Cicada emergence in Southwestern riparian forest: influences of wildfire and vegetation composition.

Annually emerging cicadas are a numerically and ecologically dominant species in Southwestern riparian forests. Humans have altered disturbance regimes that structure these forests such that floods are less common and wildfires occur more frequently than was historically the case. Impacts of these changes on primary consumers such as riparian cicadas are unknown. Because cicadas are consumed by a variety of animal species, disturbances that alter timing of their emergence or abundance could have consequences for species at higher trophic levels. We trapped emerging cicadas (Tibicen dealbatus) in burned and unburned riparian forest plots along the Middle Rio Grande in central New Mexico (USA) to determine effects of wildfire and vegetation structure on their density and phenology. We measured vegetation variables and soil temperature at cicada traps and related these variables to variation in emergence density and phenology. We also experimentally heated soil under emergence traps to examine the relationship between soil temperature and emergence phenology. Emergence density was similar in wildfire and unburned plots, though emergence date averaged earlier in wildfire plots and experimentally heated traps. We identified models containing cottonwood proximity (distance from the nearest cottonwood tree) and cottonwood canopy coverage as the most parsimonious explanations of emergence density at each trap. Model selection results were consistent with the literature and field observations that showed that cottonwood trees are an essential resource for T. dealbatus. Cottonwood canopy was also correlated with low soil temperatures, which are associated with later emergence dates. Failure of cottonwoods to reestablish following wildfire could result in cicadas emerging at lower densities and at earlier dates. For cicadas to emerge at densities and times that provide the greatest benefits to birds and other riparian-obligate secondary consumers, riparian forests should be protected from fire, and native vegetation in wildfire sites should be restored.     

Mechanisms generating modification of benthos following tidal flat invasion by a Spartina hybrid.

Many coastal habitats are being substantially altered by introduced plants. In San Francisco Bay, California, USA, a hybrid form of the eastern cordgrass Spartina alterniflora is rapidly invading open mudflats in southern and central sections of the Bay, altering habitat, reducing macrofaunal densities, and shifting species composition. The invasion has resulted in significant losses of surface-feeding amphipods, bivalves, and cirratulid polychaetes, while subsurface feeding groups such as tubificid oligochaetes and capitellid polychaetes have been unaffected. In the present paper, we document the causes and mechanisms underlying the changes observed. Through a series of in situ manipulative experiments we examined the influence of hybrid Spartina canopy on a range of physical, chemical, and biological properties. The hybrid Spartina canopy exerted a strong influence on the hydrodynamic regime, triggering a series of physical, chemical, and biological changes in the benthic system. Relative to tidal flats, water velocity was reduced in hybrid patches, promoting deposition of fine-grained, organic-rich particles. The resulting changes in the sediment environment included increased porewater sulfide concentrations and anoxia, which led to poor survivorship of surface feeders such as bivalves, amphipods, and polychaetes. These are key taxa that support higher trophic levels including migratory shorebirds that feed on tidal flats. Altered flow in the Spartina canopy further contributed to changes in barnacle recruitment and resuspension of adult benthic invertebrates. Increased crab-induced predation pressure associated with Spartina invasion also contributed to changes in benthic invertebrate communities. Our results suggest that multiple physical, chemical, biotic, and trophic impacts of the Spartina invasion have resulted in substantial changes in benthic communities that are likely to have important effects on the entire ecosystem.     

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.     

Modeling species-habitat relationships with spatially autocorrelated observation data.

Spatial autocorrelation in wildlife observation data arises when extrinsic environmental processes and patterns that influence the spatial distribution of wildlife are themselves spatially structured, or when species are subject to intrinsic population processes, causing contagion or dispersion effects. Territoriality, Allee effects, dispersal limitations, and social clustering are examples of intrinsic processes. Both forms of autocorrelation can violate the assumptions of generalized linear regression models, resulting in biased estimation of model coefficients and diminished predictive performance. Such consequences may be avoided for extrinsic autocorrelation when autocorrelated environmental variables are available for use as model covariates, whereas intrinsic spatial autocorrelation requires an alternative modeling approach. The autologistic model provides an approach suited to the binary observations often obtained in wildlife surveys, but its performance has not been tested across widely varying sampling intensities or strengths of intrinsic spatial structure. Here we use simulated data to test the autologistic model under a range of sampling conditions. The autologistic model obtains better fits and substantially better predictive performance than the standard logistic regression model over the full range of sampling designs and intensities tested. We provide a simple Bayesian implementation of the autologistic model, which until now has not been achieved with standard statistical software alone. A step-by-step procedure is given for characterizing and modeling spatial autocorrelation in binary observation data, along with computer code for fitting autologistic models in WinBUGS, a freeware Bayesian analysis package. This approach avoids normal approximations to the pseudo-likelihood, in contrast to previous Bayesian applications of the autologistic model. We provide a sample application of the autologistic model, fitted to survey data for a gliding marsupial in southeastern Australia.     

Urbanization affects stream ecosystem function by altering hydrology, chemistry, and biotic richness.

Catchment urbanization can alter physical, chemical, and biological attributes of stream ecosystems. In particular, changes in land use may affect the dynamics of organic matter decomposition, a measure of ecosystem function. We examined leaf-litter decomposition in 18 tributaries of the St. Johns River, Florida, USA. Land use in all 18 catchments ranged from 0% to 93% urban which translated to 0% to 66% total impervious area (TIA). Using a litter-bag technique, we measured mass loss, fungal biomass, and macroinvertebrate biomass for two leaf species (red maple [Acer rubrum] and sweetgum [Liquidambar styraciflua]). Rates of litter mass loss, which ranged from 0.01 to 0.05 per day for red maple and 0.006 to 0.018 per day for sweetgum, increased with impervious catchment area to levels of approximately 30-40% TIA and then decreased as impervious catchment area exceeded 40% TIA. Fungal biomass was also highest in streams draining catchments with intermediate levels of TIA. Macroinvertebrate biomass ranged from 17 to 354 mg/bag for red maple and from 15 to 399 mg/bag for sweetgum. Snail biomass and snail and total invertebrate richness were strongly related to breakdown rates among streams regardless of leaf species. Land-use and physical, chemical, and biological variables were highly intercorrelated. Principal-components analysis was therefore used to reduce the variables into several orthogonal axes. Using stepwise regression, we found that flow regime, snail biomass, snail and total invertebrate richness, and metal and nutrient content (which varied in a nonlinear manner with impervious surface area) were likely factors affecting litter breakdown rates in these streams.     

Chemically mediated competition between microbes and animals: microbes as consumers in food webs

Microbes are known to affect ecosystems and communities as decomposers, pathogens, and mutualists. However, they also may function as classic consumers and competitors with animals if they chemically deter larger consumers from using rich food-falls such as carrion, fruits, and seeds that can represent critical windfalls to both microbes and animals. Microbes often use chemicals (i.e., antibiotics) to compete against other microbes. Thus using chemicals against larger competitors might be expected and could redirect significant energy subsidies from upper trophic levels to the detrital pathway. When we baited traps in a coastal marine ecosystem with fresh vs. microbe-laden fish carrion, fresh carrion attracted 2.6 times as many animals per trap as microbe-laden carrion. This resulted from fresh carrion being found more frequently and from attracting more animals when found. Microbe-laden carrion was four times more likely to be uncolonized by large consumers than was fresh carrion. In the lab, the most common animal found in our traps (the stone crab Menippe mercenaria) ate fresh carrion 2.4 times more frequently than microbe-laden carrion. Bacteria-removal experiments and feeding bioassays using organic extracts of microbe-laden carrion showed that bacteria produced noxious chemicals that deterred animal consumers. Thus bacteria compete with large animal scavengers by rendering carcasses chemically repugnant. Because food-fall resources such as carrion are major food subsidies in many ecosystems, chemically mediated competition between microbes and animals could be an important, common, but underappreciated interaction within many communities.     

Assessing tiger population dynamics using photographic capture-recapture sampling

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.     

Modeling the beta diversity of coral reefs

Quantifying the beta diversity (species replacement along spatiotemporal gradients) of ecosystems is important for understanding and conserving patterns of biodiversity. However, virtually all studies of beta diversity focus on one-dimensional transects orientated along a specific environmental gradient that is defined a priori. By ignoring a second spatial dimension and the associated changes in species composition and environmental gradients, this approach may provide limited insight into the full pattern of beta diversity. Here, we use remotely sensed imagery to quantify beta diversity continuously, in two dimensions, and at multiple scales across an entire tropical marine seascape. We then show that beta diversity can be modeled (0.852 > or = r2 > or = 0.590) at spatial scales between 0.5 and 5.0 km2, using the environmental variables of mean and variance of depth and wave exposure. Beta diversity, quantified within a "window" of a given size, is positively correlated to the range of environmental conditions within that window. For example, beta diversity increases with increasing variance of depth. By analyzing such relationships across seascapes, this study provides a framework for a range of disparate coral reef literature including studies of zonation, diversity, and disturbance. Using supporting evidence from soft-bottom communities, we hypothesize that depth will be an important variable for modeling beta diversity in a range of marine systems. We discuss the implications of our results for the design of marine reserves.     

Simulation of germination of pioneer species along an experimental drought gradient

The germination of ten plant species from the Iberian Peninsula was assessed along a water deficit gradient between -0. 1652 (moist) and -0.4988 MPa (dry) of osmotic potential, created by addition of increasing concentrations of polyethylene glycol (PEG 6000) to distilled water in which plants were grown hydroponically. The level and rate of germination of Daucus carota and Thapsia villosa significantly decreased with decreasing psi. Seeds of Dactylis glomerata and Dittrichia viscosa had positive germination responses to low osmotic potentials; germination of Epilobium hirsutum was not affected by osmotic potential. Germination of Medicago arabica, Cynosurus cristatus, Cistus ladanifer and Cistus albidus, was no favored by the addition of polyethylene glycol (PEG). Germination of Foeniculum vulgare and Thapsia villosa was inhibited by PEG.