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When is a species declining? Optimizing survey effort to detect population changes in reptiles.

ABSTRACT: Biodiversity monitoring programs need to be designed so that population changes can be detected reliably. This can be problematical for species that are cryptic and have imperfect detection. We used occupancy modeling and power analysis to optimize the survey design for reptile monitoring programs in the UK. Surveys were carried out six times a year in 2009-2010 at multiple sites. Four out of the six species--grass snake, adder, common lizard, slow-worm -were encountered during every survey from March-September. The exceptions were the two rarest species--sand lizard and smooth snake--which were not encountered in July 2009 and March 2010 respectively. The most frequently encountered and most easily detected species was the slow-worm. For the four widespread reptile species in the UK, three to four survey visits that used a combination of directed transect walks and artificial cover objects resulted in 95% certainty that a species would be detected if present. Using artificial cover objects was an effective detection method for most species, considerably increased the detection rate of some, and reduced misidentifications. To achieve an 85% power to detect a decline in any of the four widespread species when the true decline is 15%, three surveys at a total of 886 sampling sites, or four surveys at a total of 688 sites would be required. The sampling effort needed reduces to 212 sites surveyed three times, or 167 sites surveyed four times, if the target is to detect a true decline of 30% with the same power. The results obtained can be used to refine reptile survey protocols in the UK and elsewhere. On a wider scale, the occupancy study design approach can be used to optimize survey effort and help set targets for conservation outcomes for regional or national biodiversity assessments.

SUBMITTER: Sewell D

PROVIDER: S-EPMC3425567 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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When is a species declining? Optimizing survey effort to detect population changes in reptiles.

Sewell David D Guillera-Arroita Gurutzeta G Griffiths Richard A RA Beebee Trevor J C TJ

PloS one 20120822 8

Biodiversity monitoring programs need to be designed so that population changes can be detected reliably. This can be problematical for species that are cryptic and have imperfect detection. We used occupancy modeling and power analysis to optimize the survey design for reptile monitoring programs in the UK. Surveys were carried out six times a year in 2009-2010 at multiple sites. Four out of the six species--grass snake, adder, common lizard, slow-worm -were encountered during every survey from ...[more]

PMID: 22937044

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Project description:BackgroundBedside assessment of low levels of inspiratory effort, which are probably insufficient to prevent muscle atrophy, is challenging. The flow index, which is derived from the analysis of the inspiratory portion of the flow-time waveform, has been recently introduced as a non-invasive parameter to evaluate the inspiratory effort. The primary objective of the present study was to provide an external validation of the flow index to detect low inspiratory effort.MethodsDatasets containing flow, airway pressure, and esophageal pressure (Pes)-time waveforms were obtained from a previously published study in 100 acute brain-injured patients undergoing pressure support ventilation. Waveforms data were analyzed offline. A low inspiratory effort was defined by one of the following criteria, work of breathing (WOB) less than 0.3 J/L, Pes-time product (PTPes) per minute less than 50 cmH2O•s/min, or inspiratory muscle pressure (Pmus) less than 5 cmH2O, adding "or occurrence of ineffective effort more than 10%" for all criteria. The flow index was calculated according to previously reported method. The association of flow index with Pes-derived parameters of effort was investigated. The diagnostic accuracy of the flow index to detect low effort was analyzed.ResultsModerate correlations were found between flow index and WOB, Pmus, and PTPes per breath and per minute (Pearson's correlation coefficients ranged from 0.546 to 0.634, P < 0.001). The incidence of low inspiratory effort was 62%, 51%, and 55% using the definition of WOB, PTPes per minute, and Pmus, respectively. The area under the receiver operating characteristic curve for flow index to diagnose low effort was 0.88, 0.81, and 0.88, for the three respective definition. By using the cutoff value of flow index less than 2.1, the diagnostic performance for the three definitions showed sensitivity of 0.95-0.96, specificity of 0.57-0.71, positive predictive value of 0.70-0.84, and negative predictive value of 0.90-0.93.ConclusionsThe flow index is associated with Pes-based inspiratory effort measurements. Flow index can be used as a valid instrument to screen low inspiratory effort with a high probability to exclude cases without the condition.

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When is a species declining? Optimizing survey effort to detect population changes in reptiles.

Publications

When is a species declining? Optimizing survey effort to detect population changes in reptiles.

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