Honey bee colony performance affected by crop diversity and farmland structure: a modeling framework.

Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics, PH and PP, which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower, PH and PP were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, and PH (269.5 kg) and PP (108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.

The extent of functional redundancy changes as species' roles shift in different environments.

Assessing the ecological impacts of environmental change requires knowledge of the relationship between biodiversity and ecosystem functioning. The exact nature of this relationship can differ considerably between ecosystems, with consequences for the efficacy of species diversity as a buffer against environmental change. Using a microbial model system, we show that the relationship can vary depending on environmental conditions. Shapes suggesting functional redundancy in one environment can change, suggesting functional differences in another environment. We find that this change is due to shifting species roles and interactions. Species that are functionally redundant in one environment may become pivotal in another. Thus, caution is advised in drawing conclusions about functional redundancy based on a single environmental situation. It also implies that species richness is important because it provides a pool of species with potentially relevant traits. These species may turn out to be essential performers or partners in new interspecific interactions after environmental change. Therefore, our results challenge the generality of functional redundancy.

Transience after disturbance: Obligate species recovery dynamics depend on disturbance duration.

After a disturbance event, population recovery becomes an important species response that drives ecosystem dynamics. Yet, it is unclear how interspecific interactions impact species recovery from a disturbance and which role the disturbance duration (pulse or press) plays. Here, we analytically derive conditions that govern the transient recovery dynamics from disturbance of a host and its obligately dependent partner in a two-species metapopulation model. We find that, after disturbance, species recovery dynamics depend on the species' role (i.e. host or obligately dependent species) as well as the duration of disturbance. Host recovery starts immediately after the disturbance. In contrast, for obligate species, recovery depends on disturbance duration. After press disturbance, which allows dynamics to equilibrate during disturbance, obligate species immediately start to recover. Yet, after pulse disturbance, obligate species continue declining although their hosts have already begun to increase. Effectively, obligate species recovery is delayed until a necessary host threshold occupancy is reached. Obligates' delayed recovery arises solely from interspecific interactions independent of dispersal limitations, which contests previous explanations. Delayed recovery exerts a two-fold negative effect, because populations continue declining to even smaller population sizes and the phase of increased risk from demographic stochastic extinction in small populations is prolonged. We argue that delayed recovery and its determinants -species interactions and disturbance duration - have to be considered in biodiversity management.

Transient recovery dynamics of a predator-prey system under press and pulse disturbances.

BACKGROUND: Species recovery after disturbances depends on the strength and duration of disturbance, on the species traits and on the biotic interactions with other species. In order to understand these complex relationships, it is essential to understand mechanistically the transient dynamics of interacting species during and after disturbances. We combined microcosm experiments with simulation modelling and studied the transient recovery dynamics of a simple microbial food web under pulse and press disturbances and under different predator couplings to an alternative resource. RESULTS: Our results reveal that although the disturbances affected predator and prey populations by the same mortality, predator populations suffered for a longer time. The resulting diminished predation stress caused a temporary phase of high prey population sizes (i.e. prey release) during and even after disturbances. Increasing duration and strength of disturbances significantly slowed down the recovery time of the predator prolonging the phase of prey release. However, the additional coupling of the predator to an alternative resource allowed the predator to recover faster after the disturbances thus shortening the phase of prey release. CONCLUSIONS: Our findings are not limited to the studied system and can be used to understand the dynamic response and recovery potential of many natural predator-prey or host-pathogen systems. They can be applied, for instance, in epidemiological and conservational contexts to regulate prey release or to avoid extinction risk of the top trophic levels under different types of disturbances.

A protocol for better design, application, and communication of population viability analyses.

Population viability analyses (PVAs) contribute to conservation theory, policy, and management. Most PVAs focus on single species within a given landscape and address a specific problem. This specificity often is reflected in the organization of published PVA descriptions. Many lack structure, making them difficult to understand, assess, repeat, or use for drawing generalizations across PVA studies. In an assessment comparing published PVAs and existing guidelines, we found that model selection was rarely justified; important parameters remained neglected or their implementation was described vaguely; limited details were given on parameter ranges, sensitivity analysis, and scenarios; and results were often reported too inconsistently to enable repeatability and comparability. Although many guidelines exist on how to design and implement reliable PVAs and standards exist for documenting and communicating ecological models in general, there is a lack of organized guidelines for designing, applying, and communicating PVAs that account for their diversity of structures and contents. To fill this gap, we integrated published guidelines and recommendations for PVA design and application, protocols for documenting ecological models in general and individual-based models in particular, and our collective experience in developing, applying, and reviewing PVAs. We devised a comprehensive protocol for the design, application, and communication of PVAs (DAC-PVA), which has 3 primary elements. The first defines what a useful PVA is; the second element provides a workflow for the design and application of a useful PVA and highlights important aspects that need to be considered during these processes; and the third element focuses on communication of PVAs to ensure clarity, comprehensiveness, repeatability, and comparability. Thereby, DAC-PVA should strengthen the credibility and relevance of PVAs for policy and management, and improve the capacity to generalize PVA findings across studies.

The relevance of conditional dispersal for bacterial colony growth and biodegradation.

Bacterial degradation is an ecosystem service that offers a promising method for the remediation of contaminated soils. To assess the dynamics and efficiency of bacterial degradation, reliable microbial simulation models, along with the relevant processes, are required. We present an approach aimed at improving reliability by studying the relevance and implications of an important concept from theoretical ecology in the context of a bacterial system: conditional dispersal denoting that the dispersal strategy depends on environmental conditions. Different dispersal strategies, which either incorporate or neglect this concept, are implemented in a bacterial model and results are compared to data obtained from laboratory experiments with Pseudomonas putida colonies growing on glucose agar. Our results show that, with respect to the condition of resource uptake, the model's correspondence to experimental data is significantly higher for conditional than for unconditional bacterial dispersal. In particular, these results support the hypothesis that bacteria disperse less when resources are abundant. We also show that the dispersal strategy has a considerable impact on model predictions for bacterial degradation of resources: disregarding conditional bacterial dispersal can lead to overestimations when assessing the performance of this ecosystem service.

Neutral communities may lead to decreasing diversity-disturbance relationships: insights from a generic simulation model.

Many attempts have been made to confirm or reject the unimodal relationship between disturbance and diversity stated by the intermediate disturbance hypothesis (IDH). However, the reasons why the predictions of the IDH apply or fail in particular systems are not always obvious. Here, we use a spatially explicit, individual-based community model that simulates species coexistence in a landscape subjected to disturbances to compare diversity-disturbance curves of communities with different coexistence mechanisms: neutrality, trade-off mechanism and intraspecific density dependence. We show that the shape of diversity-disturbance curves differs considerably depending on the type of coexistence mechanism assumed: (1) Neutral communities generally show decreasing diversity-disturbance curves with maximum diversity at zero disturbance rates contradicting the IDH, whereas trade-off communities generally show unimodal relationships confirming the IDH and (2) density-dependent mechanisms do increase the diversity of both neutral and trade-off communities. Finally, we discuss how these mechanisms determine diversity in disturbed landscapes.

Rapid viability analysis for metapopulations in dynamic habitat networks.

For land-use planning, numerically fast and easily applicable tools are urgently needed that allow us to assess how landscape structure and dynamics affect biodiversity. To date, such tools exist only for static landscapes. We provide an analytical formula for the mean lifetime of species in fragmented and dynamic habitat networks where habitat patches may be destroyed and created elsewhere. The formula is able to consider both patch size heterogeneity and dynamics additionally to patch number and connectivity. It is validated through comparison with a dynamic and spatially explicit simulation model. It can be used for the optimization of spatio-temporal land-use patterns in real landscapes and for advancing our general understanding of key processes affecting the survival of species in fragmented heterogeneous dynamic landscapes.

Hutchinson revisited: patterns of density regulation and the coexistence of strong competitors.

Ecologists have long been searching for mechanisms of species coexistence, particularly since G.E. Hutchinson raised the 'paradox of the plankton'. A promising approach to solve this paradox and to explain the coexistence of many species with strong niche overlap is to consider over-compensatory density regulation with its ability to generate endogenous population fluctuations. Previous work has analysed the role of over-compensation in coexistence based on analytical approaches. Using a spatially explicit time-discrete simulation model, we systematically explore the dynamics and conditions for coexistence of two species. We go beyond the analytically accessible range of models by studying the whole range of density regulation from under- to very strong over-compensation and consider the impact of spatial structure and temporal disturbances. In particular, we investigate how coexistence can emerge in different types of population growth models. We show that two strong competitors are able to coexist if at least one species exhibits over-compensation. Analysing the time series of population dynamics reveals how the differential responses to density fluctuations of the two competitors lead to coexistence: The over-compensator generates density fluctuations but is the inferior competitor at strong amplitudes of those fluctuations; the competitor, therefore, becomes frequent and dampens the over-compensator's amplitudes, but it becomes inferior under dampened fluctuations. These species interactions cause a dynamic alternation of community states with long-term persistence of both species. We show that a variety of population growth models is able to reproduce this coexistence although the particular parameter ranges differ among the models. Spatial structure influences the probability of coexistence but coexistence is maintained for a broad range of dispersal parameters. The flexibility and robustness of coexistence through over-compensation emphasize the importance of nonlinear density dependence for species interactions, and they also highlight the potential of applying more flexible models than the classical Lotka-Volterra equations in community ecology.

Designing cost-effective payments for conservation measures to generate spatiotemporal habitat heterogeneity.

Many endangered species depend on certain types of agricultural or other forms of human land use. To conserve such species, schemes are set up in which land users receive payments for voluntarily managing their land in a biodiversity-enhancing manner. We developed a model-based framework for designing cost-effective payment schemes that generate spatiotemporal habitat heterogeneity to maximize the survival of multiple species under budget constraints. The framework integrates ecological and economic knowledge and consists of the derivation of an ecological benefit function and a budget function that are then combined to determine the cost-effective degree of spatiotemporal habitat heterogeneity. The ecological benefit function considers the timing of conservation measures, the induced habitat dynamics, and different degrees of substitutability among species. The budget function considers that the conservation agency may lack information about land users' individual conservation costs and personal attitudes and that land users can choose among different conservation measures. We applied the framework to a case study of grassland management, where the survival of three endangered species protected by the EU Habitats Directive depends on different types of land use. The lack of information available to the agency and the choice options of land users reduced the amount of conservation that can be financed with a given budget. Neglecting such findings may lead to an overestimation of the benefits of conservation programs.

A critical evaluation of ecological indices for the comparative analysis of microbial communities based on molecular datasets.

In times of global change and intensified resource exploitation, advanced knowledge of ecophysiological processes in natural and engineered systems driven by complex microbial communities is crucial for both safeguarding environmental processes and optimising rational control of biotechnological processes. To gain such knowledge, high-throughput molecular techniques are routinely employed to investigate microbial community composition and dynamics within a wide range of natural or engineered environments. However, for molecular dataset analyses no consensus about a generally applicable alpha diversity concept and no appropriate benchmarking of corresponding statistical indices exist yet. To overcome this, we listed criteria for the appropriateness of an index for such analyses and systematically scrutinised commonly employed ecological indices describing diversity, evenness and richness based on artificial and real molecular datasets. We identified appropriate indices warranting interstudy comparability and intuitive interpretability. The unified diversity concept based on 'effective numbers of types' provides the mathematical framework for describing community composition. Additionally, the Bray-Curtis dissimilarity as a beta-diversity index was found to reflect compositional changes. The employed statistical procedure is presented comprising commented R-scripts and example datasets for user-friendly trial application.

Does red noise increase or decrease extinction risk? Single extreme events versus series of unfavorable conditions.

Recent theoretical studies have shown contrasting effects of temporal correlation of environmental fluctuations (red noise) on the risk of population extinction. It is still debated whether and under which conditions red noise increases or decreases extinction risk compared with uncorrelated (white) noise. Here, we explain the opposing effects by introducing two features of red noise time series. On the one hand, positive autocorrelation increases the probability of series of poor environmental conditions, implying increasing extinction risk. On the other hand, for a given time period, the probability of at least one extremely bad year ("catastrophe") is reduced compared with white noise, implying decreasing extinction risk. Which of these two features determines extinction risk depends on the strength of environmental fluctuations and the sensitivity of population dynamics to these fluctuations. If extreme (catastrophic) events can occur (strong noise) or sensitivity is high (overcompensatory density dependence), then temporal correlation decreases extinction risk; otherwise, it increases it. Thus, our results provide a simple explanation for the contrasting previous findings and are a crucial step toward a general understanding of the effect of noise color on extinction risk.

Integrating economic costs into the analysis of flexible conservation management strategies.

Flexible conservation management, where measures (e.g., mowing of meadows, removing invasive species) are selected in each decision period depending on the current state of the ecological system, is generally perceived as superior to fixed management, where the same measure is applied in each decision period independent of the current state of the system. In past comparisons of fixed and flexible conservation strategies the additional costs that arise only in flexible strategies have usually been ignored. In this paper, we present a framework to integrate costs of flexible management into the evaluation of flexible conservation strategies. Using the example of an endangered butterfly species we demonstrate that the costs of flexible management may reverse the rank order of flexible and fixed conservation strategies, such that fixed strategies may lead to better ecological results than flexible ones for the same financial budget.

Predation effects on the evolution of life-history traits in a clonal oligochaete.

Although size at maturity and size and number of offspring are life-history traits widely studied in sexual and parthenogenetic reproduction, there is no such research on animals reproducing asexually without the involvement of gametes. Here we present an individual-based model in combination with experiments to study the clonal growth of Stylaria lacustris, an oligochaete reproducing through fission. We studied the effect of individual size at fission and fission ratio on clone fitness. Our results show that in benign environments without predators, fitness is higher when small worms produce small offspring. Then we included size-specific sublethal predation and found that the fitness of the clone is maximized when parental worms start fission at a large size and produce large descendants intercalated in the middle of the parental worm's body. These results agree with empirical findings. Furthermore, the results of our own laboratory experiment revealed that when S. lacustris is exposed to chemical alarm signals from injured conspecifics, it alters its life history in the same direction as predicted by the model. Our findings suggest that the effect of size-specific sublethal predation is similar to the effect of size-specific lethal predation because both modes of predation result in size-dependent prey mortality.

On the sympatric evolution and evolutionary stability of coexistence by relative nonlinearity of competition.

If two species exhibit different nonlinear responses to a single shared resource, and if each species modifies the resource dynamics such that this favors its competitor, they may stably coexist. This coexistence mechanism, known as relative nonlinearity of competition, is well understood theoretically, but less is known about its evolutionary properties and its prevalence in real communities. We address this challenge by using adaptive dynamics theory and individual-based simulations to compare community stabilization and evolutionary stability of species that coexist by relative nonlinearity. In our analysis, evolution operates on the species' density-compensation strategies, and we consider a trade-off between population growth rates at high and low resource availability. We confirm previous findings that, irrespective of the particular model of density dependence, there are many combinations of overcompensating and undercompensating density-compensation strategies that allow stable coexistence by relative nonlinearity. However, our analysis also shows that most of these strategy combinations are not evolutionarily stable and will be outcompeted by an intermediate density-compensation strategy. Only very specific trade-offs lead to evolutionarily stable coexistence by relative nonlinearity. As we find no reason why these particular trade-offs should be common in nature, we conclude that the sympatric evolution and evolutionary stability of relative nonlinearity, while possible in principle, seems rather unlikely. We speculate that this may, at least in part, explain why empirical demonstrations of this coexistence mechanism are rare, noting, however, that the difficulty to detect relative nonlinearity in the field is an equally likely explanation for the current lack of empirical observations, and that our results are limited to communities with non-overlapping generations and constant resource supply. Our study highlights the need for combining ecological and evolutionary perspectives for gaining a better understanding of community assembly and biogeographic patterns.

Ranking landscape development scenarios affecting natterjack toad (Bufo calamita) population dynamics in Central Poland.

When data are limited it is difficult for conservation managers to assess alternative management scenarios and make decisions. The natterjack toad (Bufo calamita) is declining at the edges of its distribution range in Europe and little is known about its current distribution and abundance in Poland. Although different landscape management plans for central Poland exist, it is unclear to what extent they impact this species. Based on these plans, we investigated how four alternative landscape development scenarios would affect the total carrying capacity and population dynamics of the natterjack toad. To facilitate decision-making, we first ranked the scenarios according to their total carrying capacity. We used the software RAMAS GIS to determine the size and location of habitat patches in the landscape. The estimated carrying capacities were very similar for each scenario, and clear ranking was not possible. Only the reforestation scenario showed a marked loss in carrying capacity. We therefore simulated metapopulation dynamics with RAMAS taking into account dynamical processes such as reproduction and dispersal and ranked the scenarios according to the resulting species abundance. In this case, we could clearly rank the development scenarios. We identified road mortality of adults as a key process governing the dynamics and separating the different scenarios. The renaturalisation scenario clearly ranked highest due to its decreased road mortality. Taken together our results suggest that road infrastructure development might be much more important for natterjack toad conservation than changes in the amount of habitat in the semi-natural river valley. We gained these insights by considering both the resulting metapopulation structure and dynamics in the form of a PVA. We conclude that the consideration of dynamic processes in amphibian conservation management may be indispensable for ranking management scenarios.

Highways versus pipelines: contributions of two fungal transport mechanisms to efficient bioremediation.

Based on experimental studies, two different fungus-mediated transport mechanisms have been suggested to facilitate the bacterial degradation of organic soil pollutants: bacteria may use liquid films around fungal hyphae for quick dispersal ('fungal highways'), and fungi may take up and translocate pollutants through their mycelial network ('fungal pipelines'). Both mechanisms are anticipated to enhance the bioavailability of pollutants to degrading bacteria. Using a microbial simulation model, we therefore investigated their respective efficiency in increasing biodegradation performance. We analysed networks that act either as bacterial dispersal vectors or as pollutant translocation vectors or as a combination of both. Our results suggest that each mechanism can improve biodegradation performance. The degree of improvement, however, varies distinctly depending on the environmental conditions, and is even negligible under certain conditions. Mycelial networks acting as 'highways' allow bacteria to overcome motility restrictions and reach remote areas, whereas networks acting as 'pipelines' may initiate degradation by bringing remote pollutants to bacteria. As a consequence, highest biodegradation improvements often emerge from the combination of both mechanisms. We conclude that 'fungal highways' as well as 'fungal pipelines' should be considered for developing novel bioremediation strategies based on fungus-mediated transport in soils.

Do simple models lead to generality in ecology?

Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems.

Dispersal networks for enhancing bacterial degradation in heterogeneous environments.

Successful biodegradation of organic soil pollutants depends on their bioavailability to catabolically active microorganisms. In particular, environmental heterogeneities often limit bacterial access to pollutants. Experimental and modelling studies revealed that fungal networks can facilitate bacterial dispersal and may thereby improve pollutant bioavailability. Here, we investigate the influence of such bacterial dispersal networks on biodegradation performance under spatially heterogeneous abiotic conditions using a process-based simulation model. To match typical situations in polluted soils, two types of abiotic conditions are studied: heterogeneous bacterial dispersal conditions and heterogeneous initial resource distributions. The model predicts that networks facilitating bacterial dispersal can enhance biodegradation performance for a wide range of these conditions. Additionally, the time horizon over which this performance is assessed and the network's spatial configuration are key factors determining the degree of biodegradation improvement. Our results support the idea of stimulating the establishment of fungal mycelia for enhanced bioremediation of polluted soils.

Spatial synchrony through density-independent versus density-dependent dispersal.

Many theoretical studies support the notion that strong dispersal fosters spatial synchrony. Nonetheless, the effect of conditional vs. unconditional dispersal has remained a matter of controversy. We scrutinize recent findings on a desynchronizing effect of negative density-dependent dispersal based on spatially explicit simulation models. Keeping net emigration rates equivalent, we compared density-independent and density-dependent dispersal for different types of intraspecific density regulation, ranging from under-compensation to over-compensation. In general, density-independent dispersal possessed a slightly higher synchronizing potential but this effect was very small and sensitive compared to the influence of the type of local density regulation. Notably, consistent outcomes for the comparison of conditional dispersal strategies strongly relied on the control of equivalent emigration rates. We conclude that the strength of dispersal is more important for spatial synchrony than its density dependence. Most important is the mode of intraspecific density regulation.