Efficient species-level monitoring at the landscape scale.

Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance.

Framework to evaluate ecological and social outcomes of collaborative management: lessons from implementation with a northern Arizona collaborative group.

As collaborative groups gain popularity as an alternative means for addressing conflict over management of public lands, the need for methods to evaluate their effectiveness in achieving ecological and social goals increases. However, frameworks that examine both effectiveness of the collaborative process and its outcomes are poorly developed or altogether lacking. This paper presents and evaluates the utility of the holistic ecosystem health indicator (HEHI), a framework that integrates multiple ecological and socioeconomic criteria to evaluate management effectiveness of collaborative processes. Through the development and application of the HEHI to a collaborative in northern Arizona, the Diablo Trust, we present the opportunities and challenges in using this framework to evaluate the ecological and social outcomes of collaborative adaptive management. Baseline results from the first application of the HEHI are presented as an illustration of its potential as a co-adaptive management tool. We discuss lessons learned from the process of selecting indicators and potential issues to their long-term implementation. Finally, we provide recommendations for applying this framework to monitoring and adaptive management in the context of collaborative management.

Prioritizing conservation effort through the use of biological soil crusts as ecosystem function indicators in an arid region.

Conservation prioritization usually focuses on conservation of rare species or biodiversity, rather than ecological processes. This is partially due to a lack of informative indicators of ecosystem function. Biological soil crusts (BSCs) trap and retain soil and water resources in arid ecosystems and function as major carbon and nitrogen fixers; thus, they may be informative indicators of ecosystem function. We created spatial models of multiple indicators of the diversity and function of BSCs (species richness, evenness, functional diversity, functional redundancy, number of rare species, number of habitat specialists, nitrogen and carbon fixation indices, soil stabilization, and surface roughening) for the 800,000-ha Grand Staircase-Escalante National Monument (Utah, U.S.A.). We then combined the indicators into a single BSC function map and a single BSC biodiversity map (2 alternative types of conservation value) with an unweighted averaging procedure and a weighted procedure derived from validations performance. We also modeled potential degradation with data from a rangeland assessment survey. To determine which areas on the landscape were the highest conservation priorities, we overlaid the function- and diversity-based conservation-value layers on the potential degradation layer. Different methods for ascribing conservation-value and conservation-priority layers all yielded strikingly similar results (r= 0.89-0.99), which suggests that in this case biodiversity and function can be conserved simultaneously. We believe BSCs can be used as indicators of ecosystem function in concert with other indicators (such as plant-community properties) and that such information can be used to prioritize conservation effort in drylands.

Predicting abundance of desert riparian birds: validation and calibration of the Effective Area Model.

Reliable prediction of the effects of landscape change on species abundance is critical to land managers who must make frequent, rapid decisions with long-term consequences. However, due to inherent temporal and spatial variability in ecological systems, previous attempts to predict species abundance in novel locations and/or time frames have been largely unsuccessful. The Effective Area Model (EAM) uses change in habitat composition and geometry coupled with response of animals to habitat edges to predict change in species abundance at a landscape scale. Our research goals were to validate EAM abundance predictions in new locations and to develop a calibration framework that enables absolute abundance predictions in novel regions or time frames. For model validation, we compared the EAM to a null model excluding edge effects in terms of accurate prediction of species abundance. The EAM outperformed the null model for 83.3% of species (N=12) for which it was possible to discern a difference when considering 50 validation sites. Likewise, the EAM outperformed the null model when considering subsets of validation sites categorized on the basis of four variables (isolation, presence of water, region, and focal habitat). Additionally, we explored a framework for producing calibrated models to decrease prediction error given inherent temporal and spatial variability in abundance. We calibrated the EAM to new locations using linear regression between observed and predicted abundance with and without additional habitat covariates. We found that model adjustments for unexplained variability in time and space, as well as variability that can be explained by incorporating additional covariates, improved EAM predictions. Calibrated EAM abundance estimates with additional site-level variables explained a significant amount of variability (P < 0.05) in observed abundance for 17 of 20 species, with R2 values >25% for 12 species, >48% for six species, and >60% for four species when considering all predictive models. The calibration framework described in this paper can be used to predict absolute abundance in sites different from those in which data were collected if the target population of sites to which one would like to statistically infer is sampled in a probabilistic way.

Butterfly edge effects are predicted by a simple model in a complex landscape.

Edge responses have been studied for decades and form a critical component of our understanding of how organisms respond to landscape structure and habitat fragmentation. Until recently, however, the lack of a general, conceptual framework has made it difficult to make sense of the patterns and variability reported in the edge literature. We present a test of an edge effects model which predicts that organisms should avoid edges with less-preferred habitat, show increased abundance near edges with preferred habitat or habitat containing complementary resources, and show no response to edges with similar-quality habitat that offers only supplementary resources. We tested the predictions of this model against observations of the edge responses of 15 butterfly species at 12 different edge types within a complex, desert riparian landscape. Observations matched model predictions more than would be expected by chance for the 211 species/edge combinations tested over 3 years of study. In cases where positive or negative edge responses were predicted, observed responses matched those predictions 70% of the time. While the model tends to underpredict neutral results, it was rare that an observed edge response contradicted that predicted by the model. This study also supported the two primary ecological mechanisms underlying the model, although not equally. We detected a positive relationship between habitat preferences and the slope of the observed edge response, suggesting that this basic life history trait underlies edge effects and influences their magnitude. Empirical evidence also suggested the presence of complementary resources underlies positive edge responses, but only when completely confined to the adjacent habitat. This multi-species test of a general edge effects model at multiple edge types shows that resource-based mechanisms can explain many edge responses and that a modest knowledge of life history attributes and resource availability is sufficient for predicting and understanding many edge responses in complex landscapes.

Impact of grazing intensity during drought in an Arizona grassland.

The ecological benefits of changing cattle grazing practices in the western United States remain controversial, due in part to a lack of experimentation. In 1997 we initiated an experimental study of two rangeland alternatives, cattle removal and high-impact grazing, and compared grassland community responses with those with more conventional, moderate grazing practices. The study was conducted in a high-elevation, semiarid grassland near Flagstaff, Arizona (U.S.A.). We conducted annual plant surveys of modified Whittaker plots for 8 years and examined plant composition shifts among treatments and years. High-impact grazing had strong directional effects that led to a decline in perennial forb cover and an increase in annual plants, particularly the exotic cheatgrass (Bromus tectorum L.). A twofold increase in plant cover by exotic species followed a severe drought in the sixth year of the study, and this increase was greatest in the high-impact grazing plots, where native cover declined by one-half. Cattle removal resulted in little increase in native plant cover and reduced plant species richness relative to the moderate grazing control. Our results suggest that some intermediate level of cattle grazing may maintain greater levels of native plant diversity than the alternatives of cattle removal or high-density, short-duration grazing practices. Furthermore, episodic drought interacts with cattle grazing, leading to infrequent, but biologically important shifts in plant communities. Our results demonstrate the importance of climatic variation in determining ecological effects of grazing practices, and we recommend improving conservation efforts in arid rangelands by developing management plans that anticipate this variation.