Rapid, recurring, structured survey versus bioblitz for generating biodiversity data and analysis with a multispecies abundance model

A bioblitz inexpensively and quickly generates biodiversity data, but bioblitzes are often conducted with haphazard, unreplicated sampling. Results tend to be taxonomically, geographically, or temporally biased, lack metadata, and consist of lists of observed taxa that do not enable further analyses or correction for imperfect detection. A rapid, recurring, structured survey (RRSS) uses a structured sampling design and temporal and spatial replication to survey randomly selected sites on a conservation property. We participated in a loosely structured bioblitz and a subsequent RRSS at Big Canoe Creek Nature Preserve in Springville (St. Clair County), Alabama (USA) to compare observed richness derived from the 2 survey approaches. The RRSS data structure enabled us to fit models that accounted for imperfect detection to estimate abundances, occupancy probabilities, and habitat associations. The loosely structured bioblitz data could not be used in such models. We present a new integrated multispecies abundance model that we applied to avian RRSS data. Our model extension enables estimation for the community, employs data augmentation to estimate the number of undetected species, and incorporates covariates. The RRSS generated a more comprehensive and less biased list of observed taxonomic richness than the loosely structured bioblitz (e.g., 73 vs. 45 bird species and 104 vs. 63 insect families from the RRSS vs. loosely structured bioblitz, respectively). Models fit to the RRSS data identified seasonal patterns in avian community composition and allowed for estimation of habitat-occupancy relationships for insect taxa. The RRSS protocol has potential for broad transferability as a standardized, quick, and inexpensive way to inventory biodiversity and estimate ecological parameters while providing an outreach opportunity.

Quantifying population declines based on presence-only records for red-list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy-modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red-list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence-only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.

Response variables for evaluation of the effectiveness of conservation corridors

Many studies have evaluated effectiveness of corridors by measuring species presence in and movement through small structural corridors. However, few studies have assessed whether these response variables are adequate for assessing whether the conservation goals of the corridors have been achieved or considered the costs or lag times involved in measuring the response variables. We examined 4 response variables-presence of the focal species in the corridor, interpatch movement via the corridor, gene flow, and patch occupancy--with respect to 3 criteria--relevance to conservation goals, lag time (fewest generations at which a positive response to the corridor might be evident with a particular variable), and the cost of a study when applying a particular variable. The presence variable had the least relevance to conservation goals, no lag time advantage compared with interpatch movement, and only a moderate cost advantage over interpatch movement or gene flow. Movement of individual animals between patches was the most appropriate response variable for a corridor intended to provide seasonal migration, but it was not an appropriate response variable for corridor dwellers, and for passage species it was only moderately relevant to the goals of gene flow, demographic rescue, and recolonization. Response variables related to gene flow provided a good trade-off among cost, relevance to conservation goals, and lag time. Nonetheless, the lag time of 10-20 generations means that evaluation of conservation corridors cannot occur until a few decades after a corridor has been established. Response variables related to occupancy were most relevant to conservation goals, but the lag time and costs to detect corridor effects on occupancy were much greater than the lag time and costs to detect corridor effects on gene flow.

Spatially explicit power analyses for occupancy-based monitoring of wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy-based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy-based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per-visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species.

[Are occupation and education interchangeable as social indicators in community health? A study in an employed population]

OBJECTIVE

Epidemiological studies and interventions to reduce inequalities in community health require the assignation of exhaustive and easy-to-obtain social indicators. Occupation and education are two of the most often used. In this study we attempt to evaluate the association between education and occupation among adult working population because if, in the absence of one of these two variables, it will be feasible to use the remaining with the lesser lost of socio-economic information.

DESIGN

From a representative sample (n = 3091) of general population (18-65 years old) drawn out from a prevalence survey on chronic disease risk factors performed in the Region of Murcia, a log-lineal analysis has been made between education and occupation among working people (65.8% of males and 34.2% of females from the original sample).

RESULTS

Men present significant association between managerial positions and university education. The association drops between clerks and high school graduates to increase among all manual workers with or without primary schooling education. Among women--with a lesser number of participants--the education/occupation association describes the same pattern but with higher magnitudes in the positive associations between managerial positions and university education. For both genders, the greatest associations are found in both diagonals of the education by occupation tables indicating: better occupation, more education, and the opposite.

CONCLUSIONS

The classification of working people according to education and occupation presents association, internal consistency and gradient. In absence of comprehensive information regarding occupation, education could be an alternative as socio-economic indicator.