scholarly journals Estimation of breeding probability can make monitoring data more revealing: a case study of amphibians

2021 ◽  
Author(s):  
Sam S. Cruickshank ◽  
Ariel Bergamini ◽  
Benedikt R. Schmidt
Author(s):  
Vanessa Tobias ◽  

In fisheries monitoring, catch is assumed to be a product of fishing intensity, catchability, and availability, where availability is defined as the number or biomass of fish present and catchability refers to the relationship between catch rate and the true population. Ecological monitoring programs use catch per unit of effort (CPUE) to standardize catch and monitor changes in fish populations; however, CPUE is proportional to the portion of the population that is vulnerable to the type of gear used in sampling, which is not necessarily the entire population. Programs often deal with this problem by assuming that catchability is constant, but if catchability is not constant, it is not possible to separate the effects of catchability and population size using monitoring data alone. This study uses individual-based simulation to separate the effects of changing environmental conditions on catchability and availability in environmental monitoring data. The simulation combines a module for sampling conditions with a module for individual fish behavior to estimate the proportion of available fish that would escape from the sample. The method is applied to the case study of the well monitored fish species Delta Smelt (Hypomesus transpacificus) in the San Francisco Estuary, where it has been hypothesized that changing water clarity may affect catchability for long-term monitoring studies. Results of this study indicate that given constraints on Delta Smelt swimming ability, it is unlikely that the apparent declines in Delta Smelt abundance are the result of changing water clarity affecting catchability.


Author(s):  
Vanessa Tobias

In fisheries monitoring, catch is assumed to be a product of fishing intensity, catchability, and availability, where availability is defined as the number or biomass of fish present and catchability refers to the relationship between catch rate and the true population. Ecological monitoring programs use catch per unit of effort (CPUE) to standardize catch and monitor changes in fish populations; however, CPUE is proportional to the portion of the population that is vulnerable to the type of gear that is used in sampling, which is not necessarily the entire population. Programs often deal with this problem by assuming that catchability is constant, but if catchability is not constant, it is not possible to separate the effects of catchability and population size using monitoring data alone. This study uses individual-based simulation to separate the effects of changing environmental conditions on catchability and availability in environmental monitoring data. The simulation combines a module for sampling conditions with a module for individual fish behavior to estimate the proportion of available fish that would escape from the sample. The method is applied to the case study of the well-monitored fish species Delta Smelt (Hypomesus transpacificus) in the San Francisco Estuary, where it has been hypothesized that changing water clarity may affect catchability for long-term monitoring studies. Results of this study indicate that given constraints on Delta Smelt swimming ability, it is unlikely that the apparent declines in Delta Smelt abundance are due to an effect of changing water clarity on catchability.


2010 ◽  
Vol 16 (2) ◽  
pp. 76 ◽  
Author(s):  
Joanne M. Hoare ◽  
Colin F. J. O’Donnell ◽  
Elaine F. Wright

Indicator species approaches are widely used in conservation as a shortcut to measuring attributes of species and ecosystems. A variety of indicator species concepts are in use and are applicable to a range of situations. Indicator species are increasingly being used in environmental reporting to evaluate trends in environmental attributes quantitatively. We use the most recent State of the Environment report from New Zealand as a case study to evaluate: (1) how indicator species concepts are being applied to environmental reporting and (2) the selection of individual species as indicators. At present indicator species used in environmental reporting in New Zealand reflect biases in national monitoring data towards forest-dwelling, terrestrial vertebrates that are vulnerable to predation by introduced mammals. Scientific literature generally supports links between selected taxa and the aspect of ecosystem health they are purported to indicate, but their roles as long-term indicators of environmental health have yet to be evaluated. A primary goal of State of the Environment reporting is to set a benchmark against which environmental outcomes can be monitored over time; thus it is recognized that taxa reported should represent a broader range of environmental attributes. However, selection of taxa for environmental reporting is severely constrained by limited national species monitoring data. A strategic approach to national measurement, storage and analysis of long-term monitoring data is required to support selection of representative species for environmental reporting. We support current initiatives to select taxa for future measurement and reporting in an objective, transparent manner and recommend that they encompass representation of: (1) taxonomic diversity, (2) ecosystem types, (3) key environmental pressures and (4) threat status.


2019 ◽  
Vol 81 ◽  
pp. 225-237 ◽  
Author(s):  
Jixian Cui ◽  
Jianlei Lang ◽  
Tian Chen ◽  
Shushuai Mao ◽  
Shuiyuan Cheng ◽  
...  

1993 ◽  
Vol 27 (3) ◽  
pp. 201-219 ◽  
Author(s):  
Michael R. Stoline ◽  
Richard N. Passero ◽  
Michael J. Barcelona

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1934
Author(s):  
Adrienne Fung ◽  
Roger Babcock

Collection systems in coastal cities are often below the groundwater table, leading to groundwater infiltration (GWI) through defects such as cracks and poor lateral connections. Climate-change-induced sea level rise (SLR) will raise groundwater levels, increasing the head and thus the inflow. A method has been developed to predict GWI when groundwater levels change using calibration with sewershed flow monitoring data. The calibration results in a parameter that characterizes the porosity of the collection system. A case study is presented for a coastal city with reliable flow monitoring data for eight days that resulted in a large range of effective defect sizes (minimum 0.0044 to maximum 0.338 radians), however, the range of predicted future GWI in currently submerged pipes varied by only 12% from the mean. The mean effective defect predicts 70 to 200% increases in GWI due to SLR of 0.3 to 0.9 m (1 to 3 ft), respectively, for currently submerged pipes. Predicted additional GWI for pipes that will become submerged due to SLR will increase GWI to values that approach or exceed the current average dry weather flow. This methodology can be used for planning of infrastructure improvements to enhance resiliency in coastal communities.


2013 ◽  
Vol 14 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Fabian Fischer ◽  
Johannes Fuchs ◽  
Florian Mansmann ◽  
Daniel A Keim

The enormous growth of data in the last decades led to a wide variety of different database technologies. Nowadays, we are capable of storing vast amounts of structured and unstructured data. To address the challenge of exploring and making sense out of big data using visual analytics, the tight integration of such backend services is needed. In this article, we introduce BANKSAFE, which was built for the VAST Challenge 2012 and won the outstanding comprehensive submission award. BANKSAFE is based on modern database technologies and is capable of visually analyzing vast amounts of monitoring data and security-related datasets of large-scale computer networks. To better describe and demonstrate the visualizations, we utilize the Visual Analytics Science and Technology (VAST) Challenge 2012 as case study. Additionally, we discuss lessons learned during the design and development of BANKSAFE, which are also applicable to other visual analytics applications for big data.


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