Showing papers by "Ralph Charles Mac Nally published in 2003"

Effects of floristics, physiognomy and non‐native vegetation on riparian bird communities in a Mojave Desert watershed

Abstract: Summary 1. In the deserts of the south-western United States of America, as in many ecoregions around the world, invasion of non-native plants is modifying the structure and composition of riparian vegetation. 2. Restoration of native plant species frequently proves to be ecologically and economically difficult. In the Muddy River drainage in the Mojave Desert (Nevada, USA), eradication of one the most aggressive invasive plants, Tamarix ramosissima (saltcedar), often reduces the structural and compositional diversity of the remaining vegetation. This can have negative effects on native animals, including birds. 3. The objectives of our work were (i) to examine relationships between avian diversity and measures of vegetational diversity (species richness, dominance of non-native plants and vegetation structure [total vegetation volume]), (ii) to explore the extent to which avian community composition was associated with vegetation composition (floristics) or vegetation structure (physiognomy), and (iii) to consider the potential effects of alternative land management and ecological restoration strategies on the biodiversity of birds and other native fauna in watersheds in the arid south-western USA. 4. Species richness of all birds and of breeding birds was best modelled by total vegetation volume alone. Neither species richness of plants nor dominance of non-native plants had a statistically significant effect on species richness, abundance or evenness of birds. 5. Species composition of birds between sites was more similar when floristics was more similar, and vice versa. Species composition of birds was not correlated with physiognomy. 6. Species richness of native birds in the Muddy River drainage appears not to suffer from invasion of non-native plants, provided that the vegetational community retains sufficient structural diversity. 7. The composition of the bird community is closely related to floristics, and other taxonomic groups may exhibit different responses to vegetation structure and composition. Therefore, explicit strategies for landscape-scale management, restoration and maximization of native faunal diversity should consider how removal of invasive plants may affect physiognomy and floristics of the vegetational community as a whole.

Validation Tests of Predictive Models of Butterfly Occurrence Based on Environmental Variables

Abstract: Ecologists often seek to predict species distributions as functions of abiotic environmental vari- ables. Statistical models are useful for making predictions about the occurrence of species based on variables derived from remote sensing or geographic information systems. We previously used 14 topographically based environmental variables from 49 locations in the Toquima Range (Nevada, U.S.A.) and species inven- tories conducted over 4 years (1996-1999) to model logistically the occurrence of resident butterfly species. To test the models, we collected new validation data in 39 locations in the nearby Shoshone Mountains in 2000-2001. We used a series of "classification rules" based on conventional logistic and Bayesian criteria to assess the success rates of predictions. The classification rules represented a gradient of stringency in the "cer- tainty" with which predictions were made. More stringent rules reduced the number of predictions made but greatly increased the success rate of predictions. For comparisons of classification rules making similar num- bers of predictions, conventional logistic and Bayesian criteria produced similar outcomes. Success rates for predicted absences were uniformly higher than for predicted presences. Increasing the temporal extent of data from 1 to 2 years elevated success rates for predicted presences but decreased success rates for predicted absences, leaving the overall success rates essentially the same. Although species occurrence rates (the propor- tion of locations in which each species was found) were correlated between the modeling and validation data sets, occurrence rates for many species increased or decreased substantially; erroneous predictions were more likely for those taxa. Model fit (measured by the explained deviance) was an indicator of the probable success rate of predicted presences but not of predicted absences or overall success rates. We suggest that clas- sification rules for predicting likely presences and absences may be decoupled to improve overall predictive success. Our general framework for modeling species occurrence is applicable to virtually any taxonomic group or ecosystem.

Distinguishing between signal and noise in faunal responses to environmental change

Abstract: Aim We tested whether variation in snapshots of butterfly species composition and species richness taken from one to six years apart could be interpreted as an ecologically meaningful trend or whether they might merely reflect stochasticity. Location Field research was conducted in the Toquima Range and Shoshone Mountains, Lander and Nye counties, Nevada, USA. Methods We obtained data for 49 sites in the Toquima Range from 1996 to 2002 and 39 sites in the Shoshone Mountains from 2000 to 2002. Sites spanned the gradient of local topographic and climatic conditions in those mountain ranges. Data on species composition and species richness were based on comprehensive field inventories. We calculated similarity of species composition using the Jaccard index. We conducted one-factor repeated-measures analyses of variance to test whether the distribution of similarity of species composition and the distribution of mean species richness depended on the number of years between inventories. Results In both mountain ranges, much less of the difference in species composition was attributable to turnover of species composition within sites over time than to spatial differences among sites. Annual species richness in the Toquima Range was more variable than in the Shoshone Mountains, but again far less of the variation in species richness was attributable to year than to differences among sites. Main conclusions Despite the fact that desert ecosystems are not expected to be highly resilient to global environmental change, there may be a time lag between deterministic environmental changes and a detectable faunal response, even in taxonomic groups that are known to be sensitive to changes in climate and vegetation. Although information on species richness and similarity of species composition are among the most practical data to collect in managed landscapes, these measures may not be highly sensitive to environmental changes over the short to moderate term.

Linking models of species occurrence and landscape reconstructions, 2002-2003

Abstract: Ecologists and land managers around the world are charged with first arresting and then reversing declines in native species. Revegetation has been proposed as one of the mechanisms by which landscapes can be rehabilitated to support viable populations of native wildlife. Because large-scale revegetation often proves to be technically difficult and costly, it is critical to evaluate the likely outcome of alternative proposals for landscape reconstruction. Here we describe a new approach for examining the potential effects of spatially extensive ecological restoration on species of concern. Our method links validated models of species occurrence with GIS-based models of various revegetation scenarios to estimate the range of biodiversity responses under each option. Explaining and predicting species occurrence long has been a major goal in ecology, conservation biology, and wildlife management (Rosenzweig 1995, Mac Nally 1995, Bell 2001). There are many possible ways to predict species occurrence. Traditional ‘habitat modeling’-predicting occurrence as a function of resource requirements, such as food sources or nesting sites-may have a high probability of success (Hanski 1999, Miller and Cale 2000), but obtaining such data can be expensive, particularly over extensive areas. Therefore, predicting species occurrence as a function of environmental variables that can be quantified easily, at small spatial grains, and over large areas, is appealing (Austin et al. 1990, Guisan and Zimmerman 2000, Jackson et al. 2000). We recently developed a statistically rigorous framework for examining the generality of predictors of species occurrence using an iterative process of model building, testing, and refinement (Fleishman et al. 2001, in press). We make extensive use of Bayes-based methods, which facilitate more detailed and practical assessment and improvement of predictions than conventional approaches (Ellison 1996, Sit and Taylor 1998). Our framework seeks to identify predictors of species occurrence at grain sizes on the order of several km2 over extents of 100s to 1000s of km2. This corresponds to the scale at which many landuse decisions must be made. To be useful, the predictions of species-occurrence models must be tested using explicit standards (Guisan and Zimmerman 2000, Jackson et al. 2000). We test our models-which effectively are hypotheses about predictors of species distributions-using independent data that were not used to build the models (Fleishman et al. in press). The process of generating and testing model predictions increases our understanding of relationships between organisms and environmental variables and contributes to the scientific foundation for regional conservation and management (Mac Nally and Bennett 1997, Hawkins et al. 2000, Mac Nally et al. 2000). Species-specific occurrence modeling has been employed widely in the past (Braithwaite et al. 1989, Lindenmayer et al. 1990, Scott et al. 2002), but occurrence models rarely have been linked with GIS-based models of alternative management strategies or revegetated landscapes (Bennett 1999, Marzluff et al. 2002). The alternatives we develop are based on ecological vegetation classes, which are defined as one or more similar floristic communities that exist under a common regime of ecological processes and that are linked to broad landscape features (Muir et al. 1995). Because ecological vegetation classes are closely connected with broad-scale topographic, edaphic, and climatic variables, they are a useful link between vegetation and landscape-scale planning and management. Alternatives vary with respect to the amount and spatial configuration of different ecological vegetation classes. Our approach recognizes that not only is there a spectrum of habitat quality (McIntyre and Barrett 1992), but also that animals respond to more than one vegetational community (Mac Nally et al. 2002). Connecting occurrence models with revegetation models allows us to estimate the quantity and distribution of suitable habitat for each species that would be available under each scenario. By treating models for individual species as probabilistic, we can generate ranges of outcomes (i.e., confidence intervals) for each alternative. Thus, we can gauge the overall potential of each alternative to achieve specified ecological objectives.