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B.S. Cade

Publications and source records attributed to B.S. Cade.

29 records · Page 2Linked to original sources

Quantile regression reveals hidden bias and uncertainty in habitat models

We simulated the effects of missing information on statistical distributions of animal response that covaried with measured predictors of habitat to evaluate the utility and performance of quantile regression for providing more useful intervals of uncertainty in habitat relationships. These procedures were evaulated for conditions in which heterogeneity and hidden bias were induced by confounding with missing variables associated with other improtant processes, a problem common in statistical modeling of ecological phenomena. Simulations for a large ( N = 10 000) finite population representing grid locations on a landscape demonstrated various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable. Quantile (0 ≤ τ ≤ 1) regression parameters for linear models that excluded the important, unmeasured variable revealed bias relative to parameters from the generating model. Depending on whether interactions of the measured and unmeasured variables were negative (interference interactions) or positive (facilitation interactions) in simulations without spatial structuring, either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Heterogeneous, nonlinear response patterns occurred with correlations between the measured and unmeasured variables. When the unmeasured variable was spatially structured, variation in parameters across quantiles associated with heterogeneous effects of the habitat variable was reduced by modeling the spatial trend surface as a cubic polynomial of location coordinates, but substantial hidden bias remained. Sampling ( n = 20–300) simulations demonstrated that regression quantile estimates and confidence intervals constructed by inverting weighted rank score tests provided valid coverage of these parameters. Local forms of quantile weighting were required for obtaining correct Type I error rates and confidence interval coverage. Quantile regression was used to estimate effects of physical habitat resources on a bivalve ( Macomona liliana ) in the spatially structured landscape on a sandflat in a New Zealand harbor. Confidence intervals around predicted 0.10 and 0.90 quantiles were used to estimate sampling intervals containing 80% of the variation in densities in relation to bed elevation. Spatially structured variation in bivalve counts estimated by a cubic polynomial trend surface remained after accounting for the nonlinear effects of bed elevation, indicating the existence of important spatially structured processes that were not adequately represented by the measured habitat variables.

Ecology↗

Isolation of Snake River islands and mammalian predation of waterfowl nests

In 1990–1992, we studied predation of waterfowl nests by mammalian predators on 30 islands in a 64-km reach of the Snake River in southwestern Idaho, USA, to identify river flows necessary to protect and enhance migratory bird use of Deer Flat National Wildlife Refuge. We monitored 235–314 Canada goose ( Branta canadensis ) nests each year and 122 duck nests, primarily mallard ( Anas platyrhynchos ), in 1991. We calculated island isolation as the flow energy (width × average water velocity [m 2 /sec]) a predator encountered in crossing to an island. Density of goose nests increased as island isolation increased ( P < 0.001). In contrast, visits of terrestrial predators to islands, mammalian predation of goose nests, and variance in predation rates decreased as island isolation increased ( P < 0.01). Nests were most frequently depredated by raccoons ( Procyon lotor ), coyotes ( Canis latrans ), badgers ( Taxidea taxus ), and mink ( Mustela vison ). Multiple regression models explained 67% of the variance in nest density and 48% of variance in predation rates ( P < 0.01). Variables of secondary importance relative to island isolation were island size and percentage of farmland on the adjacent mainland. Fewer geese nested ( P < 0.01) and predation rates were greater ( P = 0.06) on large islands, and more geese nested on islands adjacent to farmland ( P = 0.04). We also analyzed rates of nest predation relative to river flows for 21 islands from 1953 to 1992. Mammalian predation of goose nests decreased as island isolation increased with greater river flows ( P < 0.01). To identify levels of isolation needed to protect use of islands by nesting waterfowl, we estimated rates of change in nest densities and predation rates with island isolation for a range of regression quantiles. We then calculated levels of island isolation at river flows ranging from 110 to 340 m 3 /sec. Below flows of 250 m 3 /sec, nest predation rates increased rapidly. Flows ≥340 m 3 /sec adequately isolated Snake River islands for nesting waterfowl. Predator visitation and nest predation rates were at a low level, and variability in the rates was at a minimum for these flows.

Journal of Wildlife Management↗

Estimating effects of constraints on plant performance with regression quantiles

Rates of change in final summer densities of two desert annuals, Eriogonum abertianum and Haplopappus gracilis , as constrained by their initial winter germination densities were estimated with regression quantiles and compared with mechanistic fits based on a self-thinning rule proposed by Guo et al. (1998); Oikos 83: 237–245). The allometric relation used was equivalent to S = N f ( N i )−1= c f ( N i )−1, where S is the ratio of final to initial densities (survivorship), c f is a constant that is a final density specific to the species and environment, N i is the initial plant density, and N f is final plant density. We used regression quantiles to estimate c f assuming the exponent of −1 was fixed (model 1, N f ( N i )−1= c f ( N i )−1) and also obtained estimates by treating the exponent as a parameter to estimate (model 2, N f ( N i )−1= c f ( N i )λ). Regression quantiles allow rates of change to be estimated through any part of a data distribution conditional on some linear function of covariates. We focused on estimates for upper (90–99th) quantiles near the boundary of the summer density distributions where we expected effects of self-thinning to operate as the primary constraint on plant performance. Allometric functions estimated with regression quantiles were similar to functions fit by Guo et al. (1998) when the exponent was constrained to −1. However, the data were more consistent with estimates for model (2), where exponents were closer to −0.4 than −1, although model fit was not as good at higher initial plant densities as when the exponent was fixed at −1. An exponential form (model 3, N f ( N i )−1= c f ( N i )λ eγNi) that is a generalization of the discrete logistic growth function, where estimates of λ were −0.23 to −0.28 and estimates of γ were −0.003 to −0.006, provided better fit from low to high initial germination densities. Model 3 predictions were consistent with an interpretation that final summer densities were constrained by initial germination densities when these were low (<40 per 0.25 m2 for Eriogonum and <100 per 0.25 m2 for Haplopappus ) and were constrained by the self-thinning process at higher germination densities. Our exponential model (3) estimated with regression quantiles had similar form to the mechanistic relation of Guo et al. (1998) when plotted as a survivorship function, but avoided the unrealistic assumption that all populations attained a similar final density, and was based on a statistical model that has formal rules for estimation and inference.

Oikos↗

A gentle introduction to quantile regression for ecologists

Quantile regression is a way to estimate the conditional quantiles of a response variable distribution in the linear model that provides a more complete view of possible causal relationships between variables in ecological processes. Typically, all the factors that affect ecological processes are not measured and included in the statistical models used to investigate relationships between variables associated with those processes. As a consequence, there may be a weak or no predictive relationship between the mean of the response variable ( y ) distribution and the measured predictive factors ( X ). Yet there may be stronger, useful predictive relationships with other parts of the response variable distribution. This primer relates quantile regression estimates to prediction intervals in parametric error distribution regression models (eg least squares), and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of the estimates for homogeneous and heterogeneous regression models.

Frontiers in Ecology and the Environment↗

Influences of spatial and temporal variation on fish-habitat relationships defined by regression quantiles

We used regression quantiles to model potentially limiting relationships between the standing crop of cutthroat trout Oncorhynchus clarki and measures of stream channel morphology. Regression quantile models indicated that variation in fish density was inversely related to the width:depth ratio of streams but not to stream width or depth alone. The spatial and temporal stability of model predictions were examined across years and streams, respectively. Variation in fish density with width:depth ratio (10th-90th regression quantiles) modeled for streams sampled in 1993-1997 predicted the variation observed in 1998-1999, indicating similar habitat relationships across years. Both linear and nonlinear models described the limiting relationships well, the latter performing slightly better. Although estimated relationships were transferable in time, results were strongly dependent on the influence of spatial variation in fish density among streams. Density changes with width:depth ratio in a single stream were responsible for the significant ( P < 0.10) negative slopes estimated for the higher quantiles (>80th). This suggests that stream-scale factors other than width:depth ratio play a more direct role in determining population density. Much of the variation in densities of cutthroat trout among streams was attributed to the occurrence of nonnative brook trout Salvelinus fontinalis (a possible competitor) or connectivity to migratory habitats. Regression quantiles can be useful for estimating the effects of limiting factors when ecological responses are highly variable, but our results indicate that spatiotemporal variability in the data should be explicitly considered. In this study, data from individual streams and stream-specific characteristics (e.g., the occurrence of nonnative species and habitat connectivity) strongly affected our interpretation of the relationship between width:depth ratio and fish density.

Transactions of the American Fisheries Society↗

Evaluation of a habitat suitability index model

We assisted with development of a model for maternity habitat of the Indiana bat (Myotis soda/is), for use in conducting assessments of projects potentially impacting this endangered species. We started with an existing model, modified that model in a workshop, and evaluated the revised model, using data previously collected by others. Our analyses showed that higher indices of habitat suitability were associated with sites where Indiana bats were present and, thus, the model may be useful for identifying suitable habitat. Utility of the model, however, was based on a single component-density of suitable roost trees. Percentage of landscape in forest did not allow differentiation between sites occupied and not occupied by Indiana bats. Moreover, in spite of a general opinion by participants in the workshop that bodies of water were highly productive feeding areas and that a diversity of feeding habitats was optimal, we found no evidence to support either hypothesis.

Conference Paper↗

Effects of emergency haying on vegetative characteristics within selected Conservation Reserve Program fields in the Northern Great Plains

Successional changes in vegetation composition within seeded grasslands may effect attainment of long term conservaation objectives. Comparisons between vegetation composition within Conservation Reserve Program (CRP) fields planted to cool season, introduced grasses hayed for emergency we, and non hayed fields of the same age and species composition were completed to determine potential effects of periodic haying. Emergency haying had little long term effect on vegetation height/density, percent cover of live pass, or forb cover when compared to characteristics within non hayed fields?. The presence of legumes [primarily alfalfa (Medicago sativa L)] increased in response to haying, whereas, abundance of noxious weeds [chiefly Canada thistle (Cirsium arvense (L) Scop.)] diminished. Implications for long term management CRP grassland to achieve wildlife habitat objectives are discussed.

Journal of Soil and Water Conservation↗

Establishment, growth, and early survival of woody riparian species at a Colorado gravel pit

Presence of a wetted edge during the period of seedfall was an effective predictor of suitable establishment (defined as germination and survival to the 1st autumn) locations for Populas deltoides subsp. monilifera , Salix amygdaloides , S. exigua , and Tamarix ramosissima seedlings during 3 successive years of a gravel pit revegetation project in Fort Collins, Colorado. At locations predicted to be suitable for establishment, position within the pit (possibly reflecting additional moisture provided by seepage) was a significant factor in determining whether establishment actually occurred. Cover of herbaceous species, which became established at the same time as, or after, woody seedlings, was positively related to probability of establishment for 8 of 11 species-year combinations, probably reflecting more favorable moisture conditions at certain locations. Herbaceous cover also was positively related to seedling height at the end of the 1st summer of growth for 9 of 11 species-year combinations. Neither establishment nor lst-summer growth was consistently related to overall decline in the water table as estimated by the drop in surface-water level during the growing season. Flooding in the 1st spring after establishment was negatively related to subsequent survival for 5 of 8 species-year combinations. The 4 species established at different elevations in the pit, depending on location of the wetted edge during the period of seedfall, and there was no evidence that differential mortality subsequently altered their distribution along the elevation gradient. However, the primary objective in this study was to restore native woody species, and we attempted to maintain conditions conducive to meeting this objective. Differential postestablishment mortality may be more important in structuring the riparian community in more rigorous riverine environments.

Colorado↗

The role of landscape and habitat characteristics in limiting abundance of grassland nesting songbirds in an urban open space

We examine the relationships between abundance of grassland nesting songbirds observed in the Boulder Open Space, CO, USA and parameters that described landscape and habitat characteristics, in order to provide information for Boulder Open Space planners and managers. Data sets included bird abundance and plant species composition, collected during three breeding seasons (1994–1996), and landscape composition and configuration measures from a satellite image-derived land-cover map. We used regression quantiles to estimate the limitations imposed on bird abundance by urban encroachment and decreasing areas of grassland cover-types on the landscape, and habitat characteristics within 200 m diameter sample plots. After accounting for the effect of landscape grassland composition on four species (Western Meadowlark ( Sturnella neglecta ), Vesper Sparrow ( Pooecetes gramineus ), Horned Lark ( Eremophila alpestris ), and Grasshopper Sparrow ( Ammodramus savannarum )), change in abundance with proportion of urban area in the landscape was consistent with the pattern expected for limiting factors that were the active constraint at some times and places. Area of preferred grassland cover-types on the landscape was important for all species, and this remained the case when habitat variables were included in combined landscape–habitat models, with one exception (Western Meadowlark). Analysis of habitat variables enabled identification of important features at the local scale (e.g. shale plant communities in Lark Sparrow ( Chondestes grammacus ) habitat) that were indistinguishable using landscape data alone. Consideration of changes in the landscape due to urbanization and loss of grassland habitat are crucial for open space planning, and habitat features associated with localized and clumped bird species distributions provide important additional information. Widening the management focus to include areas that are not part of the open space system will facilitate a more complete understanding of potential limiting factor processes.

Landscape and Urban Planning↗

No consistent effect of plant diversity on productivity

Hector et al . (1) reported on BIODEPTH, a major international experiment on the response of plant productivity to variation in the number of plant species. They found “an overall log-linear reduction of average aboveground biomass with loss of species,” leading to what the accompanying Perspective (2) described as “a rule of thumb—that each halving of diversity leads to a 10 to 20% reduction in productivity.” These conclusions, if true, imply that the continuing high rate of plant extinction threatens the future productivity of Earth's natural and managed ecosystems and could impair their ability to produce resources essential for human survival and to regulate the concentration of atmospheric CO 2 . The three sites with proper experimental design (Portugal, Sweden, and Sheffield) all showed significant positive regressions of productivity across two or three doublings of species richness [Fig. 1; (12)]. This is the pattern expected from random selection from a set of objects with different properties (13–15), because the probability of including any specific member of the set—such as a plant species that grows rapidly or fixes nitrogen—increases with the number of objects selected. Such a pattern, found consistently in randomly assembled experimental plant communities but only rarely in natural plant communities (4, 5,13–15), has been identified as a statistical artifact of experimental design (5, 13, 14). Although one study (15) suggested that the pattern constitutes a natural mechanism by which diversity affects productivity, this requires the biologically unrealistic assumption that plant communities are randomly assembled with respect to productivity (5).

Science↗