Why Don't We Ask? A Complementary Method for Assessing the Status of Great Apes

Species conservation is difficult. Threats to species are typically high and immediate. Effective solutions for counteracting these threats, however, require synthesis of high quality evidence, appropriately targeted activities, typically costly implementation, and rapid re-evaluation and adaptation. Conservation management can be ineffective if there is insufficient understanding of the complex ecological, political, socio-cultural, and economic factors that underlie conservation threats. When information about these factors is incomplete, conservation managers may be unaware of the most urgent threats or unable to envision all consequences of potential management strategies. Conservation research aims to address the gap between what is known and what knowledge is needed for effective conservation. Such research, however, generally addresses a subset of the factors that underlie conservation threats, producing a limited, simplistic, and often biased view of complex, real world situations. A combination of approaches is required to provide the complete picture necessary to engage in effective conservation. Orangutan conservation (Pongo spp.) offers an example: standard conservation assessments employ survey methods that focus on ecological variables, but do not usually address the socio-cultural factors that underlie threats. Here, we evaluate a complementary survey method based on interviews of nearly 7,000 people in 687 villages in Kalimantan, Indonesia. We address areas of potential methodological weakness in such surveys, including sampling and questionnaire design, respondent biases, statistical analyses, and sensitivity of resultant inferences. We show that interview-based surveys can provide cost-effective and statistically robust methods to better understand poorly known populations of species that are relatively easily identified by local people. Such surveys provide reasonably reliable estimates of relative presence and relative encounter rates of such species, as well as quantifying the main factors that threaten them. We recommend more extensive use of carefully designed and implemented interview surveys, in conjunction with more traditional field methods

A theory for ecological survey methods to map individual distributions

Spatially explicit approaches are widely recommended for ecosystem management. The quality of the data, such as presence/absence or habitat maps, affects the management actions recommended and is, therefore, key to management success. However, available data are often biased and incomplete. Previous studies have advanced ways to resolve data bias and missing data, but questions remain about how we design ecological surveys to develop a dataset through field surveys. Ecological surveys may have multiple spatial scales, including the spatial extent of the target ecosystem (observation window), the resolution for mapping individual distributions (mapping unit), and the survey area within each mapping unit (sampling unit). We developed an ecological survey method for mapping individual distributions by applying spatially explicit stochastic models. We used spatial point processes to describe individual spatial placements using either random or clustering processes. We then designed ecological surveys with different spatial scales and individual detectability. We found that the choice of mapping unit affected the presence mapped fraction, and the fraction of the total individuals covered by the presence mapped patches. Tradeoffs were found between these quantities and the map resolution, associated with equivalent asymptotic behaviors for both metrics at sufficiently small and large mapping unit scales. Our approach enabled consideration of the effect of multiple spatial scales in surveys, and estimation of the survey outcomes such as the presence mapped fraction and the number of individuals situated in the presence detected units. The developed theory may facilitate management decision-making and inform the design of monitoring and data gathering

Dispersion in oscillatory flows

The enhanced axial mixing which is caused by dispersion in oscillatory flows in some mass transfer devices may limit the reactor performance. This effect has provided the motivation for the present study in which oscillatory flow dispersion in a flat channel of large aspect ratio is investigated. The rate of spreading of a uniform slug of some passive tracer has been predicted using numerical and analytical techniques and the results have been verified experimentally. The numerical approach has used a finite difference time-marching method to obtain predictions for the channel concentrations. From the results, the dispersion coefficient (D) has been evaluated for Strouhal numbers of O.O1→0.2 and for mean Reynolds numbers of O.4→2OO at Schmidt numbers (Sc) O(1O³) . It has been concluded that under these conditions D varies as stroke squared. Unless the flow is not quasi-steady (i.e. if pulsatile Reynolds number α²O(l)) D is only a weak function of frequency. These predictions for the dispersion coefficient have been in excellent agreement with those of Watson (256). It has also been concluded from the numerical study that the phase of the velocity sinusoid at the instant of injection has a critical effect upon the form of the concentration evolution. An approximate analytical technique has been developed in which weighted mean cross-channel concentrations are defined. The wall concentration is expressed approximately using a Fourier series. This procedure leads to ordinary differential equations for the axial moments. When the axial variance of mean concentration and the dispersion coefficient were computed in this way for quasi-steady flows good agreement was obtained with the numerical work. Simple opto-electronic gauges have been developed to measure mean cross-channel concentrations. The sensors have been used to obtain experimental data for the dispersion coefficient of a furrowed channel mass transfer device using slug stimulus techniques. Experimental investigations of dispersion in oscillatory flows in a flat channel using these gauges has produced values for D which are in agreement with the theoretical predictions for quasi-steady flows.</p

Synthetic and composite estimation under a superpopulation model

Small area estimation, Model-design setup, Optimality of BLUE and BLUP,

On kernel nonparametric regression designed for complex survey data

Bandwidth, Design-based inference, Local linear regression, Local polynomial regression, Model-based inference, Nonparametric regression, Sampling weights, Survey sampling,