Occupancy

About: Occupancy is a research topic. Over the lifetime, 2757 publications have been published within this topic receiving 68288 citations.

Public Safety in the Urban–Wildland Interface: Should Fire-Prone Communities Have a Maximum Occupancy?

Abstract: Residential development in fire-prone wildlands is a growing problem for land-use and emergency planners. In many areas housing is increasing without commensurate improvement in the primary road network. This compromises public safety, as minimum evacuation times are climbing in tandem with vegetation and structural fuels. Current evacuation codes for fire-prone communities require a minimum number of exits regardless of the number of households. This is not as sophisticated as building egress codes which link the maximum occupancy in an enclosed space with the required number, capacity, and arrangement of exits. This paper applies concepts from building codes to fire-prone areas to highlight limitations in existing community egress systems. Preliminary recommendations for improved community evacuation codes are also presented.

Abundance, spatial variance and occupancy: arthropod species distribution in the Azores

Abstract: 1 The positive abundance-occupancy and abundance-variance relationships are two of the most widely documented patterns in population and community ecology 2 Recently, a general model has been proposed linking the mean abundance, the spatial variance in abundance, and the occupancy of species A striking feature of this model is that it consists explicitly of the three variables abundance, variance and occupancy, and no extra parameters are involved However, little is known about how well the model performs 3 Here, we show that the abundance-variance-occupancy model fits extremely well to data on the abundance, variance and occupancy of a large number of arthropod species in natural forest patches in the Azores, at three spatial extents, and distinguishing between species of different colonization status Indeed, virtually all variation about the bivariate abundance-occupancy and abundance-variance relationships is effectively explained by the third missing variable (variance in abundance in the case of the abundance-occupancy relationship, and occupancy in the case of the abundance-variance relationship) 4 Introduced species tend to exhibit lower densities, less spatial variance in these densities, and occupy fewer sites than native and endemic species None the less, they all lie on the same bivariate abundance-occupancy and abundance-variance, and trivariate abundance-variance-occupancy, relationships 5 Density, spatial variance in density, and occupancy appear to be all the things one needs to know to describe much of the spatial distribution of species

A spatially explicit approach to estimating species occupancy and spatial correlation.

Abstract: 1. Understanding and predicting the form of species distributions, or occupancy patterns, is fundamental to macroecology and is dependent on the identification of scaling relationships that underlie the patterns observed. 2. Occupancy-abundance models based on the negative binomial distribution and Taylor's power law are spatially implicit, rather than explicit, as they include no information on the relative positions of individuals. Here we present a spatially explicit model, the spatial scaling occupancy (SSO) model, to estimate species occupancy and spatial correlation, based on join-count statistics, or a pair approximation, approach. This model provides a spatially explicit description of species range size and aspects of range structure. 3. Occupancy data from Drosophilidae species inhabiting a decaying fruit mesocosm were used to test the SSO model. Predictions from the spatially implicit and explicit models were largely equally accurate. The SSO model is thus more efficient as it is less data demanding, and more informative as it provides an estimation of spatial correlation. 4. The results also showed that species distribution patterns differ when examined with spatially implicit vs. explicit approaches; the scaling relationship between occupancy and local density identifies a focal grain for studying the scale-dependent nature of ecological relationships; and the longer the length of the sample edge, the higher the occupancy observed under conditions of spatial aggregation. 5. The SSO model presents a step towards a general scaling model for occupancy, and demonstrates that the inclusion of spatially explicit information in macroecological models warrants further attention.