Does contrast between eggshell ground and spot coloration affect egg rejection?

Obligate avian brood parasitic species impose the costs of incubating foreign eggs and raising young upon their unrelated hosts. The most common host defence is the rejection of parasitic eggs from the nest. Both egg colours and spot patterns influence egg rejection decisions in many host species, yet no studies have explicitly examined the role of variation in spot coloration. We studied the American robin Turdus migratorius, a blue-green unspotted egg-laying host of the brown-headed cowbird Molothrus ater, a brood parasite that lays non-mimetic spotted eggs. We examined host responses to model eggs with variable spot coloration against a constant robin-mimetic ground colour to identify patterns of rejection associated with perceived contrast between spot and ground colours. By using avian visual modelling, we found that robins were more likely to reject eggs whose spots had greater chromatic (hue) but not achromatic (brightness) contrast. Therefore, egg rejection decision rules in the American robin may depend on the colour contrast between parasite eggshell spot and host ground coloration. Our study also suggests that egg recognition in relation to spot coloration, like ground colour recognition, is tuned to the natural variation of avian eggshell spot colours but not to unnatural spot colours.     

Attribution theory in the organizational sciences: A case of unrealized potential

We argue that although attributional processes appear to affect virtually all goal and reward oriented behavior in organizations, they have not received adequate attention in the organizational sciences. In this Incubator, we encourage scholars to unlock the potential of attribution theory to develop more complete explanations of organizational behavior. Copyright © 2010 John Wiley & Sons, Ltd.     

Forecasts of habitat loss and fragmentation due to urban growth are sensitive to source of input data

The conversion of natural habitat to urban settlements is a primary driver of biodiversity loss, and species' persistence is threatened by the extent, location, and spatial pattern of development. Urban growth models are widely used to anticipate future development and to inform conservation management, but the source of spatial input to these models may contribute to uncertainty in their predictions. We compared two sources of historic urban maps, used as input for model calibration, to determine how differences in definition and scale of urban extent affect the resulting spatial predictions from a widely used urban growth model for San Diego County, CA under three conservation scenarios. The results showed that rate, extent, and spatial pattern of predicted urban development, and associated habitat loss, may vary substantially depending on the source of input data, regardless of how much land is excluded from development. Although the datasets we compared both represented urban land, different types of land use/land cover included in the definition of urban land and different minimum mapping units contributed to the discrepancies. Varying temporal resolution of the input datasets also contributed to differences in projected rates of development. Differential predicted impacts to vegetation types illustrate how the choice of spatial input data may lead to different conclusions relative to conservation. Although the study cannot reveal whether one dataset is better than another, modelers should carefully consider that geographical reality can be represented differently, and should carefully choose the definition and scale of their data to fit their research objectives.     

The value of urban open space: Meta-analyses of contingent valuation and hedonic pricing results

Urban open space provides a number of valuable services to urban populations, including recreational opportunities, aesthetic enjoyment, environmental functions, and may also be associated with existence values. In separate meta-analyses of the contingent valuation (CV) and hedonic pricing (HP) literature we examine which physical, socio-economic, and study characteristics determine the value of open space. The dependent variable in the CV meta-regression is defined as the value of open space per hectare per year in 2003 US$, and in the HP model as the percentage change in house price for a 10 m decrease in distance to open space. Using a multi-level modelling approach we find in both the CV and HP analyses that there is a positive and significant relationship between the value of urban open space and population density, indicating that scarcity and crowdedness matter, and that the value of open space does not vary significantly with income. Further, urban parks are more highly valued than other types of urban open space (forests, agricultural and undeveloped land) and methodological differences in study design have a large influence on estimated values from both CV and HP. We also find important regional differences in preferences for urban open space, which suggests that the potential for transferring estimated values between regions is likely to be limited.     

Predicting deer-vehicle collisions in an urban area

Collisions with deer and other large animals are increasing, and the resulting economic costs and risks to public safety have made mitigation measures a priority for both city and wildlife managers. We created landscape models to describe and predict deer-vehicle collision (DVCs) within the City of Edmonton, Alberta. Models based on roadside characteristics revealed that DVCs occurred frequently where roadside vegetation was both denser and more diverse, and that DVCs were more likely to occur when the groomed width of roadside right-of-ways was smaller. No DVCs occurred where the width of the vegetation-free or manicured roadside buffer was greater than 40 m. Landscape-based models showed that DVCs were more likely in more heterogeneous landscapes where road densities were lower and speed limits were higher, and where non-forested vegetation such as farmland was in closer proximity to larger tracts of forest. These models can help wildlife and transportation managers to identify locations of high collision frequency for mitigation. Modifying certain landscape and roadside habitats can be an effective way to reduce deer-vehicle collisions.     

Stronger predation in the tropics shapes species richness patterns in marine communities

Species interactions are widely assumed to be stronger at lower latitudes, but surprisingly few experimental studies test this hypothesis, and none ties these processes to observed patterns of species richness across latitude. We report here the first experimental field test that predation is both stronger and has a disproportionate effect on species richness in the tropics relative to the temperate zone. We conducted predator-exclusion experiments on communities of sessile marine invertebrates in four regions, which span 32 degrees latitude, in the western Atlantic Ocean and Caribbean Sea. Over a three-month timescale, predation had no effect on species richness in the temperate zone. In the tropics, however, communities were from two to over ten times more species-rich in the absence of predators than when predators were present. While micro-and macro-predators likely compete for the limited prey resource in the tropics, micropredators alone were able to exert as much pressure on the invertebrate communities as the full predator community. This result highlights the extent to which exposure to even a subset of the predator guild can significantly impact species richness in the tropics. Patterns were consistent in analyses that included relative and total species abundances. Higher species richness in the absence of predators in the tropics was also observed when species occurrences were pooled across two larger spatial scales, site and region, demonstrating a consistent scaling relationship. These experimental results show that predation can both limit local species abundances and shape patterns of regional coexistence in the tropics. When preestablished diverse tropical communities were then exposed to predation for different durations, ranging from one to several days, species richness was always reduced. These findings confirmed that impacts of predation in the tropics are strong and consistent, even in more established communities. Our results offer empirical support for the long-held prediction that predation pressure is stronger at lower latitudes. Furthermore, we demonstrate the magnitude to which variation in predation pressure can contribute to the maintenance of tropical species diversity.     

Differences in stress tolerance and brood size between a non-indigenous and an indigenous gammarid in the northern Baltic Sea

Differences in stress tolerance and reproductive traits may drive the competitive hierarchy between non-indigenous and indigenous species and turn the former ones into successful invaders. In the northern Baltic Sea, the non-indigenous Gammarus tigrinus is a recent invader of littoral ecosystems and now occupies comparable ecological niches as the indigenous G. zaddachi. In laboratory experiments on specimens collected between June and August 2009 around Tvärminne in southern Finland (59°50′N/23°15′E), the tolerances towards heat stress and hypoxia were determined for the two species using lethal time, LT₅₀, as response variable. The brood size of the two species was also studied and some observations were made on maturation of juveniles. Gammarus tigrinus was more resistant to hypoxia and survived at higher temperatures than G. zaddachi. Brood size was also greater in G. tigrinus than in G. zaddachi and G. tigrinus matured at a smaller size and earlier than G. zaddachi. Hence, there are clear competitive advantages for the non-indigenous G. tigrinus compared to the indigenous G. zaddachi, and these may be further strengthened through ongoing environmental changes related to increased eutrophication and a warming climate in the Baltic Sea region.     

Estimating California ecosystem carbon change using process model and land cover disturbance data: 1951-2000

Land use change, natural disturbance, and climate change directly alter ecosystem productivity and carbon stock level. The estimation of ecosystem carbon dynamics depends on the quality of land cover change data and the effectiveness of the ecosystem models that represent the vegetation growth processes and disturbance effects. We used the Integrated Biosphere Simulator (IBIS) and a set of 30- to 60-m resolution fire and land cover change data to examine the carbon changes of California's forests, shrublands, and grasslands. Simulation results indicate that during 1951-2000, the net primary productivity (NPP) increased by 7%, from 72.2 to 77.1 Tg C yr⁻¹ (1 teragram = 10¹² g), mainly due to CO₂ fertilization, since the climate hardly changed during this period. Similarly, heterotrophic respiration increased by 5%, from 69.4 to 73.1 Tg C yr⁻¹, mainly due to increased forest soil carbon and temperature. Net ecosystem production (NEP) was highly variable in the 50-year period but on average equalled 3.0 Tg C yr⁻¹ (total of 149 Tg C). As with NEP, the net biome production (NBP) was also highly variable but averaged −0.55 Tg C yr⁻¹ (total of -27.3 Tg C) because NBP in the 1980s was very low (-5.34 Tg C yr⁻¹). During the study period, a total of 126 Tg carbon were removed by logging and land use change, and 50 Tg carbon were directly removed by wildland fires. For carbon pools, the estimated total living upper canopy (tree) biomass decreased from 928 to 834 Tg C, and the understory (including shrub and grass) biomass increased from 59 to 63 Tg C. Soil carbon and dead biomass carbon increased from 1136 to 1197 Tg C.Our analyses suggest that both natural and human processes have significant influence on the carbon change in California. During 1951-2000, climate interannual variability was the key driving force for the large interannual changes of ecosystem carbon source and sink at the state level, while logging and fire were the dominant driving forces for carbon balances in several specific ecoregions. From a long-term perspective, CO₂ fertilization plays a key role in maintaining higher NPP. However, our study shows that the increase in C sequestration by CO₂ fertilization is largely offset by logging/land use change and wildland fires.     

Stochastic gravity models for modeling lake invasions

Freshwater aquatic systems in North America are being invaded by many different species, ranging from fish, mollusks, cladocerans to various bacteria and viruses. These invasions have serious ecological and economic impacts. Human activities such as recreational boating are an important pathway for dispersal. Gravity models are used to quantify the dispersal effect of human activity. Gravity models currently used in ecology are deterministic. This paper proposes the use of stochastic gravity models in ecology, which provides new capabilities both in model building and in potential model applications. These models allow us to use standard statistical inference tools such as maximum likelihood estimation and model selection based on information criteria. To facilitate prediction, we use only those covariates that are easily available from common data sources and can be forecasted in future. This is important for forecasting the spread of invasive species in geographical and temporal domain. The proposed model is portable, that is it can be used for estimating relative boater traffic and hence relative propagule pressure for the lakes not covered by current boater surveys. This makes our results broadly applicable to various invasion prediction and management models.