Significant Predictors Of Abundance Research Articles

A low-altitude mountain range as an important refugium for two narrow endemics in the Southwest Australian Floristic Region biodiversity hotspot.

Low-altitude mountains constitute important centres of diversity in landscapes with little topographic variation, such as the Southwest Australian Floristic Region (SWAFR). They also provide unique climatic and edaphic conditions that may allow them to function as refugia. We investigate whether the Porongurups (altitude 655 m) in the SWAFR will provide a refugium for the endemic Ornduffia calthifolia and O. marchantii under forecast climate change. We used species distribution modelling based on WorldClim climatic data, 30-m elevation data and a 2-m-resolution LiDAR-derived digital elevation model (DEM) to predict current and future distributions of the Ornduffia species at local and regional scales based on 605 field-based abundance estimates. Future distributions were forecast using RCP2.6 and RCP4.5 projections. To determine whether local edaphic and biotic factors impact these forecasts, we tested whether soil depth and vegetation height were significant predictors of abundance using generalized additive models (GAMs). Species distribution modelling revealed the importance of elevation and topographic variables at the local scale for determining distributions of both species, which also preferred shadier locations and higher slopes. However, O. calthifolia occurred at higher (cooler) elevations with rugged, concave topography, while O. marchantii occurred in disturbed sites at lower locations with less rugged, convex topography. Under future climates both species are likely to severely contract under the milder RCP2.6 projection (approx. 2 °C of global warming), but are unlikely to persist if warming is more severe (RCP4.5). GAMs showed that soil depth and vegetation height are important predictors of O. calthifolia and O. marchantii distributions, respectively. The Porongurups constitute an important refugium for O. calthifolia and O. marchantii, but limits to this capacity may be reached if global warming exceeds 2 °C. This capacity is moderated at local scales by biotic and edaphic factors.

Evaluation of two methods for quantifying passeriform lice

Two methods commonly used to quantify ectoparasites on live birds are visual examination and dust-ruffling. Visual examination provides an estimate of ectoparasite abundance based on an observer's timed inspection of various body regions on a bird. Dust-ruffling involves application of insecticidal powder to feathers that are then ruffled to dislodge ectoparasites onto a collection surface where they can then be counted. Despite the common use of these methods in the field, the proportion of actual ectoparasites they account for has only been tested with Rock Pigeons (Columba livia), a relatively large-bodied species (238-302 g) with dense plumage. We tested the accuracy of the two methods using European Starlings (Sturnus vulgaris; ~75 g). We first quantified the number of lice (Brueelia nebulosa) on starlings using visual examination, followed immediately by dust-ruffling. Birds were then euthanized and the proportion of lice accounted for by each method was compared to the total number of lice on each bird as determined with a body-washing method. Visual examination and dust-ruffling each accounted for a relatively small proportion of total lice (14% and 16%, respectively), but both were still significant predictors of abundance. The number of lice observed by visual examination accounted for 68% of the variation in total abundance. Similarly, the number of lice recovered by dust-ruffling accounted for 72% of the variation in total abundance. Our results show that both methods can be used to reliably quantify the abundance of lice on European Starlings and other similar-sized passerines.

Model selection, zero‐inflated models, and predictors of primate abundance in Korup National Park, Cameroon

Determining the ecological and anthropogenic factors that shape the abundance and distribution of wild primates is a critical component of primate conservation research. Such research is complicated, however, whenever the species under study are encountered infrequently, a characteristic of many taxa that are threatened with extinction. Typically, the resulting data sets based on surveys of such species will have a high frequency of zero counts which makes it difficult to determine the predictor variables that are associated with species abundance. In this study, we test various statistical models using survey data that was gathered on seven species of primate in Korup National Park, Cameroon. Predictor variables include hunting signs and aspects of habitat structure and floristic composition. Our statistical models include zero-inflated models that are tailored to deal with a high frequency of zero counts. First, using exploratory data analysis we found the most informative set of models as ranked by Δ-AIC (Akaike's information criterion). On the basis of this analysis, we used five predictor variables to construct several regression models including Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial. Total basal area of all trees, density of secondary tree species, hunting signs, and mean basal area of all trees were significant predictors of abundance in the zero-inflated models. We discuss the statistical logic behind zero-inflated models and provide an interpretation of parameter estimates. We recommend that researchers explore a variety of models when determining the factors that correlate with primate abundance.

Species distribution modelling of ancient cattle from early Neolithic sites in SW Asia and Europe

Species distribution models are widely used by ecologists to estimate the relationship between environmental predictors and species presence and abundance records. In this paper, we use compiled faunal assemblage records from archaeological sites located across southwest Asia and southeast Europe to estimate and to compare the biogeography of ancient wild and early domestic cattle ( Bos primigenius and Bos taurus). We estimate the contribution of multiple environmental parameters on the explanation of variation in abundance of cattle remains from archaeological sites, and find that annual precipitation and maximum annual temperature are significant predictors of abundance. We then formulate, test, and confirm a hypothesis that states the process of cattle domestication involves a change in the types of environmental ranges in which cattle exploitation occurred by applying a species distribution model to presence-only data of wild and domestic cattle. Our results show that there is an expansion of cattle rearing in more temperate environments, which is a defining characteristic of the European early Neolithic.

Landscape effects mediate breeding bird abundance in midwestern forests

We examine the influence of both local habitat and landscape variables on avian species abundance at forested study sites situated within fragmented and contiguous landscapes. The study was conducted over a six year period (1991–1996) at 10 study sites equally divided between the heavily forested Missouri Ozarks and forest fragments in central Missouri. We found greater species richness and diversity in the fragments, but there was a higher percentage of Neotropical migrants in the Ozarks. We found significant differences in the mean number of birds detected between the central Missouri fragments and the unfragmented Ozarks for 15 (63%) of 24 focal species. We used stepwise regression to determine which of 12 local vegetation variables and 4 landscape variables (forest cover, core area, edge density, and mean patch size) accounted for the greatest amount of variation in abundance for 24 bird species. Seven species (29%) were most sensitive to local vegetation variables, while 16 species (67%) responded most strongly to one of four landscape variables. Landscape variables are significant predictors of abundance for many bird species; resource managers should consider multiple measures of landscape sensitivity when making bird population management decisions.