Glucosinolates and trichomes track tissue value in two sympatric mustards

Glucosinolates, trichomes, nitrogen, and carbon are not distributed uniformly through the canopies of mustards. In this study, we asked whether glucosinolate concentrations and trichome densities in two sympatric mustards, Brassica kaber and B. nigra, are highest in tissues of greatest value to the plant. We also asked whether nitrogen or carbon content is the stronger predictor of tissue value, and what fraction of each resource is incorporated in glucosinolates. To quantify tissue values, we removed three equal-area fractions (lower, middle, and upper) from the canopies of B. kaber and B. nigra in the greenhouse, as well as whole canopies of naturally growing B. nigra in the field, at two times during growth and measured reductions in their performance relative to controls. We also measured trichome density in both experiments, as well as glucosinolate, nitrogen, and carbon concentrations for the equal-area fractions in the greenhouse. We found that upper leaves had the highest glucosinolate concentrations, trichome densities, and tissue values. Furthermore, young plants in the field had higher trichome densities and tissue values than did older plants. Collectively, these data provide strong support for optimal defense theory and are among the first such evidence for glucosinolates and for physical defenses. The positive relationship between trichome density and tissue value was strong even after we accounted for the effects of leaf expansion. While nitrogen and carbon have both received attention as currencies for trade-offs, our data suggest that nitrogen concentration is a significantly better predictor of tissue value in these two mustard species. Interestingly, <1% of the nitrogen or carbon in leaves was incorporated in glucosinolates, which may explain why glucosinolates lack a consistent response to nitrogen fertilization.     

Estimating survival rates of uncatchable animals: the myth of high juvenile mortality in reptiles

Survival rates of juvenile reptiles are critical population parameters but are difficult to obtain through mark-recapture programs because these small, secretive animals are rarely caught. This scarcity has encouraged speculation that survival rates of juveniles are very low, and we test this prediction by estimating juvenile survival rates indirectly. A simple mathematical model calculates the annual juvenile survival rate needed to maintain a stable population size, using published data on adult survival rates, reproductive output, and ages at maturity in 109 reptile populations encompassing 57 species. Counter to prediction, estimated juvenile survival rates were relatively high (on average, only about 13% less than those of conspecific adults) and highly correlated with adult survival rates. Overall, survival rates during both juvenile and adult life were higher in turtles than in snakes, and higher in snakes than in lizards. As predicted from life history theory, rates of juvenile survival were higher in species that produce large offspring, and higher in viviparous squamates than in oviparous species. Our analyses challenge the widely held belief that juvenile reptiles have low rates of annual survival and suggest instead that sampling problems and the elusive biology of juvenile reptiles have misled researchers in this respect.     

Habitat-mediated foraging limitations drive survival bottlenecks for juvenile salmon

Realistic population models and effective conservation strategies require a thorough understanding of mechanisms driving stage-specific mortality. Mortality bottlenecks for many species occur in the juvenile stage and are thought to result from limitation on food or foraging habitat during a "critical period" for growth and survival. Without a way to account for maternal effects or to measure integrated consumption rates in the field, it has been virtually impossible to test these relationships directly. Hence uncertainties about mechanisms underlying such bottlenecks remain. In this study we randomize maternal effects across sites and apply a new method for measuring consumption integrated over weeks to months to test the hypothesis that food limitation drives early-season juvenile mortality bottlenecks in Atlantic salmon (Salmo salar). Using natural signatures of geologically derived cesium (133Cs), we estimated consumption rates of >400 fry stocked into six streams. Two to four weeks after stocking, consumption was extremely low across sites (0.005 g x g(-1) x d(-1)) and was predicted to be below maintenance rations (i.e., yielding negative energy balances) for the majority of individuals from five of six sites. However, consumption during this time was positively correlated with growth rates and survival (measured at the end of the growing season). In contrast, consumption rates increased in mid- (0.030 g x g(-1) x d(-1)) and late (0.035 g x g(-1) x d(-1)) seasons, but juvenile survival and consumption were not correlated, and correlations between growth and consumption were weak. These findings are consistent with predictions of a habitat-based bioenergetic model constructed using the actual stream positions of the individual fish in the present study, which indicates that habitat-based models capture important environmental determinants of juvenile growth and survival. Hence, by combining approaches, reducing maternal effects and controlling initial conditions, we offer a general framework for linking foraging with juvenile survival and present the first direct consumption-based evidence for the early season bottleneck hypothesis.     

Southern Ocean biogeography and taxonomic resolution: what’s in the name?

We examined the taxonomic resolution of zooplankton data required to identify ocean basin scale biogeographic zonation in the Southern Ocean. A 2,154 km transect was completed south of Australia. Sea surface temperature (SST) measured at 1 min intervals showed that seven physical zones were sampled. Zooplankton were collected at a spatial resolution of ~9.2 km with a continuous plankton recorder, identified to the highest possible taxonomic resolution and enumerated. Zooplankton assemblage similarity between samples was calculated using the Bray–Curtis index for the taxonomic levels of species, genus, family, order and class after first log₁₀(x + 1) (LA) and then presence/absence (PA) transformation of abundance data. Although within and between zone sample similarity increased with decreasing taxonomic resolution, for both data transformations, cluster analysis demonstrated that the biogeographic separation of zones remained at all taxonomic levels when using LA data. ANOSIM confirmed this, detecting significant differences in zooplankton assemblage structure between all seven a priori determined physical zones for all taxonomic levels when using the LA data. In the case of the PA data for the complete data set, and both LA and PA data for a crustacean only data set, no significant differences were detected between zooplankton assemblages in the Polar frontal zone (PFZ) and inter-PFZ at any taxonomic level. Loss of information at resolutions below the species level, particularly in the PA data, prevented the separation of some zones. However, the majority of physical zones were biogeographically distinct from species level to class using both LA and PA transformations. Significant relationships between SST and zooplankton community structure, summarised as NMDS scores, at all taxonomic levels, for both LA and PA transformations, and complete and crustacean only data sets, highlighted the biogeographic relevance of low resolution taxonomic data. The retention of biogeographic information in low taxonomic resolution data shows that data sets collected with different taxonomic resolutions may be meaningfully merged for the post hoc generation of Southern Ocean time series.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common.     

Slope,aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland

The slope and aspect of a vegetated surface strongly affects the amount of solar radiation intercepted by that surface. Solar radiation is the dominant component of the surface energy balance and influences ecologically critical factors of microclimate, including near-surface temperatures, evaporative demand and soil moisture content. It also determines the exposure of vegetation to photosynthetically active and ultra-violet wavelengths. Spatial variation in slope and aspect is therefore a key determinant of vegetation pattern, species distribution and ecosystem processes in many environments. Slope and aspect angle may vary considerably over distances of a few metres, and fine-scale species’ distribution patterns frequently follow these topographic patterns. The availability of suitable microclimate at such scales may be critical for the response of species distributions to climatic change at much larger spatial scales. However, quantifying the relevant microclimatic gradients is not straightforward, as the potential variation in solar radiation flux under clear-sky conditions is modified by local and regional variations in cloud cover, and interacts with long-wave radiation exchange, local meteorology and surface characteristics.     

Scaling mass and morphology in leaves: an extension of the WBE model

Recent advances in metabolic scaling theory have highlighted the importance of exchange surfaces and vascular network geometry in understanding the integration and scaling of whole-plant form and function. Additional work on leaf form and function has also highlighted general scaling relationships for many leaf traits. However, it is unclear if a common theoretical framework can reveal the general rules underlying much of the variation observed in scaling relationships at the whole-plant and leaf level. Here we present an extension of the general model introduced by G. B. West, J. H. Brown, and B. J. Enquist that has previously been applied to scaling phenomena for whole plants to predict scaling relationships in leaves. Specifically, the model shows how the exponents that describe the scaling of leaf surface area, length, and petiole diameter should change with increasing leaf mass (or with one another) and with variation in leaf dimensionality. The predictions of the model are tested and found to be in general agreement with a large data set of leaves collected from both temperate and arid sites. Our results demonstrate that a general model based on the scaling properties of biological distribution networks can also be successfully applied to understand the diversity of leaf form and function.     

Nutrient dynamics and tree growth of silvopastoral systems: impact of poultry litter

Fertilizing pastures with poultry litter has led to an increased incidence of nutrient-saturated soils, particularly on highly fertilized, well drained soils. Applying litter to silvopastures, in which loblolly pine (Pinus taeda L.) and bahiagrass (Paspalum notatum) production are integrated, may be an ecologically desirable alternative for upland soils of the southeastern USA. Integrating subterranean clover (Trifolium subterraneum) into silvopastures may enhance nutrient retention potential. This study evaluated soil nutrient dynamics, loblolly pine nutrient composition, and loblolly pine growth of an annually fertilized silvopasture on a well drained soil in response to fertilizer type, litter application rate, and subterranean clover. Three fertilizer treatments were applied annually for 4 yr: (i) 5 Mg litter ha(-1) (5LIT), (ii) 10 Mg litter ha(-1) (10LIT), and (iii) an inorganic N, P, K pasture blend (INO). Litter stimulated loblolly pine growth, and neither litter treatment produced soil test P concentrations above runoff potential threshold ranges. However, both litter treatments led to accumulation of several nutrients (notably P) in upper soil horizons relative to INO and unfertilized control treatments. The 10LIT treatment may have increased N and P leaching potential. Subterranean clover kept more P sequestered in the upper soil horizon and conferred some growth benefits to loblolly pine. Thus, although these silvopasture systems had a relatively high capacity for nutrient use and retention at this site, litter should be applied less frequently than in this study to reduce environmental risks.     

Nitrogen leaching from Douglas-fir forests after urea fertilization

Leaching of nitrogen (N) after forest fertilization has the potential to pollute ground and surface water. The purpose of this study was to quantify N leaching through the primary rooting zone of N-limited Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] forests the year after fertilization (224 kg N ha(-1) as urea) and to calculate changes in the N pools of the overstory trees, understory vegetation, and soil. At six sites on production forests in the Hood Canal watershed, Washington, tension lysimeters and estimates of the soil water flux were used to quantify the mobilization and leaching of NO(3)-N, NH(4)-N, and dissolved organic nitrogen below the observed rooting depth. Soil and vegetation samples were collected before fertilization and 1 and 6 mo after fertilization. In the year after fertilization, the total leaching beyond the primary rooting zone in excess of control plots was 4.2 kg N ha(-1) (p = 0.03), which was equal to 2% of the total N applied. The peak NO(3)-N concentration that leached beyond the rooting zone of fertilized plots was 0.2 mg NO(3)-N L(-1). Six months after fertilization, 26% of the applied N was accounted for in the overstory, and 27% was accounted for in the O+A horizon of the soil. The results of this study indicate that forest fertilization can lead to small N leaching fluxes out of the primary rooting zone during the first year after urea application.