In eastern U.S. oak forests, defoliation by gypsy moths and the risk of Lyme disease are determined by interactions among acorns, white-footed mice, moths, deer, and ticks. Experimental removal of mice, which eat moth pupae, demonstrated that moth outbreaks are caused by reductions in mouse density that occur when there are no acorns. Experimental acorn addition increased mouse density. Acorn addition also increased densities of black-legged ticks, evidently by attracting deer, which are key tick hosts. Mice are primarily responsible for infecting ticks with the Lyme disease agent. The results have important implications for predicting and managing forest health and human health.

Masting, the intermittent production of large flower or seed crops by a population of perennial plants, can enhance the reproductive success of participating plants and drive fluctuations in seed‐consumer populations and other ecosystem components over large geographic areas. The spatial and taxonomic extent over which masting is synchronized can determine its success in enhancing individual plant fitness as well as its ecosystem‐level effects, and it can indicate the types of proximal cues that enable reproductive synchrony. Here, we demonstrate high intra‐ and intergeneric synchrony in mast seeding by 17 species of New Zealand plants from four families across >150 000 km2. The synchronous species vary ecologically (pollination and dispersal modes) and are geographically widely separated, so intergeneric synchrony seems unlikely to be adaptive per se. Synchronous fruiting by these species was associated with anomalously high temperatures the summer before seedfall, a cue linked with the La Niña phase of El Niño–Southern Oscillation. The lone asynchronous species appears to respond to summer temperatures, but with a 2‐yr rather than 1‐yr time lag. The importance of temperature anomalies as cues for synchronized masting suggests that the timing and intensity of masting may be sensitive to global climate change, with widespread effects on taxonomically disparate plant and animal communities.

Many pathogens and parasites attack multiple host species, so their ability to invade a host community can depend on host community composition. We present a graphical isocline framework for studying disease establishment in systems with two host species, based on treating host species as resources. The isocline approach provides a natural generalization to multi‐host systems of two related concepts in disease ecology – the basic reproductive rate of a parasite, and threshold host density. Qualitative isocline shape characterizes the threshold community configurations that permit parasite establishment. In general, isocline shape reflects the relative forces of inter‐ and intraspecific transmission of shared parasites. We discuss the qualitative implications of parasite isocline shape for issues of mounting concern in conservation ecology.

Carnivore guilds play a vital role in ecological communities by cascading trophic effects, energy and nutrient transfer, and stabilizing or destabilizing food webs. Consequently, the structure of carnivore guilds can be critical to ecosystem patterns. Body size is a crucial influence on intraguild interactions, because it affects access to prey resources, effectiveness in scramble competition, and vulnerability to intraguild predation. Coyotes (Canis latrans), bobcats (Lynx rufus), gray foxes (Urocyon cinereoargenteus), raccoons (Procyon lotor), red foxes (Vulpes vulpes), and striped skunks (Mephitis mephitis) occur sympatrically throughout much of North America and overlap in resource use, indicating potential for interspecific interactions. Although much is known about the autecology of the individual species separately, little is known about factors that facilitate coexistence and how interactions within this guild influence distribution, habitat use, and temporal activity of the smaller carnivores. To assess how habitat autecology and interspecific interactions affect the structure of this widespread carnivore guild, we conducted a large‐scale, non‐invasive carnivore survey using an occupancy modeling framework. We deployed remote cameras during 3‐week surveys to detect carnivores at 1,118 camera locations in 357 2.6‐km2 sections (3–4 cameras/section composing a cluster) in the 16 southernmost counties of Illinois (16,058 km2) during January–April, 2008–2010. We characterized microhabitat at each camera location and landscape‐level habitat features for each camera cluster. In a multistage approach, we used information‐theoretic methods to evaluate competing models for detection, species‐specific habitat occupancy, multispecies co‐occupancy, and multiseason (colonization and extinction) occupancy dynamics. We developed occupancy models for each species to represent hypothesized effects of anthropogenic features, prey availability, landscape complexity, and vegetative land cover. We quantified temporal activity patterns of each carnivore species based on their frequency of appearance in photographs. Further, we assessed whether smaller carnivores shifted their diel activity patterns in response to the presence of potential competitors. Of the 102,711 photographs of endothermic animals, we recorded photographs of bobcats (n = 412 photographs), coyotes (n = 1,397), gray foxes (n = 546), raccoons (n = 40,029), red foxes (n = 149), and striped skunks (n = 2,467). Bobcats were active primarily during crepuscular periods, and their activity was reduced with precipitation and higher temperatures. The probability of detecting bobcats decreased after a bobcat photograph was recorded, suggesting avoidance of remote cameras after the first encounter. Across southern Illinois, bobcat occupancy at the camera‐location and camera‐cluster scale (ψtrueˆlocal = 0.24 ± 0.04, camera cluster ψtrueˆcluster = 0.75 ± 0.06) was negatively influenced by anthropogenic features and infrastructure. Bobcats had high rates of coloni...

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.

Variation in annual flowering effort is described for 16 long datasets from 11 species of Chionochloa (Poaceae) in New Zealand. All populations exhibited extreme mast seeding. The most variable species was C. crassiuscula (coefficient of variation, CV= 3.02) over 26 years at Takahe Valley, Fiordland, which is the highest published CV we know of worldwide. The other populations also had high CVs (lowest CV= 1.42, mean CV = 1.84) which were higher than for other well-studied genera such as Picea, Pinus and Quercus. There were also frequent years of zero flowering (mean across all populations was 37.2% zero years; maximum 53% for C. rubra and C. crassiuscula over 19 years) whereas zero years are rare in other published masting datasets. Flowering was highly synchronous among species within a site (mean r= 0.886), and also (though significantly less so) among sites. Among sites, synchrony was not significantly higher within-species (mean r =0.711) than between-species (r= 0.690). Warm summer temperatures led to heavy flowering the following summer. Flowering synchrony increased with increasing synchrony in local deseasonalised summer temperatures, and decreased with increasing distance between sites. Mast seeding has been shown in Chionochloa to reduce losses to specialist flower or seed predators. Among-species synchrony may be adaptive if species share a common seed predator. Developing seeds of at least 10 Chionochloa species are attacked by larvae of an undescribed cecidomyiid. In Takahe Valley, where masting is most pronounced, cecidomyiids attacked all six Chionochloa species in all four years studied. Mean annual losses were almost constant (10.0 to 13.4%) while flowering effort varied 100-fold. The invariant losses are consistent with other evidence that the cecidomyiid may have extended diapause, which would make it harder to satiate by mast seeding. We hypothesise that one possible factor favouring such extremely high levels of mast seeding in Chionochloa is that its seed predator is very hard to satiate. Kelly and A. L. Harrison, Plant and Microbial Sciences, Uni6. of Canterbury, Christchurch 1, New Zealand (d.kelly@botn.canterbury.ac.nz). -W. G. Lee, Landcare Research, Pri6ate Bag 1930, Dunedin, New Zealand. -I. J. Payton, Landcare Research, P.O. Box 69, Lincoln, New Zealand. -P. R. Wilson, Landcare Research, Pri6ate Bag 6, Nelson, New Zealand. -E. M. Schauber, Dept of Ecology and E6olutionary Biology, Uni6. of Connecticut, Storrs, CT, USA and Inst. of Ecosystem Studies, Millbrook, NY, USA. Mast seeding is the intermittent synchronous production of large seed crops by a population of plants (Kelly 1994). It requires variation among years in the reproductive effort of individual plants and synchrony between individuals within a population. Mast seeding is found in plants from many different taxonomic groups and from most parts of the world, although it seems to be especially common in temperate forest trees (Silvertown 1980) and in the New Zealand flora (Webb and Kelly 1993, Kelly 1994). From an...

Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected sub-model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex sub-model structures for non-target sub-models. We tested the performance of different model selection strategies using four data sets and three model types. For each data set, we determined the "true" distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of "true" AIC weight we recovered under different model selection strategies. Sequential-by-sub-model strategies often performed poorly. Based on our results, we recommend using a build-up or secondary candidate sets, which were more reliable and carrying all models within 5-10 AIC of the top model forward to subsequent stages. The structure of non-target sub-models was less important. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

: Establishment and spread of infectious diseases are controlled by the frequency of contacts among hosts. Although managers can estimate transmission coefficients from the relationship between disease prevalence and age or time, they may wish to quantify or compare contact rates before a disease is established or while it is at very low prevalence. Our objectives were to quantify direct and indirect contacts rates among white‐tailed deer (Odocoileus virginianus) and to compare these measures of contact rate with simpler measures of joint space use. We deployed Global Positioning System (GPS) collars on 23 deer near Carbondale, Illinois, USA, from 2002 to 2005. We used location data from the GPS collars to measure pairwise rates of direct and indirect contact, based on a range of proximity criteria and time lags, as well as volume of intersection (VI) of kernel utilization distributions. We analyzed contact rates at a given distance criterion and time lag using mixed‐model logistic regression. Direct contact rates increased with increasing VI and were higher in autumn—spring than in summer. After accounting for VI, the estimated odds of direct contact during autumn—spring periods were 5.0–22.1‐fold greater (depending on the proximity criterion) for pairs of deer in the same social group than for between‐group pairs, but for direct contacts during summer the within:between‐group odds ratio did not differ significantly from 1. Indirect contact rates also increased with VI, but the effects of both season and pair‐type were much smaller than for direct contacts and differed little as the time lag increased from 1–30 days. These results indicate that simple measures of joint space use are insufficient indices of direct contact because group membership can substantially increase contacts at a given level of joint space use. With indirect transmission, however, group membership had a much smaller influence after accounting for VI. Relationships between contact rates and season, VI, and pair‐type were generally robust to changes in the proximity criterion defining a contact, and patterns of indirect contacts were affected little by the choice of time lag from 1–30 days. The use of GPS collars provides a framework for testing hypotheses about the form of contact networks among large mammals and comparing potential direct and indirect contact rates across gradients of ecological factors, such as population density or landscape configuration.