Landscape structure plays a key role in mediating a variety of ecological processes affecting biodiversity patterns; however, its precise effects and the mechanisms underpinning them remain unclear. ...While the effects of landscape structure have been extensively investigated both empirically and theoretically from a metapopulation perspective, the effects of spatial structure at the landscape scale remain poorly explored from a metacommunity perspective. Here, we attempt to address this gap using a spatially explicit, individual‐based metacommunity model to explore the effects of landscape compositional heterogeneity and per se spatial configuration on diversity at the landscape and patch levels via their influence on long‐term community assembly processes. Our model simulates communities composed of species of annual, asexual organisms living, reproducing, dispersing, and competing within grid‐based, fractal landscapes that vary in their magnitude of spatial environmental heterogeneity and in their degree of spatial environmental autocorrelation. Communities are additionally subject to temporal environmental fluctuations and external immigration, allowing for turnover in community composition. We found that compositional heterogeneity and spatial autocorrelation had differing effects on richness, diversity, and the landscape and patch scales. Landscape‐level diversity was driven by community dissimilarity at the patch level and increased with greater heterogeneity, while landscape richness was largely the result of the short‐term accumulation of immigrants and decreased with greater compositional heterogeneity. Both richness and diversity decreased in variance with greater compositional heterogeneity, indicating a reduction in community turnover over time. Patch‐level richness and diversity patterns appeared to be driven by overall landscape richness and local mass effects, resulting in maximum patch‐level richness and diversity at moderate levels of compositional heterogeneity and high spatial autocorrelation.
The role of landscape spatial structure in shaping biodiversity patterns remains poorly explored from a metacommunity perspective. We used an individual‐based metacommunity model to investigate the effects of compositional heterogeneity and spatial configuration on biodiversity via their effects on community assembly. We show that different degrees of compositional heterogeneity and spatial autocorrelation result in different assembly processes predominating and that richness and diversity are shaped by different processes at the landscape and patch scales, resulting in differing responses to compositional heterogeneity and spatial autocorrelation at different scales.
Mass-flowering crops may affect long-term population dynamics, but effects on pollinators have never been studied across several years. We monitored wild bees in oilseed rape fields in 16 landscapes ...in Germany in two consecutive years. Effects on bee densities of landscape oilseed rape cover in the years of monitoring and in the previous years were evaluated with landscape data from three consecutive years. We fit empirical data to a mechanistic model to provide estimates for oilseed rape attractiveness and its effect on bee productivity in comparison to the rest of the landscape, and we evaluated consequences for pollinator densities in consecutive years. Our results show that high oilseed rape cover in the previous year enhances current densities of wild bees (except for bumble bees). Moreover, we show a strong attractiveness of and dilution on (i.e., decreasing bee densities with increasing landscape oilseed rape cover) oilseed rape for bees during flowering in the current year, modifying the effect of the previous year's oilseed rape cover in the case of wild bees (excluding
Bombus
). As long as other factors such as nesting sites or natural enemies do not limit bee reproduction, our findings suggest long-term positive effects of mass-flowering crops on bee populations, at least for non-
Bombus
generalists, which possibly help to maintain crop pollination services even when crop area increases. Similar effects are conceivable for other organisms providing ecosystem services in annual crops and should be considered in future studies.
Honeybees, Apis mellifera, perform re-orientation flights to learn about the new surroundings of the hive when their hive is transported to a new location. Since the pattern of re-orientation flights ...has not yet been studied, we asked whether this form of exploratory behavior differs from the well described exploratory orientation flights performed by young honeybees before they start foraging. We also investigated whether the exploratory components of re-orientation flights differ from foraging flights and if so how. We recorded re-orientation flights using harmonic radar technology and compared the patterns and flight parameters of these flights with the first exploratory orientation flights of young honeybees and foraging flights of experienced foragers. Just as exploratory orientation flights of young honeybees, re-orientation flights can be classified into short- and long-range flights, and most short-range re-orientation flights were performed under unfavorable weather conditions. This indicates that bees adapt the flight pattern of their re-orientation and orientation flights to changing weather conditions in a similar way. Unlike exploratory orientation flights, more than one sector of the landscape was explored during a long-range re-orientation flight, and significantly longer flight durations and flight distances were observed. Thus, re-orienting bees explored a larger terrain than bees performing their first exploratory orientation flight. By displacing some bees after their first re-orientation flight, we could demonstrate that a single re-orientation flight seems to be sufficient to learn the new location of the hive. The flight patterns of re-orientation flights differed clearly from those of foraging flights. Thus, re-orientation flights represent a special exploratory behavior that is triggered by a change in the location of the hive.
The topology of ecological interaction webs holds important information for theories of coevolution, biodiversity, and ecosystem stability 1–6. However, most previous network analyses solely counted ...the number of links and ignored variation in link strength. Because of this crude resolution, results vary with scale and sampling intensity, thus hampering a comparison of network patterns at different levels 7–9. We applied a recently developed 10 quantitative and scale-independent analysis based on information theory to 51 mutualistic plant-animal networks, with interaction frequency as measure of link strength. Most networks were highly structured, deviating significantly from random associations. The degree of specialization was independent of network size. Pollination webs were significantly more specialized than seed-dispersal webs, and obligate symbiotic ant-plant mutualisms were more specialized than nectar-mediated facultative ones. Across networks, the average specialization of animal and plants was correlated, but is constrained by the ratio of plant to animal species involved. In pollination webs, rarely visited plants were on average more specialized than frequently attended ones, whereas specialization of pollinators was positively correlated with their interaction frequency. We conclude that quantitative specialization in ecological communities mirrors evolutionary trade-offs and constraints of web architecture. This approach can be easily expanded to other types of biological interactions.
Costs of dispersal Bonte, Dries; Van Dyck, Hans; Bullock, James M. ...
Biological reviews of the Cambridge Philosophical Society,
20/May , Volume:
87, Issue:
2
Journal Article
Peer reviewed
Dispersal costs can be classified into energetic, time, risk and opportunity costs and may be levied directly or deferred during departure, transfer and settlement. They may equally be incurred ...during life stages before the actual dispersal event through investments in special morphologies. Because costs will eventually determine the performance of dispersing individuals and the evolution of dispersal, we here provide an extensive review on the different cost types that occur during dispersal in a wide array of organisms, ranging from micro‐organisms to plants, invertebrates and vertebrates. In general, costs of transfer have been more widely documented in actively dispersing organisms, in contrast to a greater focus on costs during departure and settlement in plants and animals with a passive transfer phase. Costs related to the development of specific dispersal attributes appear to be much more prominent than previously accepted. Because costs induce trade‐offs, they give rise to covariation between dispersal and other life‐history traits at different scales of organismal organisation. The consequences of (i) the presence and magnitude of different costs during different phases of the dispersal process, and (ii) their internal organisation through covariation with other life‐history traits, are synthesised with respect to potential consequences for species conservation and the need for development of a new generation of spatial simulation models.
Proper timing of activities is one of the principal challenges faced by most organisms. Organisms need to account for various aspects in decision making like avoiding inordinate risks, synchronizing ...with resource availability, or finding mates. We provide analytical and simulation models to investigate the influence of life expectancy, resource competition and unpredictable environmental conditions (environmental uncertainty) on the evolutionarily stable distribution of emergence times in organisms depending on seasonally available resources. We focus on the partitioning of total phenotypic variance in emergence times into 1) genetic variance in mean emergence times between lineages and 2) environmental trait variance that determines the intra-lineage variance in the timing of emergence.
Both, life expectancy of organisms and intensity of competition severely influence the evolutionary response to environmental uncertainty. Our main findings can be summarized as follows: 1) in general diversifying bet hedging (environmental trait variance) is the adequate mechanism to reduce the risk arising from environmental uncertainty while conservative bet hedging, i.e. delaying emergence into ‘safe’ phases of the season is restricted to short lived organisms and to situations with vanishing competition. 2) Environmental trait variance increases with increasing environmental uncertainty whereas 3) significant genetic variance evolves only under severe resource competition; it is driven by selection for an ideal free distribution of emergence times. 4) The level of genetic variance evolving declines with increasing life expectancy of organisms. 5) With sufficiently short life expectancy evolutionary branching and coexistence of distinctly different emergence strategies occurs; the number of co-occurring strategies is determined by the level of environmental uncertainty.
Our model provides cues for understanding how different ecological factors contribute and interact to shape the evolution of emergence strategies.
From random walks to informed movement Fronhofer, Emanuel A.; Hovestadt, Thomas; Poethke, Hans-Joachim
Oikos,
June 2013, Volume:
122, Issue:
6
Journal Article
Peer reviewed
Open access
The analysis of animal movement is a large and continuously growing field of research. Detailed knowledge about movement strategies is of crucial importance for understanding eco-evolutionary ...dynamics at all scales – from individuals to (meta-)populations. This and the availability of detailed movement and dispersal data motivated Nathan and colleagues to published their much appreciated call to base movement ecology on a more thorough mechanistic basis. So far, most movement models are based on random walks. However, even if a random walk might describe real movement patterns acceptably well, there is no reason to assume that animals move randomly. Therefore, mechanistic models of foraging strategies should be based on information use and memory in order to increase our understanding of the processes that lead to animal movement decisions. We present a mechanistic movement model of an animal with a limited perceptual range and basic information storage capacities. This 'spatially informed forager' constructs an internal map of its environment by using perception, memory and learned or evolutionarily acquired assumptions about landscape attributes. We analyse resulting movement patterns and search efficiencies and compare them to area restricted search strategies (ARS) and biased correlated random walks (BCRW) of omniscient individuals. We show that, in spite of their limited perceptual range, spatially informed individuals boost their foraging success and may perform much better than the best ARS. The construction of an internal map and the use of spatial information results in the emergence of a highly correlated walk between patches and a rather systematic search within resource clusters. Furthermore, the resulting movement patterns may include foray search behaviour. Our work highlights the strength of mechanistic modelling approaches and sets the stage for the development of more sophisticated models of memory use for movement decisions and dispersal.
Many organisms show polymorphism in dispersal distance strategies. This variation is particularly ecological relevant if it encompasses a functional separation of short- (SDD) and long-distance ...dispersal (LDD). It remains, however, an open question whether both parts of the dispersal kernel are similarly affected by landscape related selection pressures. We implemented an individual-based model to analyze the evolution of dispersal traits in fractal landscapes that vary in the proportion of habitat and its spatial configuration. Individuals are parthenogenetic with dispersal distance determined by two alleles on each individual's genome: one allele coding for the probability of global dispersal and one allele coding for the variance σ of a Gaussian local dispersal with mean value zero. Simulations show that mean distances of local dispersal and the probability of global dispersal, increase with increasing habitat availability, but that changes in the habitat's spatial autocorrelation impose opposing selective pressure: local dispersal distances decrease and global dispersal probabilities increase with decreasing spatial autocorrelation of the available habitat. Local adaptation of local dispersal distance emerges in landscapes with less than 70% of clumped habitat. These results demonstrate that long and short distance dispersal evolve separately according to different properties of the landscape. The landscape structure may consequently largely affect the evolution of dispersal distance strategies and the level of dispersal polymorphism.
Metapopulation models typically assume that suitable habitats occupied by local populations and unsuitable matrix separating them form a ‘black-and-white’ landscape mosaic, in which dispersal is ...primarily determined by the spatial configuration of habitat patches. In reality, however, the matrix composition is also likely to influence dispersal. Using intensive mark-recapture surveys we investigated inter-patch movements in Maculinea (Phengaris) nausithous and M. teleius occurring sympatrically in six metapopulations. Three of these metapopulations had the matrix dominated by forest, an inhospitable environment for grassland butterflies, whereas in the remaining three the matrix was mostly composed of open environments. Dispersal parameters derived with the Virtual Migration model revealed significant differences between both groups of metapopulations. Both species had a lower propensity to emigrate from their natal habitat patches, and they suffered substantially higher dispersal mortality in the metapopulations with forest matrix. On the other hand, mean dispersal distances were roughly an order of magnitude longer in forest matrix as compared with open landscapes (ca. 500–1,500 vs. 100–200 m). Our results suggest that inhospitable forest matrix induces strong selection against dispersal, leading to a reduced emigration rate. At the same time, the selection may promote emigrants with good dispersal abilities, which are able to perform long-distance movements. Thus, while it is generally believed that a matrix structurally similar to the habitat of a species should improve the functional connectivity of habitat patches, our findings imply that this may not necessarily be the case.
Bioclimate envelope models (BEMs) have often been criticized as being too simplistic due to e.g. not incorporating effects of biotic interactions or evolutionary adaptation. However, BEMs are widely ...applied and have proven to be often useful. Here we investigate, under which conditions evolution of dispersal, local adaptation or interspecific competition may be of minor importance for forecasting future range shifts. Therefore we use individual-based simulations of metapopulations under climate change living in spatial temperature gradients. Scenarios incorporate single-species systems or systems with competing species, respectively. Dispersal rate is evolving and adaptation to local conditions may also evolve in some scenarios. Results show that in single-species scenarios excluding evolutionary adaptation, species either follow optimal habitat conditions or go extinct if habitat connectivity is too low.These simulations are in close accordance to predictions from BEMs. Including evolutionary adaptation qualitatively changes these results. In the absence of competing species the species either completely invades the world or goes extinct. With competitors, results strongly depend on habitat fragmentation. For highly connected habitats the range border may shift as predicted by BEMs, for intermediate connectivity it will lag behind, while species will go extinct if fragmentation is too high. Our results indicate that (simple) BEMs may work well if habitats are well connected and species will not encounter many difficulties in dispersing to new sites. Selection in this case may promote evolution of even higher dispersal activities. We thus show that the presence of biotic interactions may be ignored for predictions of range shifts when high dispersal can be expected.
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