Canopy structural modeling using object-oriented image classification and laser scanning

A terrestrial laser scanning (TLS) experiment was carried out in the EAGLE 2006 campaign to characterize and model the canopy structure of the Speulderbos forest. Semi-variogram analysis was used to describe spatial variability of the surface. The dependence of the spatial variability on the applied grid size showed, that in this forest spatial details of the digital surface model are lost in the case of larger than 0.3-0.4 m grid size. Voxel statistics was used for describing the density of the canopy structure. Five zones of the canopy were identified according to their density distribution. Basic geometric structures were tested for modeling the forest at the individual tree level. The results create a firm basis for modeling physical processes in the canopy

Report on estimating the size of dolphin schools, based on data obtained during a charter cruise of the M/V Gina Anne, October 11 -November 25, 1979

Estimates of dolphin school sizes made by observers and crew members aboard tuna seiners or by observers on ship or aerial surveys are important components of population estimates of dolphins which are involved in the yellowfin tuna fishery in the eastern Pacific. Differences in past estimates made from tuna seiners and research ships and aircraft have been noted by Brazier (1978). To compare various methods of estimating dolphin school sizes a research cruise was undertaken with the following major objectives: 1) compare estimates made by observers aboard a tuna seiner and in the ship's helicopter, from aerial photographs, and from counts made at the backdown channel, 2) compare estimates of observers who are told the count of the school size after making their estimate to the observer who is not aware of the count to determine if observers can learn to estimate more accurately, and 3) obtain movie and still photographs of dolphin schools of known size at various stages of chase, capture and release to be used for observer training. The secondary objectives of the cruise were to: 1) obtain life history specimens and data from any dolphins that were killed incidental to purse seining. These specimens and data were to be analyzed by the U.S. National Marine Fisheries Service ( NMFS ) , 2) record evasion tactics of dolphin schools by observing them from the helicopter while the seiner approached the school, 3) examine alternative methods for estimating the distance and bearing of schools where they were first sighted, 4) collect the Commission's standard cetacean sighting, set log and daily activity data and expendable bathythermograph data. (PDF contains 31 pages.

Community Change within a Caribbean Coral Reef Marine Protected Area following Two Decades of Local Management

Structural change in both the habitat and reef-associated fish assemblages within spatially managed coral reefs can provide key insights into the benefits and limitations of Marine Protected Areas (MPAs). While MPA zoning effects on particular target species are well reported, we are yet to fully resolve the various affects of spatial management on the structure of coral reef communities over decadal time scales. Here, we document mixed affects of MPA zoning on fish density, biomass and species richness over the 21 years since establishment of the Saba Marine Park (SMP). Although we found significantly greater biomass and species richness of reef-associated fishes within shallow habitats (5 meters depth) closed to fishing, this did not hold for deeper (15 m) habitats, and there was a widespread decline (38% decrease) in live hard coral cover and a 68% loss of carnivorous reef fishes across all zones of the SMP from the 1990s to 2008. Given the importance of live coral for the maintenance and replenishment of reef fishes, and the likely role of chronic disturbance in driving coral decline across the region, we explore how local spatial management can help protect coral reef ecosystems within the context of large-scale environmental pressures and disturbances outside the purview of local MPA management.Funding was provided by the Saba Conservation Foundation ((SCF), King Abdullah University of Science and Technology, The Australian National University and Australian Research Council. The funders had no role in study design and analysis, decision to publish, or preparation of the manuscript. Staff of the SCF were involved in data collection

Distance sampling with a random scale detection function

Cornelia Oedekoven was supported by a studentship jointly funded by the University of St Andrews and EP-SRC, through the National Centre for Statistical Ecology (EP-SRC Grant EP/C522702/1). Hans Skaug thanks the Center for Stock Assessment Research for facilitating his visit to University of California, Santa Cruz.Distance sampling was developed to estimate wildlife abundance from observational surveys with uncertain detection in the search area. We present novel analysis methods for estimating detection probabilities that make use of random effects models to allow for unmodeled heterogeneity in detection. The scale parameter of the half-normal detection function is modeled by means of an intercept plus an error term varying with detections, normally distributed with zero mean and unknown variance. In contrast to conventional distance sampling methods, our approach can deal with long-tailed detection functions without truncation. Compared to a fixed effect covariate approach, we think of the random effect as a covariate with unknown values and integrate over the random effect. We expand the random scale to a mixed scale model by adding fixed effect covariates. We analyzed simulated data with large sample sizes to demonstrate that the code performs correctly for random and mixed effect models. We also generated replicate simulations with more practical sample sizes (∼100) and compared the random scale half-normal with the hazard rate detection function. As expected each estimation model was best for different simulation models. We illustrate the mixed effect modeling approach using harbor porpoise vessel survey data where the mixed effect model provided an improved model fit in comparison to a fixed effect model with the same covariates. We propose that a random or mixed effect model of the detection function scale be adopted as one of the standard approaches for fitting detection functions in distance sampling.PostprintPeer reviewe