Temporal genetic patterns of diversity and structure evidence chaotic genetic patchiness in a spiny lobster

Population structure of many marine organisms is spatially patchy and varies within and between years, a phenomenon defined as chaotic genetic patchiness. This results from the combination of planktonic larval dispersal and environmental stochasticity. Additionally, in species with bi‐partite life, postsettlement selection can magnify these genetic differences. The high fecundity (up to 500,000 eggs annually) and protracted larval duration (12–24 months) and dispersal of the southern rock lobster, Jasus edwardsii, make it a good test species for chaotic genetic patchiness and selection during early benthic life. Here, we used double digest restriction site‐associated DNA sequencing (ddRADseq) to investigate chaotic genetic patchiness and postsettlement selection in this species. We assessed differences in genetic structure and diversity of recently settled pueruli across four settlement years and between two sites in southeast Australia separated by approximately 1,000 km. Postsettlement selection was investigated by identifying loci under putative positive selection between recently settled pueruli and postpueruli and quantifying differences in the magnitude and strength of the selection at each year and site. Genetic differences within and among sites through time in neutral SNP markers indicated chaotic genetic patchiness. Recently settled puerulus at the southernmost site exhibited lower genetic diversity during years of low puerulus catches, further supporting this hypothesis. Finally, analyses of outlier SNPs detected fluctuations in the magnitude and strength of the markers putatively under positive selection over space and time. One locus under putative positive selection was consistent at both locations during the same years, suggesting the existence of weak postsettlement selection.     

GENETIC DRIFT AND COLLECTIVE DISPERSAL CAN RESULT IN CHAOTIC GENETIC PATCHINESS

Chaotic genetic patchiness denotes unexpected patterns of genetic differentiation that are observed at a fine scale and are not stable in time. These patterns have been described in marine species with free‐living larvae, but are unexpected because they occur at a scale below the dispersal range of pelagic larvae. At the scale where most larvae are immigrants, theory predicts spatially homogeneous, temporally stable genetic variation. Empirical studies have suggested that genetic drift interacts with complex dispersal patterns to create chaotic genetic patchiness. Here we use a coancestry model and individual‐based simulations to test this idea. We found that chaotic genetic patterns (qualified by global F_ST and spatio‐temporal variation in F_ST's between pairs of samples) arise from the combined effects of (1) genetic drift created by the small local effective population sizes of the sessile phase and variance in contribution among breeding groups and (2) collective dispersal of related individuals in the larval phase. Simulations show that patchiness levels qualitatively comparable to empirical results can be produced by a combination of strong variance in reproductive success and mild collective dispersal. These results call for empirical studies of the effective number of breeders producing larval cohorts, and population genetics at the larval stage.     

Deconstructing environmental predictability: seasonality,environmental colour and the biogeography of marine life histories

Environmental predictability is predicted to shape the evolution of life histories. Two key types of environmental predictability, seasonality and environmental colour, may influence life‐history evolution independently but formal considerations of both and how they relate to life history are exceedingly rare. Here, in a global biogeographical analysis of over 800 marine invertebrates, we explore the relationships between both forms of environmental predictability and three fundamental life‐history traits: location of larval development (aplanktonic vs. planktonic), larval developmental mode (feeding vs. non‐feeding) and offspring size. We found that both dispersal potential and offspring size related to environmental predictability, but the relationships depended on both the environmental factor as well as the type of predictability. Environments that were more seasonal in food availability had a higher prevalence of species with a planktonic larval stage. Future studies should consider both types of environmental predictability as each can strongly affect life‐history evolution.     

Closing the larval loop: linking larval ecology to the population dynamics of marine benthic invertebrates

The majority of marine benthic invertebrates exhibit a complex life cycle that includes separate planktonic larval, and bottom-dwelling juvenile and adult phases. To understand and predict changes in the spatial and temporal distributions, abundances, population growth rate, and population structure of a species with such a complex life cycle, it is necessary to understand the relative importance of the physical, chemical and biological properties and processes that affect individuals within both the planktonic and benthic phases. To accomplish this goal, it is necessary to study both phases within a common, quantitative framework defined in terms of some common currency. This can be done efficiently through construction and evaluation of a population dynamics model that describes the complete life cycle.

Two forms that such a model might assume are reviewed: a stage-based, population matrix model, and a model that specifies discrete stages of the population, on the bottom and in the water column, in terms of simultaneous differential equations that may be solved in both space and time. Terms to be incorporated in each type of model can be formulated to describe the critical properties and processes that can affect populations within each stage of the life cycle. For both types of model it is shown how this might be accomplished using an idealized balanomorph barnacle as an example species. The critical properties and processes that affect the planktonic and benthic phases are reviewed. For larvae, these include benthic adult fecundity and fertilization success, growth and larval stage duration, mortality, larval behavior, dispersal by currents and turbulence, and larval settlement. It is possible to predict or estimate empirically all of the key terms that should be built into the larval and benthic components of the model. Thus, the challenge of formulating and evaluating a full life cycle model is achievable. Development and evaluation of such a model will be challenging because of the diverse processes which must be considered, and because of the disparities in the spatial and temporal scales appropriate to the benthic and planktonic larval phases. In evaluating model predictions it is critical that sampling schemes be matched to the spatial and temporal scales of model resolution.     

Modeling bird species distribution change in fire prone Mediterranean landscapes: incorporating species dispersal and landscape dynamics

Species distribution models (SDMs) have traditionally been founded on the assumption that species distributions are in equilibrium with environmental conditions and that these species–environment relationships can be used to estimate species responses to environmental changes. Insight into the validity of this assumption can be obtained from comparing the performance of correlative species distribution models with more complex hybrid approaches, i.e. correlative and process‐based models that explicitly include ecological processes, thereby accounting for mismatches between habitat suitability and species occupancy patterns. Here we compared the ability of correlative SDMs and hybrid models, which can accommodate non‐equilibrium situations arising from dispersal constraints, to reproduce the distribution dynamics of the ortolan bunting Emberiza hortulana in highly dynamic, early successional, fire driven Mediterranean landscapes. Whereas, habitat availability was derived from a correlative statistical SDM, occupancy was modeled using a hybrid approach combining a grid‐based, spatially‐explicit population model that explicitly included bird dispersal with the correlative model. We compared species occupancy patterns under the equilibrium assumption and different scenarios of species dispersal capabilities. To evaluate the predictive capability of the different models, we used independent species data collected in areas affected to different degree by fires. In accordance with the view that disturbance leads to a disparity between the suitable habitat and the occupancy patterns of the ortolan bunting, our results indicated that hybrid modeling approaches were superior to correlative models in predicting species spatial dynamics. Furthermore, hybrid models that incorporated short dispersal distances were more likely to reproduce the observed changes in ortolan bunting distribution patterns, suggesting that dispersal plays a key role in limiting the colonization of recently burnt areas. We conclude that SDMs used in a dynamic context can be significantly improved by using combined hybrid modeling approaches that explicitly account for interactions between key ecological constraints such as dispersal and habitat suitability that drive species response to environmental changes.     

The spatial scale of population fluctuations and quasi-extinction risk

Using a spatially homogeneous population model with migration (random individual dispersal) and spatially autocorrelated environmental noise, we show how migration and local density regulation affect the spatial scale of fluctuations in the log of population sizes as well as the 1-yr differences in these. The difference between the squares of these two spatial scales of population fluctuations does not depend on the spatial scale of the noise but only on migration rate and strength of local density regulation. We also show how migration, local density regulation, and spatially correlated environmental noise affect the realized population process at a specific location. As the migration increases, the realized local density regulation and the expected population size increase, while the realized environmental noise decreases. This approach also enables us to analyze the dynamics of the total population size within quadrats of different sizes. The risk of local quasi extinction is strongly reduced by increasing quadrat size or migration rate, while an increase in environmental stochasticity or spatial correlation in the environmental noise increases the risk of quasi extinction.     

Polymorphism in developmental mode and its effect on population genetic structure of a spionid polychaete, Pygospio elegans

Population genetic structure of sedentary marine species is expected to be shaped mainly by the dispersal ability of their larvae. Long-lived planktonic larvae can connect populations through migration and gene flow, whereas species with nondispersive benthic or direct-developing larvae are expected to have genetically differentiated populations. Poecilogonous species producing different larval types are ideal when studying the effect of developmental mode on population genetic structure and connectivity. In the spionid polychaete Pygospio elegans, different larval types have been observed between, and sometimes also within, populations. We used microsatellite markers to study population structure of European P. elegans from the Baltic Sea (BS) and North Sea (NS). We found that populations with planktonic larvae had higher genetic diversity than did populations with benthic larvae. However, this pattern may not be related to developmental mode, since in P. elegans, developmental mode may be associated with geography. Benthic larvae were more commonly seen in the brackish BS and planktonic larvae were predominant in the NS, although both larval types also are found from both areas. Significant isolation-by-distance (IBD) was found overall and within regions. Most of the pair-wise F(ST) comparisons among populations were significant, although some geographically close populations with planktonic larvae were found to be genetically similar. However, these results, together with the pattern of IBD, autocorrelation within populations, as well as high estimated local recruitment, suggest that dispersal is limited in populations with planktonic larvae as well as in those with benthic larvae. The decrease in salinity between the NS and BS causes a barrier to gene flow in many marine species. In P. elegans, low, but significant, differentiation was detected between the NS and BS (3.34% in AMOVA), but no clear transition zone was observed, indicating that larvae are not hampered by the change in salinity.     

Effects of habitat size and isolation on species immigration–extinction dynamics and community nestedness in a desert river system

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Viability analyses with habitat-based metapopulation models

Population viability analysis (PVA) models incorporate spatial dynamics in different ways. At one extreme are the occupancy models that are based on the number of occupied populations. The simplest occupancy models ignore the location of populations. At the other extreme are individual-based models, which describe the spatial structure with the location of each individual in the population, or the location of territories or home ranges. In between these are spatially structured metapopulation models that describe the dynamics of each population with structured demographic models and incorporate spatial dynamics by modeling dispersal and temporal correlation among populations. Both dispersal and correlation between each pair of populations depend on the location of the populations, making these models spatially structured. In this article, I describe a method that expands spatially structured metapopulation models by incorporating information about habitat relationships of the species and the characteristics of the landscape in which the metapopulation exists. This method uses a habitat suitability map to determine the spatial structure of the metapopulation, including the number, size, and location of habitat patches in which subpopulations of the metapopulation live. The habitat suitability map can be calculated in a number of different ways, including statistical analyses (such as logistic regression) that find the relationship between the occurrence (or, density) of the species and independent variables which describe its habitat requirements. The habitat suitability map is then used to calculate the spatial structure of the metapopulation, based on species-specific characteristics such as the home range size, dispersal distance, and minimum habitat suitability for reproduction. Received: April 1, 1999 / Accepted: October 29, 1999     

Coherence,conservation and patch‐occupancy analysis

Spatial coherence (synchrony) among subpopulations poses a danger to the metacommunity, as it increases the risk of regional extinction. When this effect is significant, the use of inference techniques based on the stochastic patch occupancy model (SPOM) may be inadequate, since SPOMs assume that each habitat patch is either occupied or empty, thereby neglecting the intra‐patch dynamics. Here we suggest a general classification of the dynamics that allows the identification, in a model‐independent manner, of the regimes where coherence effects are strong. We also present a new technique, based on patch occupancy (presence/absence) data, for identifying the role of spatial coherence in the stabilization of a metapopulation. If the chance of a local extinction grows with the connectivity, this implies that spatial synchronization is too strong and that regional‐scale extinction becomes possible. When this scenario occurs, a decrease in the movement of individuals (habitat fragmentation, reduced dispersal rates) has a positive effect on the sustainability of the spatially distributed population. The results of individual based simulations of a spatially structured population are analyzed with SPOM and the regime where the two‐state approximation fails is identified.     

The effect of ant association on the population genetics of the Australian butterfly Jalmenus evagoras (Lepidoptera: Lycaenidae)

Populations of the myrmecophilous lycaenid Jalmenus evagoras Donovan were assessed for genetic structure at three hierarchical spatial scales: sites, geographically-defined subpopulations, and subpopulations defined by species of mutualistic ant-associate. Estimates of Wright's FST generated from multilocus electrophoretic data revealed low, though significant, amounts of genetic structure. Most structure was observed at the level of geographic subpopulations, suggesting that adult butterflies do not exhibit preferential mating and oviposition along the lines of ant associate. The genetic structure data, together with estimates of Nei's genetic distance (D) for pairwise site and subpopulation comparisons, suggest that J. evagoras populations are spatially and temporally dynamic. These patterns are considered in the context of extinction and recolonization models. The extreme patchiness of J. evagoras populations stems from the stringent requirements of both host plant and host ant, contributing to an extinction/ recolonization process. We discuss the key parameters influencing genetic cohesion versus differentiation under an extinction/recolonization regime, including mode of butterfly dispersal, site turnover rate, and the effects of host dispersal and phenology. This system provides a model of population-level consequences of certain mutualistic interactions as well as of a class of patterns arising from an extinction/recolonization process.     

Dispersal promotes compensatory dynamics and stability in forced metacommunities

Understanding the factors that govern the stability of populations and communities has gained increasing importance as habitat fragmentation and environmental perturbations continue to escalate due to human activities. Dispersal is commonly viewed as essential to the maintenance of diversity in spatially subdivided communities, but few experiments have explored how dispersal interacts with the spatiotemporal components of environmental perturbations to determine community-level stability. We examined these processes using an experimental planktonic system composed of three competing species of zooplankton. We subjected zooplankton metacommunities to varying levels of dispersal and pH perturbations that varied in their degree of spatial synchrony. We show that dispersal can reverse the destabilizing effects of environmental forcing when perturbations are spatially asynchronous. Asynchrony in pH perturbations generated spatially and temporally varying species refugia that promoted source-sink dynamics and allowed prolonged persistence of zooplankton species that were otherwise extirpated in synchronously varying metacommunities. This, in turn, increased local species diversity, promoted compensatory population dynamics, and enhanced local community-level stability. Our results indicate that patterns of spatial covariation in environmental variability are critical to predicting the effects of dispersal on the dynamics and persistence of communities.     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.     

Patch occupancy of North American mammals: is patchiness in the eye of the beholder?

Aim Intraspecific variation in patch occupancy often is related to physical features of a landscape, such as the amount and distribution of habitat. However, communities occupying patchy environments typically exhibit non‐random distributions in which local assemblages of species‐poor patches are nested subsets of assemblages occupying more species‐rich patches. Nestedness of local communities implies interspecific differences in sensitivity to patchiness. Several hypotheses have been proposed to explain interspecific variation in responses to patchiness within a community, including differences in (1) colonization ability, (2) extinction proneness, (3) tolerance to disturbance, (4) sociality and (5) level of adaptation to prevailing environmental conditions. We used data on North American mammals to compare the performance of these ‘ecological’ hypotheses and the ‘physical landscape’ hypothesis. We then compared the best of these models against models that scaled landscape structure to ecologically relevant attributes of individual species. Location North America. Methods We analysed data on prevalence (i.e. proportion of patches occupied in a network of patches) and occupancy for 137 species of non‐volant mammals and twenty networks consisting of four to seventy‐five patches. Insular and terrestrial networks exhibited significantly different mean levels of prevalence and occupancy and thus were analysed separately. Indicator variables at ordinal and family levels were included in models to correct for effects caused by phylogeny. Akaike's information criterion was used in conjunction with ordinary least squares and logistic regression to compare hypotheses. Results A patch network's physical structure, indexed using patch area and isolation, received the greatest support among models predicting the prevalence of species on insular networks. Niche breadth (diet and habitat) received the greatest support for predicting prevalence of species occupying terrestrial networks. For both insular and terrestrial systems, physical features (patch area and isolation) received greater support than any of the ecological hypotheses for predicting species occupancy of individual patches. For terrestrial systems, scaling patch area by its suitability to a focal species and by individual area requirements of the species, and scaling patch isolation by species‐specific dispersal ability and niche breadth, resulted in models of patch occupancy that were superior to models relying solely on physical landscape features. For all selected models, unexplained levels of variation were high. Main conclusions Stochasticity dominated the systems we studied, indicating that random events are probably quite important in shaping local communities. With respect to deterministic factors, our results suggest that forces affecting species prevalence and occupancy may differ between insular and terrestrial systems. Physical features of insular systems appeared to swamp ecological differences among species in determining prevalence and occupancy, whereas species with broad niches were disproportionately represented in terrestrial networks. We hypothesize that differential extinction over long time periods in highly variable networks has driven nestedness of mammalian communities on islands, whereas differential colonization over shorter time‐scales in more homogeneous networks probably governed the local structure of terrestrial communities. Our results also demonstrate that integration of a species' ecological traits with physical features of a patch network is superior to reliance on either factor separately when attempting to predict the species' probability of patch occupancy in terrestrial systems.     

Development and characterization of 12 microsatellite markers from the deep-sea hydrothermal vent siboglinid Riftia pachyptila

Ecological processes at deep‐sea hydrothermal vents on fast‐spreading mid‐ocean ridges are punctuated by frequent physical disturbance, often accompanied by a high occurrence of population turnover. To persist through local extinction events, sessile invertebrate species living in these geologically and chemically dynamic habitats depend on larval dispersal. We characterized 12 polymorphic microsatellite loci from one such species, the siboglinid tubeworm Riftia pachyptila. All loci conformed to Hardy–Weinberg expectations without linkage (mean H_E = 0.9405, mean N_A = 20.25). These microsatellites are being employed in the investigation of spatial and temporal population genetic structure in the eastern Pacific Ocean.     

Spatial and genetic investigation of aggregation in Ischnochiton (Polyplacophora; Neoloricata; Ischnochitonina; Ischnochitonidae; Ischnochitoninae) species with different larval development

Many species are aggregated at some spatial scale but for some species, due to habitat or behaviour, aggregation can be difficult to assess quantitatively. Here, aggregation of chiton species (Polyplacophora; Neoloricata; Ischnochitonina; Ischnochitonidae; Ischnochitoninae; Ischnochiton) living under boulders in intertidal boulder fields was investigated at several relatively small spatial scales. Closely related species were found to be aggregated at the level of individual boulders, but evidence for grouping at the larger scale of patches of boulders varied. When organisms are mobile, dispersal can have an important influence on spatial patterns. Some organisms, such as marine invertebrates, have a highly dispersive larval phase that can influence spatial patterns of adults, particularly where the adult is sessile or relatively sedentary. Aggregation was compared in two species to test whether different modes of larval development influence spatial pattern. There was some evidence that species with a planktonic larva were even more aggregated than expected, in contrast to predictions based on this mode of development. Both types of larval development (planktonic and non‐planktonic) produce larvae with short development times in these species, so one possible explanation for the grouping habit of these chitons is that they do not disperse, at all, from their natal boulder. The complexity of the boulder field habitat and the cryptic behaviour of these chitons may also contribute to a lack of dispersal. A simple application of a genetic method indicated, however, that philopatry at this scale is unlikely.     

Local and Regional Determinants of Colonisation-Extinction Dynamics of a Riparian Mainland-Island Root Vole Metapopulation

The role of local habitat geometry (habitat area and isolation) in predicting species distribution has become an increasingly more important issue, because habitat loss and fragmentation cause species range contraction and extinction. However, it has also become clear that other factors, in particular regional factors (environmental stochasticity and regional population dynamics), should be taken into account when predicting colonisation and extinction. In a live trapping study of a mainland-island metapopulation of the root vole (Microtus oeconomus) we found extensive occupancy dynamics across 15 riparian islands, but yet an overall balance between colonisation and extinction over 4 years. The 54 live trapping surveys conducted over 13 seasons revealed imperfect detection and proxies of population density had to be included in robust design, multi-season occupancy models to achieve unbiased rate estimates. Island colonisation probability was parsimoniously predicted by the multi-annual density fluctuations of the regional mainland population and local island habitat quality, while extinction probability was predicted by island population density and the level of the recent flooding events (the latter being the main regionalized disturbance regime in the study system). Island size and isolation had no additional predictive power and thus such local geometric habitat characteristics may be overrated as predictors of vole habitat occupancy relative to measures of local habitat quality. Our results suggest also that dynamic features of the larger region and/or the metapopulation as a whole, owing to spatially correlated environmental stochasticity and/or biotic interactions, may rule the colonisation – extinction dynamics of boreal vole metapopulations. Due to high capacities for dispersal and habitat tracking voles originating from large source populations can rapidly colonise remote and small high quality habitat patches and re-establish populations that have gone extinct due to demographic (small population size) and environmental stochasticity (e.g. extreme climate events).     

USING ISOLATION BY DISTANCE AND EFFECTIVE DENSITY TO ESTIMATE DISPERSAL SCALES IN ANEMONEFISH

Robust estimates of dispersal are critical for understanding population dynamics and local adaptation, as well as for successful spatial management. Genetic isolation by distance patterns hold clues to dispersal, but understanding these patterns quantitatively has been complicated by uncertainty in effective density. In this study, we genotyped populations of a coral reef fish (Amphiprion clarkii) at 13 microsatellite loci to uncover fine‐scale isolation by distance patterns in two replicate transects. Temporal changes in allele frequencies between generations suggested that effective densities in these populations are 4–21 adults/km. A separate estimate from census densities suggested that effective densities may be as high as 82–178 adults/km. Applying these effective densities with isolation by distance theory suggested that larval dispersal kernels in A. clarkii had a spread near 11 km (4–27 km). These kernels predicted low fractions of self‐recruitment in continuous habitats, but the same kernels were consistent with previously reported, high self‐recruitment fractions (40–60%) when realistic levels of habitat patchiness were considered. Our results suggested that ecologically relevant larval dispersal can be estimated with widely available genetic methods when effective density is measured carefully through cohort sampling and ecological censuses, and that self‐recruitment studies should be interpreted in light of habitat patchiness.     

Dispersal and diversity – unifying scale‐dependent relationships within the neutral theory

The response of species diversity to dispersal capability is inherently scale‐dependent: increasing dispersal capability is expected to increase diversity at the local scale, while decreasing diversity at the metacommunity scale. However, these expectations are based on model formulations that neglect dispersal limitation and species segregation at the local scale. We developed a unifying framework of dispersal–diversity relationships and tested the generality of these expectations. For this purpose we used a spatially‐explicit neutral model with various combinations of survey area (local scale) and landscape size (metacommunity scale). Simulations were conducted using landscapes of finite and of conceptually infinite size. We analyzed the scale‐dependence of dispersal‐diversity relationships for exponentially‐bounded versus fat‐tailed dispersal kernels, several levels of speciation rate and contrasting assumptions on recruitment at short dispersal distances. We found that the ratio of survey area to landscape size is a major determinant of dispersal–diversity relationships. With increasing survey‐to‐landscape area ratio the dispersal–diversity relationship switches from monotonically increasing through a U‐shaped pattern (with a local minimum) to a monotonically decreasing pattern. Therefore, we provide a continuous set of dispersal–diversity relationships, which contains the response shapes reported previously as extreme cases. We suggest the mean dispersal distance with the minimum of species diversity (minimizing dispersal distance) for a certain scenario as a key characteristic of dispersal–diversity relationships. We show that not only increasing mean dispersal distances, but also increasing variances of dispersal can enhance diversity at the local scale, given a diverse species pool at the metacommunity scale. In conclusion, the response of diversity to variations of dispersal capability at spatial scales of interest, e.g. conservation areas, can differ more widely than expected previously. Therefore, land use and conservation activities, which manipulate dispersal capability, need to consider the landscape context and potential species pools carefully.     

Are spatially correlated or uncorrelated disturbance regimes better for the survival of species?

The survival of species in dynamic landscapes (characterised by patch destruction and subsequent regeneration) depends on both the species' attributes and the disturbance pattern. Using a spatially explicit model we explored how the mean time to extinction of a metapopulation depends on the spatial correlation of patch destruction in relation to the population growth and dispersal abilities of species. Two contrasting answers are possible. On the one hand, increasing spatial correlation of patch destruction increases the spatial correlation of population growth and this is known to decrease metapopulation persistence. On the other hand, spatially correlated patch destruction and regeneration can lead to clustered habitat patches and this is known to increase metapopulation persistence. Therefore, we hypothesised that some species are better off under spatially correlated and alternatively uncorrelated disturbance regimes. However, contrary to this hypothesis, in all kinds of cases spatial correlation reduced metapopulation persistence. We found this to be due to the fact that the spatial correlation of patch destruction causes increasing temporal fluctuations in the regional carrying capacity of the metapopulation and is hence generally disadvantageous for long-term persistence. The main consequence for conservation biology is that reducing spatial correlation in disturbances is likely to be a reliable strategy in a dynamic landscape that will benefit practically all species with a low risk of adverse side effects .