS thanks to its ability to sublimate heterogeneous information. In this paper, the analysis of spatial and temporal degradation of natural resources is carried out in the Likodra River watershed. The Likodra River is located in the northwestern part of the Republic of Serbia, and is positioned in the municipality of Krupanj. The main stream in the immediate vicinity of the town of Krupanj formed from four small streams that have expressed torrential character (the Bogostica with the Krzava and the Cadjavica with the Brstica). In May 2014, the urban area and rural parts of the municipality Krupanj were affected by catastrophic flash floods that resulted in the loss of human lives and enormous material damage. Soil degradation in the study area was analyzed using the Erosion Potential Method (EPM). The method is characterized by a high degree of reliability for determining the intensity of erosion, calculation of sediment yield and transport. The advantage of this method compared to other methods its lower complexity in terms of quantity of input parameters, simplicity and the possibility of application in GIS. In addition, the method has the advantage of choice, because it was developed in this area. The method is based on the analytical processing of data on factors affecting erosion. As the erosion spatial phenomenon appears on the map according to the classification on the basis of the calculated analytical erosion coefficient (Z), which depends on the characteristics of the soil, vegetation cover, relief and visible degree of erosion. By applying the Erosion Potential Method (EPM) an erosion map has been developed, showing the spatial distribution of erosion processes in the catchment area of the Likodra River watershed. The erosion map provides an insight into the state of erosion processes of different intensity and character. For the study basin, all its visible manifestations are manifested in the medium coefficient of erosion Zsr = 0.204. The current state of erosion was analyzed in comparison with the situation in the original 1983 erosion map of FR Serbia.

The blackflies (Diptera: Simuliidae) of insular Newfoundland. III. Factors affecting the distribution and migration of larval simuliids in small streams on the Avalon Peninsula

1975 ◽  
Vol 53 (2) ◽  
pp. 114-123 ◽  
Author(s):  
David J. Lewis ◽  
Gordon F. Bennett
Keyword(s):  
Population Dynamics ◽  
Chemical Composition ◽  
Water Depth ◽  
Current Velocity ◽  
Substrate Type ◽  
Factors Affecting ◽  
Small Streams ◽  
And Migration ◽  
Avalon Peninsula ◽  
Significant Factors

Factors affecting the population dynamics, distribution, and migration of nine species of simuliid larvae in a complex of small streams on the Avalon Peninsula, Newfoundland, were studied. The most significant factors affecting the distribution and migration of simuliid larvae were current velocity, substrate type, and water depth; temperature, light, chemical composition of the water, and parasites were found to be of little or no significance.

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