Weak trophic interactions and the balance of enriched metacommunities

Weak trophic interactions have been shown to promote the stability of ecological food webs characterized by perfect mixing. However, their importance at the landscape level and response to enrichment has not been extensively examined. In this paper we examine the food-web model explored by McCann et al. [1998. Weak trophic interactions and the balance of nature. Nature 395, 794-798]. The model is expanded into a metacommunity construct where local communities are coupled through global or local dispersal. We analyze global and local stability, as well as spatial synchrony in relation to trophic interaction strength and dispersal regimes. Results reveal that weak interactions can operate through two scale-dependent mechanisms: (i) under low local dispersal regimes, local stabilization of each community under weak interactions directly scales-up to global stability. (ii) Under high local dispersal, asynchronous local destabilization associated with weak interactions proves the driver behind global stability. In the face of enrichment, weak trophic interactions are shown to be instrumental in promoting global stability when dispersal is local. These results demonstrate how the importance of weak trophic interactions can be generalized at the landscape level despite contrary local predictions.     

Habitat destruction in mutualistic metacommunities

We investigate a mutualistic metacommunity where the strength of the mutualistic interaction between species is measured by the extent to which the presence of one species on a patch either reduces the extinction rate of the others present on the same patch or increases their ability to colonize other patches. In both cases, a strong enough mutualism enables all species to persist at habitat densities where they would all be extinct in the absence of the interaction. However, a mutualistic interaction that enhances colonization enables the species to persist at lower habitat density than one that suppresses extinction. All species abruptly go extinct (catastrophe) when the habitat density is decreased infinitesimally below a critical value. A comparison of the mean field or spatially implicit case with unrestricted dispersal and colonization to all patches in the system with a spatially explicit case where dispersal is restricted to the immediate neighbours of the original patch leads to the intriguing conclusion that restricted dispersal can be favourable for species that have a beneficial effect on each other when habitat conditions are adverse. When the mutualistic interaction is strong enough, the extinction threshold or critical amount of habitat required for the persistence of all species is lower when the dispersal is locally restricted than when unrestricted ! The persistence advantage for all species created by the mutualistic interaction increases substantially with the number of species in the metacommunity, as does the advantage for restricted dispersal over global dispersal.     

Modelling the morphological response to nutrient availability in the clonal plant Trientalis europaea L.

The morphological responses to changes in environmental quality shown by many clonal plants have been interpreted as an expression of foraging behaviour, as they allow the ramets to become concentrated in more favourable microhabitats. The morphological response to increased nutrient availability in the pseudoannual plant Trientalis europaea was studied in a field experiment. The response was largely size-dependent and consistent with enhanced clonal growth. Fertilized ramets produced more tubers and a larger main tuber. In contrast, stolon length was not affected by the treatment. A spatially explicit simulation model calibrated with data from the field experiment examined the population dynamics of T. europaea ramets in a spatially hetereogeneous, temporally constant, environment. The model showed that T. europaea was effective at concentrating its ramets in favourable patches, but this process was strongly influenced by patch size. The analysis of this response at the clone level showed that ramet aggregation was mainly due to the enhanced performance of clones located initially in the favourable patches, or clones that located a favourable patch by chance. In these clones, the simultaneous increase of ramet size and survival accelerated the production of ramets. The temporal and spatial scale at which the aggregation of ramets in favourable patches was manifested suggests that the effectiveness of the morphological response in T. europaea is favoured by a high spatio-temporal predictability in the environment. Overall, the model emphasized the important role of population dynamics in understanding the nature of the foraging response.     

Effect of systemic diseases on clonal integration: modelling approach

Systemic disease spread has been suggested as a possible disadvantage of clonal plant integration. As connected ramets have higher risk of being infected, disease should cause a selective pressure against clonality. Since experimental tests of this hypothesis are not easy to perform, we chose a modelling approach, by which we could easily separate different factors influencing the process. We used a spatially explicit model of clonal growth with disease spread implemented and we tested the hypothesis that systemic disease decreases the competitive ability of highly integrated clonal plants when compared to less integrated plants with the same parameters. In contrast to our expectations, the integrator was competitively stronger than the splitter in most cases and it lost only when the disease severity and infection rates were very high. We think that the larger the integrated network is, the better the plant utilises its translocation ability. Even a very small amount of resource sharing greatly increased the relative success of the integrator and larger integrators were competitively stronger than the smaller ones. Our results also indicate that although the same infection rate caused more systemic disease in the integrator than in the splitter population, the disease has only a limited potential to select for the splitter strategy. This is caused not only by the advantages of the clonal integration but also by the fact that there is only a small range of infection rates at which there is sufficient difference in disease impact between the strategies.     

Beyond dual-lattice models: Incorporating plant strategies when modeling the interplay between facilitation and competition along environmental severity gradients

We introduce a spatially explicit model that evaluates how the trade-offs between the life strategies of two interacting plant species affect the outcome of their interaction along environmental severity gradients. In our model, we represent the landscape as a two-dimensional lattice, with environmental severity increasing from left to right. Two species with different strategies, a competitor and a stress-tolerant, interact in the lattice. We find that facilitation expands the realized niche of the competitor into harsh environments by suppressing the stress-tolerant species. Most of their coexisting range is dominated by a positive effect of one species on another, with a reciprocal negative effect from the species receiving the benefits on its benefactor (“+, −”), whereas mutualistic (“+, +”) interactions are only found in the harshest part of the environmental gradient. Contrarily as assumed by models commonly used in facilitation research (e.g. dual-lattice models), our results indicate that “+, +” interactions are not dominant, and that their differences with “+, −” interactions along environmental severity gradients depend on the strategies of the interacting species. By integrating the trade-off between competitive ability and stress tolerance, our model provides a new framework to investigate the interplay of facilitative and competitive interactions along environmental gradients and their impacts on processes such as population dynamics and community organization.     

How spatial resource distribution and memory impact foraging success: A hybrid model and mechanistic index

Understanding how animals forage has always been a fundamental issue in Ethology and has become critical more recently in Environmental Conservation. Since the formalization of optimal foraging theory, theoretical models intended to depict the behavior of a generic forager have served as the main tools to analyze and ultimately comprehend the mechanisms of foraging. Due to complexity and technical constraints, these models have traditionally focused on single aspects of foraging, leaving out other concurrent processes that may also interplay. The recent inclusion of several facets inside united models has given rise to interesting results on the importance of interacting factors such as memory and resource heterogeneity.In this paper, we present a hybrid model integrating metabolism, foraging decisions, memory, as well as spatially explicit movement and resource distribution. We use it to examine the effects of spatial resource distribution – an aspect often neglected in favor of probabilistic resource heterogeneity – on the viability of a generic random-walking forager, and rely on the model to devise an ecological metric that can explain and render the relative profitability of given spatial distributions. Furthermore, we assess the significance of memory properties relatively to the profitability of resource distributions. Most notably, we reveal contrasted effects of memory depending on the aspect of resource varied in space (i.e. prey abundance, or prey body mass).On the whole, a general comparison of our findings with results obtained with spatially implicit models leads us to stress the complex interaction between memory and spatial resource distribution as well as the criticality of spatial representation in the modeling of foraging. Accordingly, we conclude with a discussion on the ecological implications of these results, as well as the advantages of hybrid modeling for the accurate simulation of foraging.     

Do species population parameters and landscape characteristics affect the relationship between local population abundance and surrounding habitat amount?

In landscape ecology, correlational approaches are typically used to analyse links between local population abundance, and the surrounding habitat amount to estimate biologically-relevant landscape size (extent) for managing endangered or pest populations. The direction, strength, and spatial extent of the correlations are then sometimes interpreted in terms of species population parameters. Here we simulated the population dynamics of generalized species across spatially explicit landscapes that included two distinct habitat types. We investigated how characteristics of a landscape (structure), including the variation in habitat quality and spatial aggregation of the habitat, and the precise population-dynamic properties of the simulated species (dispersal and growth rates) affect the correlation between population abundance and amount of surrounding favourable habitat in the landscape. To evaluate these spatial extents of correlation, proportions of favourable habitat were calculated within several circles of increasing diameter centred on sampling patches of favourable habitat where population abundance was recorded.We found that the value of the correlation coefficients between population abundance and amount of surrounding favourable habitat depended on both population dynamic parameters and landscape characteristics. Coefficients of correlation increased with the variation in habitat quality and the aggregation of favourable habitat in the landscape, but decreased with the dispersal distance. The distance at which the correlation was maximized was sensitive to an interaction between the level of aggregation of the habitat and the dispersal distance; whereas the greatest distance at which a significant correlation occurred was more sensitive to the variation in habitat quality. Our results corroborate the view that correlational analyses do provide information on the local population dynamics of a species in a given habitat type and on its dispersal rate parameters. However, even in simplified, model frameworks, direct relationships are often difficult to disentangle and global landscape characteristics should be reported in any studies intended to derive population-dynamic parameters from correlations. Where possible, replicated landscapes should be examined in order to control for the interaction between population dynamics and landscape structure. Finally, we recommend using species-specific, population-dynamic modelling in order to interpret correctly the observed patterns of correlation in the landscape.     

空间直观景观模型LANDIS Ⅰ．运行机制

空间直观景观模型是指在异质景观中模拟景观尺度上生态过程的空间直观模型．LANDIS是一个用于模拟森林景观干扰、演替和管理的空间直观景观模型．通过在样地尺度上跟踪以10年为间隔的物种年龄级,半定量化地描述火和风倒,及使用位数组表示物种年龄结构,LANDIS能同时在物种、样地和景观尺度上模拟各种生态过程及其相互关系．详细论述了LANDIS模型对种子传播、火、风倒和砍伐等生态过程的模拟,并讨论了模型中存在的一些不足．     

空间直观景观模型在呼中林区土壤侵蚀预测研究中的初步应用

土壤通用流失方程(USLE)已被广泛应用于大尺度的土壤侵蚀预测．在以往的土壤侵蚀研究中,由于只能获得静态的植被图,土壤通用流失方程只能用于土壤侵蚀的静态估算．空间直观景观模型能在大尺度上模拟植被动态,为土壤通用流失方程提供动态的植被因子,从而使土壤侵蚀的动态模拟成为可能．本研究结合空间直观景观模型LANDIS和土壤通用流失修正方程,以大兴安岭呼中林区为研究区。动态地模拟未来650年内有采伐和无采伐预案下的土壤侵蚀量;同时以无火无采伐预案下的土壤侵蚀为对比值．结果表明,土壤侵蚀量随时间变化呈周期性的波动,其波动程度在无火无采伐预案下最小,而在有火无采伐预案下最大;采伐对土壤侵蚀的影响没有火对土壤侵蚀的影响在空间上表现得明显,但是其累积效果则比火的影响强;降低采伐所产生的裸露土能有效降低年平均土壤侵蚀量,但是对土壤侵蚀动态变化的影响不明显;虽然采伐增加使平均土壤侵蚀量增加,但是也同时使土壤侵蚀的年际变化更趋于平稳．     

Spatial models of virus-immune dynamics

To date, the majority of theoretical models describing the dynamics of infectious diseases in vivo are based on the assumption of well-mixed virus and cell populations. Because many infections take place in solid tissues, spatially structured models represent an important step forward in understanding what happens when the assumption of well-mixed populations is relaxed. Here, we explore models of virus and virus-immune dynamics where dispersal of virus and immune effector cells was constrained to occur locally. The stability properties of our spatial virus-immune dynamics models remained robust under almost all biologically plausible dispersal schemes, regardless of their complexity. The various spatial dynamics were compared to the basic non-spatial dynamics and important differences were identified: When space was assumed to be homogeneous, the dynamics generated by non-spatial and spatially structured models differed substantially at the peak of the infection. Thus, non-spatial models may lead to systematic errors in the estimates of parameters underlying acute infection dynamics. When space was assumed to be heterogeneous, spatial coupling not only changed the equilibrium properties of the uncoupled populations but also equalized the dynamics and thereby reduced the likelihood of dynamic elimination of the infection. In line with experimental and clinical observations, long-lasting oscillation periods were virtually absent. When source-sink dynamics were considered, the long-term outcome of the infection depended critically on the degree of spatial coupling. The infection collapsed when emigration from source sites became too large. Finally, we discuss the implications of spatially structured models on medical treatment of infectious diseases, and note that a huge gap exists in data accurately describing infection dynamics in solid tissues.     

Extrapolation methods for climate time series revisited – Spatial correlations in climatic fluctuations influence simulated tree species abundance and migration

Simulations of tree population dynamics under past and future climatic changes with time- and space-discrete models often suffer from a lack of detailed long-term climate time series that are required to drive these models. Inter- and extrapolation methods which are applied to generate long-term series differ in terms of whether they do or do not account for spatial correlation of climatic fluctuations. In this study we compared tree species abundance and migration outcomes from simulations using extrapolation methods generating spatially correlated (SC) and spatially independent (SI) climatic fluctuations. We used the spatially explicit and linked forest-landscape model TreeMig and a simple cellular automaton to demonstrate that spatial correlation of climatic fluctuations affects simulation outcomes. We conclude that methods to generate long-term climate time series should account for the spatial correlation of climatic fluctuations found in available climate records when simulating tree species abundance and migration.     

Expansion of Brown Bears (Ursus arctos) into the Eastern Alps: A Spatially Explicit Population Model

We present a spatially explicit population model for analysing the expansion of brown bears (Ursus arctos) after the reintroduction program in central Austria. The model is based on field investigations into brown bears in Austria and Slovenia and on current knowledge of brown bears. The landscape of the eastern Alps is represented by a GIS-derived raster map defining local habitat suitability and five major spatial barriers to dispersal. The population model follows the fate of individual bears and simulates reproduction, dispersal, home range establishment, and mortality in annual time steps. We indirectly adjust unknown or uncertain model parameters with 10-year data on the number of females with cubs in central Austria and determine key variables of population dynamics, such as population sizes and growth rates within different population nuclei, dispersal distances, or mortality rates, for model parameterisations that reproduce the data on females with cubs. We estimated a current (1996–2000) growth rate of the population in Austria and adjacent parts of Italy of some 14%; a high proportion of this growth was due toimmigration from Slovenia. Consequently, the growth rate of the subpopulation in central Austria, which probably is isolated functionally (i.e., no exchange of females) from the nuclei along the Austrian–Slovenian border, yielded some 7%. This subpopulation may comprise seven residents, and we estimated for females a 33% risk of extinction during the 1992–2000 period. Validation and confirmation of our model results with data on bear densities that were not used for model construction and parameterisation supported our findings. The high female mortality rates, together with the vulnerability of the small population to chance events (i.e., demographic stochasticity), are the most pressing threat for the population in the eastern Alps. Our approach could be widely applied for analysing dynamics of rare and endangered species in which the paucity of data precludes an appraisal of the state of the population using standard methods.     

The importance of dispersal in determining seed versus safe site limitation of plant populations

The traditional dichotomy of seed versus safe site limitation of plant populations is an oversimplification. While most plant models implicitly assume that the number of safe sites colonized will increase directly with increased seed production by each plant, the number of sites colonized may also strongly depend on patterns of seed dispersal relative to the parent plant, since the majority of a plant’s seeds are deposited very close to it and so not all safe sites are equally accessible. I created a series of spatially explicit individual based plant population models exploring how seed versus safe site limitation is jointly affected by the number of seeds produced per plant and mean dispersal distances. While increased dispersal distance led to reduced seed limitation (more saturation of available safe sites) when a parent plant’s site was temporarily unsuitable following its death, increased dispersal distances could increase seed limitation, especially at low per-plant fecundities, if safe sites did not turn over through time. Models comparing localized to global seed dispersal indicated substantially different degrees of seed limitation for constant per-plant fecundities. Thus seed addition experiments need to be designed to add seeds in realistic spatial patterns to yield meaningful results.     

Establishing a beachhead: a stochastic population model with an Allee effect applied to species invasion

We formulated a spatially explicit stochastic population model with an Allee effect in order to explore how invasive species may become established. In our model, we varied the degree of migration between local populations and used an Allee effect with variable birth and death rates. Because of the stochastic component, population sizes below the Allee effect threshold may still have a positive probability for successful invasion. The larger the network of populations, the greater the probability of an invasion occurring when initial population sizes are close to or above the Allee threshold. Furthermore, if migration rates are low, one or more than one patch may be successfully invaded, while if migration rates are high all patches are invaded.     

Simulating Mediterranean landscape pattern and vegetation dynamics under different fire regimes

In the Mediterranean Basin, landscape patterns are strongly human-modified. In recent decades, because of industrialisation and rural exodus, many fields have been abandoned, generating changes in the landscape pattern. In this framework, I aim to study the effect of landscape pattern on landscape dynamic processes in the Mediterranean Basin using simulation models and considering that fire may interact with landscape pattern. First I generate a gradient of five artificial random landscapes. In each landscape I include four species types growing in the Mediterranean Basin, each type with different plant traits (Quercus, Pinus, Erica and Cistus types). In each landscape scenario, each species covers 30% of the landscape but with a different spatial distribution, from the coarsest-grained (L1) to the finest-grained (L5). Then, the dynamics of each of these five landscapes were simulated for 100 years using the FATELAND simulation model. Simulations were run with six fire regime scenarios in each landscape scenario (no fire, mean fire interval of 80, 40, 20, 10 and 5 years). Landscape attributes were computed for the initial and the final landscapes. As expected, the results suggest that, as expected, some species increase and others decrease depending on the fire regime. However, the results also show that different landscape structures produce different dynamics and thus that there is a clear interaction between landscape pattern and fire regime. For instance, coarse-grained spatial patterns generate slower dynamics than fine-grained patterns, and fire-sensitive species are maintained longer under coarse-grained patterns (i.e., fragmentation accelerates extinction of fire-sensitive species).A draft version of this paper was presented at the Special Symposium “Global Change and Landscape Fires” held during the IALE World Congress, in Darwin, Australia, 13–17 July 2003.     

Dealing with Uncertainty in Spatially Explicit Population Models

It has been argued that spatially explicit population models (SEPMs) cannot provide reliable guidance for conservation biology because of the difficulty of obtaining direct estimates for their demographic and dispersal parameters and because of error propagation. We argue that appropriate model calibration procedures can access additional sources of information, compensating the lack of direct parameter estimates. Our objective is to show how model calibration using population-level data can facilitate the construction of SEPMs that produce reliable predictions for conservation even when direct parameter estimates are inadequate. We constructed a spatially explicit and individual-based population model for the dynamics of brown bears (Ursus arctos) after a reintroduction program in Austria. To calibrate the model we developed a procedure that compared the simulated population dynamics with distinct features of the known population dynamics (=patterns). This procedure detected model parameterizations that did not reproduce the known dynamics. Global sensitivity analysis of the uncalibrated model revealed high uncertainty in most model predictions due to large parameter uncertainties (coefficients of variation CV 0.8). However, the calibrated model yielded predictions with considerably reduced uncertainty (CV 0.2). A pattern or a combination of various patterns that embed information on the entire model dynamics can reduce the uncertainty in model predictions, and the application of different patterns with high information content yields the same model predictions. In contrast, a pattern that does not embed information on the entire population dynamics (e.g., bear observations taken from sub-areas of the study area) does not reduce uncertainty in model predictions. Because population-level data for defining (multiple) patterns are often available, our approach could be applied widely.     

Spatial distribution of soil seed banks of three African savanna woody species at two contrasting sites

In southern African savannas, bush encroachment is a major problem for range managers. However, little is understood of the actual regeneration processes leading to it, and in particular the role of soil seed banks. The horizontal (between microsites) and vertical (with depth in litter and soil) distribution of soil seed banks of the microphyllous woody species, Acacia tortilis, A. nilotica and Dichrostachys cinerea (all legumes of the Mimosoideae), were quantified in an area with low intensity grazing (reserve), and a bordering cattle farm with high intensity grazing (farm). Species differed in seed bank densities between microsites and sites. Seed densities for all species were highest below parent tree canopies and decreased with distance beyond the canopy, and with soil depth. D. cinerea had the smallest seed bank associated with parent trees, particularly on the farm (8 vs. 1643 seeds/tree on the reserve), A. tortilis had the largest (6357, 31910), with A. nilotica intermediate (1789, 1906). The proportion of current (recently fallen) versus old (1 year old) seeds differed between species and sites. These species form at least short-term persistent seed banks with the old seeds largely representing the persistent seed bank. Seed densities in the open (inter-canopy) and those dispersed under either of the other two (non-parental) study species were much lower than those associated with parent trees. The latter were mostly found under the acacias (single-stemmed) rather than D. cinerea (multistemmed). Total seed store per parent plant increased with plant size (best fits were mostly power curves of canopy area). A large proportion of intact seeds were viable, namely 81–84% for A. tortilis, 68–77% for A. nilotica and 63–78% for D. cinerea, with no differences between sites. Viability tended to increase with depth of burial, except for A. nilotica seeds at the 3–5 cm depths on the farm. At the landscape scale there were 1.5 million and 140000 A. tortilis seeds/ha on the reserve and farm respectively, with corresponding values of 2000 and 31000 for D. cinerea, and 23000 and 86000 for A. nilotica.