Managing plant population spread: prediction and analysis using a simple model

Models can be used to direct the management of population spread for the control of invasives or to encourage species of conservation value. Analytical models are attractive because of their theoretical basis and limited data requirements, but there is concern that their simplicity may limit their practical utility. We address the applied use of simple models in a study of a declining annual herb, Rhinanthus minor. We parameterized a population-spread model using field data on demography and dispersal for four management systems: grazed only (GR), hay-cut once (H1), hay-cut twice (H2), and hay-cut with autumn grazing (HG). Within a replicated experiment we measured spread rates of introduced R. minor populations over eight years. The modeled and measured spread rates were very similar in terms of both patterns of management effects and absolute values, so that in both cases HG > H2, H1 > GR. The treatments affected both dispersal and demography (establishment and survival) and so we used decomposition approaches to analyze the major causes of differences in population spread. Increased dispersal under hay-cutting was more important than demographic changes and accounted for approximately 70% of the differences in spread rate between the hay-cut and grazed-only treatments. Furthermore, management effects on the tail of the dispersal curve were by far the most critical in governing spread. This study suggests that simple models can be used to inform practical conservation management, and we demonstrate straightforward uses of our model to predict the impacts of different management strategies. While simple models can give accurate projections, we emphasize that they must be parameterized with high-quality data gathered at the appropriate spatial scale.     

Rapid ecosystem shifts in peatlands: linking plant physiology and succession

Stratigraphic records from peatlands suggest that the shift from a rich fen (calcareous fen) to an ombrotrophic bog can occur rapidly. This shift constitutes a switch from a species-rich ecosystem to a species-poor one with greater carbon storage. In this process, the invasion and expansion of acidifying bog species of Sphagnum (peat mosses) play a key role. To test under what conditions an acidifying bog species could invade a rich fen, we conducted three experiments, contrasting the bog species S. fucsum with the rich-fen species S. warnstorfii and S. teres. We first tested the effect of calcareous water by growing the three species at different constant height above the water table (HWT; 2, 7, and 14 cm) in a rich-fen pool and measured maximum photosynthetic rate and production and difference in length growth as an indicator of competition. In none of the species was the photosynthetic capacity negatively affected when placed at low HWT, but S. fuscum was a weaker competitor at low HWT. In our second experiment we transplanted the three species into microhabitats with different and naturally varying HWT in a rich fen. Here, S. fuscum nearly ceased to photosynthesize when transplanted to low HWT (brown moss carpet), while it performed similarly to the two rich-fen species at the intermediate level (S. warnstorfii hummock level). In contrast to S. fuscum, the rich-fen sphagna performed equally well in both habitats. The brown moss carpet was seasonally flooded, and in our third experiment we found that S. fuscum, but not S. teres, was severely damaged when submerged in rich-fen water. Our results suggest two thresholds in HWT affecting the ecosystem switch: one level that reduces the risk of submergence and a higher one that makes bog sphagna competitive against the rich-fen species.     

Predicting future effects from nutrient abatement and climate change on phosphorus concentrations in Lake Bourget, France

Like many temperate European lakes, Lake Bourget (France) has suffered from eutrophication during the second half of the last century. Due to a remarkable restoration program, the lake has been recovering for the past 25 years after a massive decrease in total phosphorus (TP) loading. TP concentrations have decreased from about 100-120 to 20-25 μg/L. Additional efforts are, however, still required to obtain a perennially sustainable good ecological status and model parameterisation of fluxes can assist in predicting future outcomes, especially in the context of global warming. In this paper, a dynamic model (MeroLakeMab) was developed and tested with the purpose to reconstruct the loading history of Lake Bourget and to predict TP concentrations during scenarios of increased temperature, decreased water runoff and decreased P loading. Simulations suggested that the historical TP loading decrease may have been as extensive as 88%. Decreases in water discharge to Lake Bourget at magnitudes forecasted by the Intergovernmental Panel on Climate Change (IPCC) would not affect TP concentrations notably, but marked concentration changes could, however, occur if decreases in runoff would have a strong impact on the TP loading. Increasing temperature effects on yearly mean TP concentrations in the water column would be very small compared to effects from changes in the TP loading. Predictions such as these could be instrumental for future successful lake management.     

The evolution of CSR life-history strategies in a plant model with explicit physiology and architecture

This paper introduces a functional-structural plant model based on artificial life concepts and L-systems. This model takes into account realistic physiological rules, the architecture of the plants and their demography. An original benefit of this approach is that it allows the simulation of plant evolution at both functional and life-history levels implementing mutations to the L-systems and a set of genetic parameter values. The conducted experiments focus on the evolutionary emergence of different life history strategies in an environment with heterogeneous resource availability and disturbance frequency. It is found that, depending on the encountered conditions, the plants develop three major strategies classified as competitors, stress-tolerators and ruderals according to Grime's CSR theory. Most of the evolved characteristics comply with theoretical biology or field observations on natural plants. Besides these results, our modelling framework is highly flexible and many refinements can be readily implemented depending on the issues one intends to address. Moreover, the model can readily be used to address many questions at the interface between evolutionary ecology, plant functional and community ecologies and ecosystem ecology.     

Interactions among plant defense compounds: a method for analysis

Summary. Plants contain an enormous diversity and quantity of secondary metabolites, some of which are toxic and deterrent to herbivores and pathogens. This impressive diversity of plant compounds suggests a high probability of interactions among them. Synergistic interactions are those in which the combined activity of two or more chemicals is greater than that expected given their individual activities. On the other hand, antagonistic interactions are those in which the combined activity of two or more chemicals is less than that expected given their individual activities. Synergistic interactions could increase plant fitness whereas antagonistic interactions could decrease plant fitness. Interactions are thus potentially very important, not only in explaining the diversity of defense compounds within individual plants, but also in providing insight into plant defense strategies. Although synergistic interactions have received increased attention in the ecological literature in the last decade, the number of documented cases of synergy remains small and antagonistic interactions are rarely considered. The primary reason for this scarcity may be the difficulty of detecting, analyzing and displaying such interactions. Analysis by ANOVA, though sometimes used, often is not appropriate. We introduce a simple technique, isobolographic analysis, that is used in pharmacology for detecting and rigorously quantifying synergy and antagonism and provide an example using the brine shrimp toxicity assay. More statistically sophisticated approaches, such as isobolographic analysis, will allow ecologists to effectively document the role of chemical synergy and antagonism in interactions between species. Such chemical interactions may ultimately provide insight into longstanding, ecological questions. Received 26 October 1998; accepted 24 March 1999.     

Predicting breeding habitat for amphibians: a spatiotemporal analysis across Yellowstone National Park

The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species, including 6828-10 764 ha for tiger salamanders, 971-3017 ha for western toads, 4732-16 696 ha for boreal chorus frogs, and 4940-19 690 ha for Columbia spotted frogs.     

Multivariate analysis of spatial patterns: a unified approach to local and global structures

We propose a new approach to the multivariate analysis of data sets with known sampling site spatial positions. A between-sites neighbouring relationship must be derived from site positions and this relationship is introduced into the multivariate analyses through neighbouring weights (number of neighbours at each site) and through the matrix of the neighbouring graph. Eigenvector analysis methods (e.g. principal component analysis, correspondence analysis) can then be used to detect total, local and global structures. The introduction of the D-centring (centring with respect to the neighbouring weights) allows us to write a total variance decomposition into local and global components, and to propose a unified view of several methods. After a brief review of the matrix approach to this problem, we present the results obtained on both simulated and real data sets, showing how spatial structure can be detected and analysed. Freely available computer programs to perform computations and graphical displays are proposed.     

Extending the leaf economics spectrum to decomposition: evidence from a tropical forest

I investigated the relationship between leaf physiological traits and decomposition of leaf litter for 35 plant species of contrasting growth forms from a lowland tropical forest in Panama to determine whether leaf traits could be used to predict decomposition. Decomposition rate (k) was correlated with specific leaf area (SLA), leaf nitrogen (N), phosphorus (P), and potassium (K) across all species. Photosynthetic rate per unit mass (Amass) was not correlated with k, but structural equation modeling showed support for a causal model with significant indirect effects of Amass on k through SLA, N, and P, but not K. The results indicate that the decomposability of leaf tissue in this tropical forest is related to a global spectrum of leaf economics that varies from thin, easily decomposable leaves with high nutrient concentrations and high photosynthetic rates to thick, relatively recalcitrant leaves with greater physical toughness and defenses and low photosynthetic rates. If this pattern is robust across biomes, then selection for suites of traits that maximize photosynthetic carbon gain over the lifetime of the leaf may be used to predict the effects of plant species on leaf litter decomposition, thus placing the ecosystem process of decomposition in an evolutionary context.     

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant,Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework).     

Multiple plant exploiters on a shared host: testing for nonadditive effects on plant performance.

The combined impact of multiple plant parasites on plant performance can either be additive (the total damage equals the sum of the individual effects) or nonadditive (synergistic or antagonistic damage). Two statistical models are available for testing the independent (=additive) effects of two factors. Here we suggest that the natural history of the plant-parasite system should motivate the choice of a statistical model to test for additivity. Using in-field, manipulative experiments, we examined the interactions between the herbivorous mite Calacarus flagelliseta Fletchmann, De Moraes and Barbosa (Acari: Eriophyidae), the fungal pathogen Oidium caricae F. Noack (a powdery mildew), and their host plant Carica papaya L. in Hawaii. First, we found that herbivorous mites had a moderate negative effect on powdery mildew: when mites were absent, powdery mildew colonies were larger and more numerous. Second, we showed that each plant parasite, when evaluated alone, significantly reduced several measures of plant performance. Third, we found that the combined impact of mites and mildew on plant performance is mostly additive and, for a few variables, less than additive. Finally, we explored compensatory responses and found no evidence for nonlinearities in the relationship between plant performance and cumulative parasite impact. Plants are almost universally subject to attack by multiple herbivores and pathogens; thus a deeper understanding of how multiple plant parasites shape each other's population dynamics and plant performance is essential to understanding plant-parasite interactions.     

Nitrogen regulation of the climate-carbon feedback: evidence from a long-term global change experiment

Modeling studies have shown that nitrogen (N) strongly regulates ecosystem responses and feedback to climate warming. However, it remains unclear what mechanisms underlie N regulation of ecosystem-climate interactions. To examine N regulation of ecosystem feedback to climate change, we have conducted a warming and clipping experiment since November 1999 in a tallgrass prairie of the Great Plains, USA. Infrared heaters were used to elevate soil temperature by an average of 1.96 degrees C at a depth of 2.5 cm from 2000 to 2008. Yearly biomass clipping mimicked hay or biofuel feedstock harvest. We measured carbon (C) and N concentrations, estimated their content and C:N ratio in plant, root, litter, and soil pools. Warming significantly stimulated C storage in aboveground plant, root, and litter pools by 17%, 38%, and 29%, respectively, averaged over the nine years (all P < 0.05) but did not change soil C content or N content in any pool. Plant C:N ratio and nitrogen use efficiency increased in the warmed plots compared to the control plots, resulting primarily from increased dominance of C4 plants in the community. Clipping significantly decreased C and N storage in plant and litter pools (all P < 0.05) but did not have interactive effects with warming on either C or N pools over the nine years. Our results suggest that increased ecosystem nitrogen use efficiency via a shift in species composition toward C4 dominance rather than plant N uptake is a key mechanism underlying warming stimulation of plant biomass growth.     

Life-history strategies of plant pathogens: distribution patterns and phylogenetic analysis

Here we analyze herbarium records, surveys, and studies of fungal plant pathogens in tropical natural systems in order to establish a framework to study plant-pathogen interactions from a life-history perspective. We looked at how life-history traits of pathogens and their host plants affect the distribution of pathogens in different tropical habitats, and the importance of host phylogeny in determining the habitat associations of obligate fungal pathogens. Our study reveals that plant-pathogen interactions are prevalent and widespread in the tropics. Phylogenetic analysis of the distribution of obligate pathogens among plant families did not suggest a strong overall pattern of higher-level host phylogeny in pathogen host range, except that smut pathogens are particularly dominant on Poaceae and Asteraceae, and rusts are most common on Fabaceae, families that dominate disturbed areas in the tropics.     

Toward a predictive theory of risk effects: hypotheses for prey attributes and compensatory mortality

Risk effects, or the costs of antipredator behavior, can comprise a large proportion of the total effect of predators on their prey. While empirical studies are accumulating to demonstrate the importance of risk effects, there is no general theory that predicts the relative importance of risk effects and direct predation. Working toward this general theory, it has been shown that functional traits of predators (e.g., hunting modes) help to predict the importance of risk effects for ecosystem function. Here, I note that attributes of the predator, the prey, and the environment are all important in determining the strength of antipredator responses, and I develop hypotheses for the ways that prey functional traits might influence the magnitude of risk effects. In particular, I consider the following attributes of prey: group size and dilution of direct predation risk, the degree of foraging specialization, body mass, and the degree to which direct predation is additive vs. compensatory. Strong tests of these hypotheses will require continued development of methods to identify and quantify the fitness costs of antipredator responses in wild populations.     

Effects of regional vs. ecological factors on plant species richness: an intercontinental analysis

Conclusions from past studies on the roles that historical and regional factors and contemporary and ecological factors have played in regulating large-scale patterns of species richness have been controversial. Conflicting past results were likely affected by differences in the range of environments analyzed and the scales of observation. Eastern North America and eastern Asia are ideal regions for examining the relative effects of historical and regional factors and contemporary and ecological factors on large-scale patterns of plant species richness because these two regions are closely matched in terms of climate and because their floras originated from the same paleoflora but have experienced different histories of development since the late Paleogene when climate cooling caused their separation. We report on a comprehensive data set of 471 floras ranging from 10 km2 to 4.7 x 10(6) km2 and spanning a wide range of climate and latitude (from 21 degrees to 55 degrees N) to examine whether the contribution of region relative to climate persists from small to large floras and increases from cooler to warmer climates. We found that eastern Asia is richer than eastern North America when sample area, maximum elevation, and climate are accounted for, that this difference diminishes toward higher latitudes, and that elevation plays a much stronger role in eastern Asia than in eastern North America. Our analysis reconciles contemporary/ecological and historical/regional explanations for species richness variation and helps explain why different conclusions have been reached by different authors working in the same geographical areas: the strength of the region effect itself varies with location and range of climatic conditions of the observations.     

Emergence cues of a mayfly in a high-altitude stream ecosystem: potential response to climate change.

To understand the consequences of human accelerated environmental change, it is important to document the effects on natural populations of an increasing frequency of extreme climatic events. In stream ecosystems, recent climate change has resulted in extreme variation in both thermal and hydrological regimes. From 2001 to 2004, a severe drought in western United States corresponded with earlier emergence of the adult stage of the high-altitude stream mayfly, Baetis bicaudatus. Using a long-term database from a western Colorado stream, the peak emergence date of this mayfly population was predicted by both the magnitude and date of peak stream flow, and by the mean daily water temperature, suggesting that Baetis may respond to declining stream flow or increasing water temperature as proximate cues for early metamorphosis. However, in a one-year survey of multiple streams from the same drainage basin, only water temperature predicted spatial variation in the onset of emergence of this mayfly. To decouple the effects of temperature and flow, we separately manipulated these factors in flow-through microcosms and measured the timing of B. bicaudatus metamorphosis to the adult stage. Mayflies emerged sooner in a warmed-water treatment than an ambient-water treatment; but reducing flow did not accelerate the onset of mayfly emergence. Nonetheless, using warming temperatures to cue metamorphosis enables mayflies to time their emergence during the descending limb of the hydrograph when oviposition sites (protruding rocks) are becoming available. We speculate that large-scale climate changes involving warming and stream drying could cause significant shifts in the timing of mayfly metamorphosis, thereby having negative effects on populations that play an important role in stream ecosystems.     

Spatial analysis of chromium in southwestern part of Iran: probabilistic health risk and multivariate global sensitivity analysis

This study was concerned with chromium as a potential carcinogenic contaminant in 64 wells located in five aquifers, southwest of Iran. A probabilistic health risk assessment indicated a high risk to the local residents including adults and children in the study area. A sequential sensitivity analysis and a novel approach known as multivariate global sensitivity analysis using both principal component analysis and B-spline were applied to investigate the behavior of health risk model along time considering four independent input parameters in the risk equation. In this context, based on the results of sensitivity analysis, concentration of chromium in drinking water (C_w) and body weight (W) were the most influential parameters. Random forest (RF) was used as a variable selection method to choose the most influential parameters for the prediction of chromium. Five parameters, among 13 water quality variables, including phosphate, nitrate, fluoride, manganese and iron were selected by RF as the most important parameters for spatial prediction. Hybrid methods of RF and ordinary kriging (RFOK) and RF and inverse distance weighting (RFIDW) were then applied for spatial prediction of Cr using the secondary variables. The RFOK and RFIDW were more efficient than that of ordinary kriging (OK) with respect to a cross-validation algorithm. For instance, in terms of relative root mean squared error, the performance of OK was improved from 31.72 to 23.21 and 23.61 for RFOK and RFIDW, respectively.