Population growth versus population spread of an ant-dispersed neotropical herb with a mixed reproductive strategy

In plants that produce seeds with contrasting genetic background (selfed versus outcrossed), the question arises whether the ecological function of the two types of progeny differ. This paper addresses this issue for the ant-dispersed Calathea micans by introducing a novel application of the Neubert–Caswell model for analysis of wave speed for structured populations. Because dispersal as well as vital rates are structured, the model allows for distinct dispersal kernels for different types of progeny and thus permits comparisons of the sensitivity to changes in demographic and dispersal parameters of in situ population growth rate versus population spread across space. The study site was a lowland, evergreen tropical rain forest at La Selva Biological station, Costa Rica, where the species is commonly found throughout the forest. In C. micans, seeds produced by open flowers (potentially outcrossed) or by closed flowers (selfed) bear oily arils and are dispersed by ants. Five life-history stages were used to characterize the population: seedlings originating from seeds produced by open flowers, seedlings originating from seeds produced by closed flowers, juvenile vegetative plants, reproductive plants without new shoots and reproductive plants with new shoots. Demography varied seasonally. Transitions were estimated from marking and following the fate of plants (N = 400) in a natural population over a dry and a wet season. The population dynamics was described by a 10 × 10 matrix, with five life-history stages and two habitat states. The habitat states cycle repeatedly, dry–wet–dry–wet. To estimate dispersal kernels for each seed type, individual seeds (N = 225 and 306 seeds produced by open and closed flowers, respectively) were color-coded and placed in depots, allowing the ants to redistribute them. Five months later, seedlings with an attached seed coat bearing the intact color-coding, were surveyed around the depots. Radial distances and angles were recorded for each seedling (N = 67 and 81 seedlings arising from open and closed flowers, respectively). The results of the model give an asymptotic growth rate of 1.06 per season and an asymptotic rate of spread of 8.36 cm per season. There is a high correlation (r = 0.99) between elasticity of growth rate and elasticity of rate of spread of the population. Both rates are most sensitive to changes in stasis of juveniles during the dry season. However, most interesting is the analysis that revealed that population spread is more sensitive than in situ population growth to demographic rates of seedlings arising from open flowers. The analysis suggests a new way of thinking about ecological functions of multiple modes of reproduction.     

A peaked function for modeling temperature dependence of plant productivity

We suggests that temperature response of plant productivity can be modeled by the Arrhenius function modified to describe the effect of temperature on enzyme activity: G_A(T) = 2f(T)/(1 + f²(T)), where f(T) = exp(E_a/RT_opt − E_a/RT), R the universal gas constant, E_a the activation energy and T_opt is the optimal temperature. In common with other functions used for modeling the temperature response of plant productivity, the curve of function G is almost symmetrical and bell-shaped. The special convenience of G_A is that it relates the width of the “bell” to thermodynamic concepts, such as activation energy of chemical reactions converting carbon dioxide and water to carbohydrates.     

Incorporating animal behavior into seed dispersal models: implications for seed shadows

Seed dispersal fundamentally influences plant population and community dynamics but is difficult to quantify directly. Consequently, models are frequently used to describe the seed shadow (the seed deposition pattern of a plant population). For vertebrate-dispersed plants, animal behavior is known to influence seed shadows but is poorly integrated in seed dispersal models. Here, we illustrate a modeling approach that incorporates animal behavior and develop a stochastic, spatially explicit simulation model that predicts the seed shadow for a primate-dispersed tree species (Virola calophylla, Myristicaceae) at the forest stand scale. The model was parameterized from field-collected data on fruit production and seed dispersal, behaviors and movement patterns of the key disperser, the spider monkey (Ateles paniscus), densities of dispersed and non-dispersed seeds, and direct estimates of seed dispersal distances. Our model demonstrated that the spatial scale of dispersal for this V. calophylla population was large, as spider monkeys routinely dispersed seeds >100 m, a commonly used threshold for long-distance dispersal. The simulated seed shadow was heterogeneous, with high spatial variance in seed density resulting largely from behaviors and movement patterns of spider monkeys that aggregated seeds (dispersal at their sleeping sites) and that scattered seeds (dispersal during diurnal foraging and resting). The single-distribution dispersal kernels frequently used to model dispersal substantially underestimated this variance and poorly fit the simulated seed-dispersal curve, primarily because of its multimodality, and a mixture distribution always fit the simulated dispersal curve better. Both seed shadow heterogeneity and dispersal curve multimodality arose directly from these different dispersal processes generated by spider monkeys. Compared to models that did not account for disperser behavior, our modeling approach improved prediction of the seed shadow of this V. calophylla population. An important function of seed dispersal models is to use the seed shadows they predict to estimate components of plant demography, particularly seedling population dynamics and distributions. Our model demonstrated that improved seed shadow prediction for animal-dispersed plants can be accomplished by incorporating spatially explicit information on disperser behavior and movements, using scales large enough to capture routine long-distance dispersal, and using dispersal kernels, such as mixture distributions, that account for spatially aggregated dispersal.     

Modelling CO2 and energy exchanges in a northern semiarid grassland using the carbon- and nitrogen-coupled Canadian Land Surface Scheme (C-CLASS)

The development of carbon (C) and nitrogen (N) simulations is one of the ongoing efforts in the land surface schemes of climate models. The C- and N-coupled Canadian Land Surface Scheme (C-CLASS) was recently modified to better represent grassland ecosystems. Improvements include revised plant growth and senescence calculations that are driven by the plant C balance between fixation and respiration, and leaf-out and leaf-fall schemes that are regulated by the seasonal dynamics of C and N reserves. These revisions were developed to better simulate the stress-related senescence and regrowth of perennials. The model was tested with observations of surface carbon and energy fluxes, soil temperature and moisture, and plant growth during 3 years of declining precipitation at a northern semiarid grassland near Lethbridge, Alberta, Canada. The R² and standard deviations between the simulated and observed half-hourly fluxes were 0.95 and 22.5 W m⁻² for net radiation, 0.82 and 42.1 W m⁻² for sensible heat, 0.66 and 29.2 W m⁻² for latent heat, and 0.63 and 0.95 μmol C m⁻² s⁻¹ for net CO₂ exchange. The model and observations both showed a strong impact of declining precipitation on annual carbon budgets in this semi-arid grassland. In a wet year (1998, precipitation = 482 mm), the ecosystem acted as a strong C sink (92 g C m⁻² modelled and 109 g C m⁻² measured from June 20th to December 31st). In a near-normal year (1999, precipitation = 341 mm), a smaller C sink was indicated (24 g C m⁻² modelled and 21 g C m⁻² measured). In a dry year (2000, precipitation = 276 mm), the ecosystem acted as a small C source (−18 g C m⁻² modelled and −17 g C m⁻² measured).     

Modeling and coupling of soil respiration and soil water content in fenced Leymus chinensis steppe,Inner Mongolia

Soil respiration was measured with the enclosed chamber method during 2 years in fenced Leymus chinensis steppe, Inner Mongolia, China. Soil water content at 0–10 cm depth was a major limited factor of soil respiration in semi-arid grassland, accounting for 76.4% of the variation. The temperature-dependent exponential function could only explain 38.7% of the variation in soil respiration. With 246 data over the entire experimental period, multiple linear stepwise regressions of soil respiration rate were analyzed with the influencing factors, including soil water content at 0–10 cm depth, air temperature, air pressure, air humidity, total radiation and their interactions. With soil water content at 0–10 cm depth (W) and air temperature (T_h) as combined factors, the twice linear regression (F = 1.68WT_h − 109.09) was simple and its coefficients were significant, accounting for 83.1% of the variation in soil respiration. Due to the lack of long-term and continuous soil water content, a water sub-model based on precipitation and evapotranspiration was introduced, which could provide better fits with the measured values (R² = 0.813). The magnitudes of soil respiration calculated from the twice linear regression equation and water sub-model were 439.58 and 463.06 g CO₂ m⁻² in 2001 (19 June–23 September) and in 2002 (1 June–24 September), respectively. The mean hourly soil respiration rates were in the range of the previous studies in the adjacent region and the world's major temperate grasslands.     

LANDIS and forest landscape models

This paper provides contextual documentation of the LANDIS model development to provide a framework for the other papers in this special issue. The LANDIS model of forest landscape disturbance and succession was developed since the early 1990s as a research and management tool that optimizes the possible landscape extent (100 s ha to 1000 s km²), while providing mechanistic detail adequate for a broad range of potential problems. LANDIS is a raster model, and operates on landscapes mapped as cells, containing tree species age classes. Spatial processes, such as seed dispersal, and disturbances such as fire, wind, and harvesting can occur. LANDIS development benefited from the modelling and research progress of the 1960s to the1980s, including the growth of landscape ecology during the 1980s. In the past decade the model has been used by colleagues across North America, as well as in Europe and China. This has been useful to those not able to undertake the cost and effort of developing their own model, and it has provided a growing diverse set of test landscapes for the model. These areas include temperate, southern, and boreal forests of eastern North America, to montane and boreal western forests, coastal California forest and shrub systems, boreal Finnish forests, and montane forests in Switzerland and northeastern China. The LANDIS model continues to be refined and developed. Papers in this special issue document recent work. Future goals include integration within a larger land use change model, and applications to landscape and regional global change projection based on newly incorporated biomass and carbon dynamics.     

Artificial neural network approach for modelling nitrogen dioxide dispersion from vehicular exhaust emissions

Artificial neural networks (ANNs) are useful alternative techniques in modelling the complex vehicular exhaust emission (VEE) dispersion phenomena. This paper describes a step-by-step procedure to model the nitrogen dioxide (NO₂) dispersion phenomena using the ANN technique. The ANN-based NO₂ models are developed at two air-quality-control regions (AQCRs), one, representing, a traffic intersection (AQCR1) and the other, an arterial road (AQCR2) in the Delhi city. The models are unique in the sense that they are developed for ‘heterogeneous¹’ traffic conditions and tropical meteorology. The inputs to the model consist of 10 meteorological and 6 traffic characteristic variables. Two-year data, from 1 January 1997 to 31 December 1998 has been used for model training and data from 1 January to 31 December 1999, for model testing and evaluation purposes. The results show satisfactory performance of the ANN-based NO₂ models on the evaluation data set at both the AQCRs (d = 0.76 for AQCR1, and d = 0. 59 for AQCR2).     

Catastrophic-like shifts in shallow Turkish lakes: a modeling approach

A generalized logistic model (GLM) was developed to determine occurrence of submerged macrophytes in shallow Lake Eymir, and the model was tested independently on the upstream shallow Lake Mogan using the data collected fortnightly from both lakes during 1997–2002. The independent variables included concentrations of chlorophyll-a (chl-a), suspended solids (SS) and total phosphorus (TP), Secchi disc transparency and z-scores of water levels. The dependent variable was the binary index of submerged plant occurrence. We used bootstrapping to determine the maximum number of epochs to train the model and to execute training when the corrected average cross entropy (c-index) leveled off. The model predicted that SS concentration, z-scores of water levels and TP concentration were the most important variables for determining occurrence of submerged plants. Sensitivity analyses showed that the probability of submerged plant occurrence followed a strong hysterisis response to varying water levels and the concentrations of SS and TP, with the break points being ±50 cm, 12–17 mg l⁻¹ and 200–300 μg l⁻¹, respectively. This observed sensitivity was in accordance with the alternative stable states hypothesis of shallow lakes. For occurrence of submerged plants, chlorophyll-a concentration and Secchi disc transparency had low significance. This was in concert with both relevances of input variables and the field results. The model gave a good definition of the system since the c-index and corrected c-index on the training data were high (0.970 and 0.963, respectively). Testing the model on Lake Mogan produced a c-index of 0.815 with around 80% of the cases being correctly classified. This showed that the model had a high ability to generalize over a spatially independent test set; therefore, it had a great reliability as well. In addition, the predictive power of the model was indeed very high. Consequently, the model captured the relationships between the input and output variables successfully and consistently with alternative stable states hypothesis.     

Modelling carbon storage in highly fragmented and human-dominated landscapes: Linking land-cover patterns and ecosystem models

To extend coupled human–environment systems research and include the ecological effects of land-use and land-cover change and policy scenarios, we present an analysis of the effects of forest patch size and shape and landscape pattern on carbon storage estimated by BIOME-BGC. We evaluate the effects of including within-patch and landscape-scale heterogeneity in air temperature on carbon estimates using two modelling experiments. In the first, we combine fieldwork, spatial analysis, and BIOME-BGC at a 15-m resolution to estimate carbon storage in the highly fragmented and human-dominated landscape of Southeastern Michigan, USA. In the second, we perform the same analysis on 12 hypothetical landscapes that differ only in their degree of fragmentation. For each experiment we conduct four air-temperature treatments, three guided by field-based data and one empirically informed by local National Weather Service station data. The three field data sets were measured (1) exterior to a forest patch, (2) from the patch edge inward to 60 m on east-, south-, and west-facing aspects, separately, and (3) interior to that forest patch. Our field-data analysis revealed a decrease in maximum air temperature from the forest patch edge to a depth of 80 m. Within-patch air-temperature values were significantly different (α = 0.01) among transects (c.v. = 13.28) and for all measurement locations (c.v. = 30.58). Results from the first experiment showed that the interior treatment underestimated carbon storage by ～8000 Mg C and the exterior treatment overestimated carbon storage by 30,000 Mg C within Dundee Township, Southeastern Michigan, when compared to a treatment that included within-patch heterogeneity. In the second experiment we found a logarithmic increase in carbon storage with increasing fragmentation (r² = 0.91). While a number of other processes (e.g. altered disturbance frequency or severity) remain to be included in future experiments, this combined field and modelling study clearly demonstrated that the inclusion of within-patch and landscape heterogeneity, and landscape fragmentation, each have a strong effect on forest carbon cycling and storage as simulated by a widely used ecosystem process model.     

Utilizing satellite imagery and GLOBE student data to model soil dynamics

General Purpose Atmosphere Plant Soil Simulator (GAPS), a menu-driven soil-vegetation-atmosphere transfer (SVAT) model, was used to simulate soil water dynamics from 1998 through 2001 for Greenville, PA, USA. GLOBE student data collected by students from Reynolds Junior and Senior High School, coupled with normalized difference vegetation index (NDVI) data derived from SPOT4 vegetation imagery, were used to parameterize and validate the model. Data from the National Weather Service Cooperative (NWSC) was used to evaluate the GLOBE dataset. Overall, there was a high index of agreement (d > 0.80) between field measurements and simulated soil water values from both datasets (GLOBE and NWSC). Simulations using the GLOBE climate data outperformed the NWSC data for the 1999, 2000, and 2001 growing seasons. In addition, the GLOBE simulations showed that NDVI could be utilized to predict transpiration periods (QI, QII, and QIII) for northern latitudes >35° with a distinct winter period. In phenological terms, QI reflects the onset of the growing season when vegetation is greening up (NDVI < 0.60) and transpiration is beginning (<2 mm/day) and QII reflects the end of the growing seasons when vegetation is greening down and transpiration is decreasing. QIII reflects the height of the growing season when transpiration rates average between 2 and 5 mm per day and NDVI is at its maximum (>0.60). Results of this study demonstrate that GLOBE student data, coupled with remotely sensed data, can provide an important source of input and validation information for capacitance SVAT models such as GAPS.     

Nitrogen controls on ecosystem carbon sequestration: a model implementation and application to Saskatchewan,Canada

A plant–soil nitrogen (N) cycling model was developed and incorporated into the Integrated BIosphere Simulator (IBIS) of Foley et al. [Foley, J.A., Prentice, I.C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface process, terrestrial carbon balance and vegetation dynamics. Global Biogeochem. Cycles 10, 603–628]. In the N-model, soil mineral N regulates ecosystem carbon (C) fluxes and ecosystem C:N ratios. Net primary productivity (NPP) is controlled by feedbacks from both leaf C:N and soil mineral N. Leaf C:N determines the foliar and canopy photosynthesis rates, while soil mineral N determines the N availability for plant growth and the efficiency of biomass construction. Nitrogen controls on the decomposition of soil organic matter (SOM) are implemented through N immobilization and mineralization separately. The model allows greater SOM mineralization at lower mineral N, and conversely, allows greater N immobilization at higher mineral N. The model's seasonal and inter-annual behaviours are demonstrated. A regional simulation for Saskatchewan, Canada, was performed for the period 1851–2000 at a 10 km × 10 km resolution. Simulated NPP was compared with high-resolution (1 km × 1 km) NPP estimated from remote sensing data using the boreal ecosystem productivity simulator (BEPS) [Liu, J., Chen, J.M., Cihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 44, 81–87]. The agreement between IBIS and BEPS, particularly in NPP spatial variation, was considerably improved when the N controls were introduced into IBIS.     

A simplified approach to implement forest eco-hydrological properties in regional hydrological modelling

The topic of this paper is a simplified model for simulating the hydrological properties of forest stands based on a robust computation of the temporal LAI (leaf area index) dynamics. The approach allows the simulation of all hydrologically relevant processes. It includes interception of precipitation and transpiration of forest stands with and without groundwater in the rooting zone. The model also considers phenology, mortality and simple management practice. It was implemented as a module in the eco-hydrological model SWIM (Soil and Water Integrated Model). The approach was tested on Scots pine (Pinus sylvestris) and common oak (Quercus robur and Q. petraea).The results demonstrate a good simulation of annual biomass increase and LAI and satisfactory simulation of litter production (annual mean value). A comparison of the date of May sprout for Scots pine and leaf unfolding for Oak (1980–1990) with observed data of the DWD (German Weather Service) shows a good reproduction of the temporal dynamic. The daily simulation of transpiration shows an excellent correlation of r = 0.81 for the year 1998 but only r = 0.65 for 1999. The interception losses were also simulated and compared with weekly observed data showing satisfactory results in the vegetation periods and annual sums, but worse agreement in autumn and spring time. A regional assessment study was done in the federal state of Brandenburg (Germany) to test the applicability and multi-criteria evaluation capabilities of the approach on the landscape and catchments scale using forest data, daily river discharge and regional water balance.     

Evaluation of information indices as indicators of environmental stress in terrestrial soils

Information indices from Ecosystem Network Analysis (ENA) can be used to quantify the development of an ecosystem in terms of its size and organization. There are two types of indices, i.e. absolute indices that describe both the size and organization of ecosystem (Total System Throughput (TST)—system size, Ascendancy (A)—size of organized flows and Development Capacity (C)—upper limit for A, Overhead (L)—size of unorganized flows) and relative indices that describe only the organization (Average Mutual Information (AMI = A:TST), Flow Diversity (H = C:TST), Relative Overhead (RL = L:TST)).It is theorized that environmental stress impair the ecosystem development and that the effect of stress can be quantified with the ENA information indices. Here we applied ENA on a case of environmental stress in a terrestrial ecosystem, i.e. soils that have endured long-term exposure to elevated copper concentration and altered pH.The absolute indices showed an unexpected pattern of response to pollution, suggesting that ecosystems in polluted soils are more active and better organized than these in unpolluted soils. The relative indices, alternatively, responded to pollution as predicted by theory, i.e. with decrease of stress (pollution level) the level of specialization increased (increase of AMI) and losses of energy, e.g. due to respiration, decreased (decrease of Overhead). The diversity and evenness of flows showed hump-backed relationship with stress. Less polluted soils appeared to be less vulnerable to external disturbances and more efficient in processing energy (higher Relative Ascendancy (RA = A:C)) than polluted soils. The relative information indices were rigid to changes in values of assumed parameters. The relative indices, opposite to absolute indices, appeared to be useful as indicators of environmental stress on the ecosystem level.     

Three-dimensional modeling of the lower trophic levels in the Ria de Aveiro (Portugal)

The water and the ecosystem dynamics of the Ria de Aveiro, a shallow, multi-branch lagoon located on the northwest coast of Portugal, are simulated using a new fully coupled 3D modeling system. This model couples the hydrodynamic model SELFE (semi-implicit Eulerian-Lagrangian finite element) and an ecological model extended from EcoSim 2.0 to represent zooplankton dynamics. The model application is based on an unstructured grid spatial discretization, which is particularly appropriate for this system given its complex geometry. The baroclinic circulation is calibrated and validated for different environmental conditions, leading to velocity errors smaller than 5 cm/s across the lagoon. Ecological simulations, focused on zooplankton dynamics represented by a site-specific formulation, are then presented and compared against field data for two contrasting environmental conditions: Autumn 2000 and Spring 2001. Results show that the fully coupled model is able to reproduce the dynamics of the ecosystem in the Spring 2001, fitting the model results inside the range of data variation. During this period zooplankton differences between data and model results are of about 0.005 mg C/l (60%), while other ecological tracers’ differences are generally smaller than 20–30% along the several branches of the lagoon. In the Autumn 2000, the model tends to overestimate zooplankton by a factor of 10 and to underestimate phytoplankton and ammonium, with discrepancies of about 0.1 mg C/l and 4.8 μmol N/l, respectively. Factors like the ecological conditions imposed at the boundaries, the input parameters of the ecological model and the simplification of the ecosystem structure, since phytoplankton is the only primary producer considered, may explain the observed differences.     

Analyzing and modelling spatial distribution of summering lesser kestrel: The role of spatial autocorrelation

In modelling spatial distribution of species, ignoring spatial autocorrelation (SA) and multicollinearity may lead to false ecological conclusions. Here we take into account both issues for examining and modelling the spatial pattern of abundance of the globally threatened lesser kestrel (Falco naumanni) during summer in a 38,400 ha area of northwestern Spain where large premigratory aggregations of the species occur. Spatial pattern was examined using Moran's correlogram, and models were built including geographical coordinates and autocovariate terms (which account for SA) in generalized linear models (GLM) and hierarchical partitioning (HP) models. HP models allow to alleviate multicollinearity. A grid-based approach was used by dividing the study area in 24 contiguous 4 km × 4 km squares where birds were counted in 2–3 visits per square (response variable). Environmental coarse-grained variables were extracted from a geographic information system (GIS) at three spatial extents. Moran's correlogram showed that lesser kestrel mean abundance per square was spatially autocorrelated up to 4–8 km. The results from both GLM and HP analyses were roughly compatible. The GLM models explained 80.0% of the variation in kestrel abundance and were the same at the three spatial extents. Lesser Kestrel abundance was not significantly explained by landscape variables, but was negatively related to both the distance to the nearest communal roost and distance to the nearest breeding colony with more of 10 breeding pairs of lesser kestrel. An autocovariate term added later in the GLM models improved both their explanatory power (from 74.5 to 80.0%) and model residuals, which were not longer spatially autocorrelated, fulfilling thus the statistical assumption of independent errors. Findings suggest that the spatial distribution of abundance of summering lesser kestrel is, at least, partially driven by endogenous causes, such as conspecific attraction. Exogenous causes such as finer-scale variables (e.g. type of crops and food available) are yet likely needed for lesser kestrel-environment relationships.     

A method for building spatial model of annual weed seed dispersal from experimental data and its application to simulating Bromus sterilis population dispersal

Spatial model of annual weed seed dispersal, in this article, was theoretically derived. According to the requirements of building the spatial model, we designed and done an indoor experiment of weed seed dispersal by wind. In the experiment, the seeds of Bromus sterilis were released at 100 cm height under different wind velocity conditions. Based on the experimental data, the spatial models of seed dispersal of the weed species were built, which were divided into three types according to the coefficient β < 0, β = 0, β > 0. The results showed that dispersal of annual weed seed in any direction obeyed an approximate Gaussian distribution; under the experimental conditions, spatial distribution type of weed seed dispersal changed with variation of wind velocity. Well-known Howard et al.'s model (Howard et al., 1991) of Bromus sterilis seed dispersal is an especial example of the model built in this article. The result of model analysis indicated that the distribution type described by Howard's model was similar to that of seed dispersal of the weed species at the height of 100 cm under the condition of lower wind velocity (about 2.18 m/s). Using CA simulation analysis we found that mean control agent applying to a cell with weed should have a decrease with an increase of wind velocity to prevent weed with the initial configuration from spreading, which implicated less herbicide needs spraying in every cell with weed on average when wind velocity increases.     

Accelerating Forest Succession in a Fragmented Landscape: The Role of Birds and Perches

Previous research suggests that in highly fragmented forest landscapes ecological succession can be arrested by lack of seeds, but that seed deposition abundance and diversity of bird-dispersed plants can be enhanced by bird-attracting structures such as snags. Consequently, bird perches remain a potential tool for accelerating ecological succession and reforesting disturbed land. Consequently, in order to determine the effectiveness of bird perches in reclaiming forested landscapes, seed dispersal, seedbank storage, and recruitment of bird-dispersed plants was studied on a central Florida mined site with clay-rich soil undergoing primary succession over a seven-year period. Data collection included 20 continuous months of seed dispersal data, an analysis of the total and germinable seedbanks, and plant recruitment at one and two years after a fire destroyed perches and burnt vegetation. Seed dispersal to perches reached a peak seedfall by weight in August, which was attributable to nonmigratory birds. Myrica cerifera, the most abundant species dispersed to the sites, was the only species dispersed during the winter and spring months, and it may be a keystone species for the frugivorous bird guild in central Florida. Seedfall beneath perches had a higher diversity of seed genera, and seed numbers (340 seeds m⁻² yr⁻¹) were 150 times greater than in sites without perches. Seeds of bird-dispersed plants in the seedbank under perches numbered 77 ± 33 (m⁻²) in total and 17 ± 5 for the viable seedbank. The population density of bird-dispersed plants was 1.4 and 2.0 plants m⁻² at one and two years afler the fire. Less than 0.06% of the dispersed seeds survived to become seedlings. Species composition shifted from seedfall to seedlings, with small-seeded, early-successional (r-selected) shrubs and herbs becoming relatively more common than the desired large-seeded, late-successional (K-selected) tree species. Perches attracted birds and associated seeds, but the physically harsh conditions created by primary succession and/or high predation on seeds appeared to reduce the success of the desired late-successional plant species. Nonetheless, there was a higher abundance and diversity of bird-dispersed plants under perches, suggesting that perch structures have a limited ability to enhance plant diversity under conditions of primary succession.     

Dispersal of seeds by the tropical sea breeze

Given the dependence of most wind-pollinated and wind-dispersed species on low relative humidity (RH) for abscission, and the minimization of RH in the early afternoon, there ought to be a marked directional bias in seed dispersal at sites with a strong local diurnal circulation. We filmed the abscission of seeds of five wind-dispersed tropical species near the coast of Mexico (Jalisco). We found that (1) most abscission occurred during the period from 10:00 to 17:00 hours; (2) there was a strong bias for landward dispersal due to the midday sea breeze; (3) the little nocturnal dispersal that occurred was toward the sea (due to the night land breeze); (4) there was no abscission in the absence of wind (i.e., indoors) except for one species; and (5) holding relative humidity constant, the proportion of seeds diurnally abscising is strongly correlated with horizontal wind speed. We predict that a similar bias (this time for upslope dispersal) for xerochastic dispersal will occur in complex terrain. We conclude that in coastal and mountainous terrain, dispersal models (and inverse modeling efforts) must include a directionality term.     

A process-based model of nitrogen cycling in forest plantations: Part II. Simulating growth and nitrogen mineralisation of Eucalyptus globulus plantations in south-western Australia

We applied a new version of the G’DAY ecosystem model to short-rotation plantations of Eucalyptus globulus growing under a Mediterranean climate in south-western Australia. The new version, that includes modified submodels for biomass production, water balance, litter and soil organic matter (SOM) decomposition, and soil inorganic N balance, was parameterised and applied to three experimental eucalypt sites (Mumballup, Darkan and Northcliffe) of contrasting productivity. With a common base set of parameter values, the model was able to correctly reproduce observed time series of soil water content, canopy leaf area index and stemwood data at the three sites. The model's ability to simulate soil N supply under forest plantations was tested by simulating N mineralisation at each of the three sites over the duration of the experiment (10 years). Simulated annual net N mineralisation in the litter and top 20 cm soil layer ranged from 50 to 170 kg N ha⁻¹ across the sites as a result of differences in rates of litter production, SOM and litter decomposition, and microbial N immobilisation and (re-)mineralisation. Simulations of annual soil N mineralisation were similar to measured rates over a 3-year period, except for an overestimation in 1 year at Mumballup and 2 years at Darkan. Model results indicated the importance of fine root production and turnover for N supply. As plantations age, supply of N to trees increasingly originates from litter decomposition, while the contribution from decomposition of SOM decreases. Although major soil feedbacks associated with litter production, decomposition and N availability are adequately integrated into G’DAY, further work is required in some aspects of the model, including the utility of the C-allocation submodel over a wide range of site conditions and silvicultural treatments.