Landscape fragmentation overturns classical metapopulation thinking.

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants." This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

Accelerating joint species distribution modelling with Hmsc-HPC by GPU porting.

Joint species distribution modelling (JSDM) is a widely used statistical method that analyzes combined patterns of all species in a community, linking empirical data to ecological theory and enhancing community-wide prediction tasks. However, fitting JSDMs to large datasets is often computationally demanding and time-consuming. Recent studies have introduced new statistical and machine learning techniques to provide more scalable fitting algorithms, but extending these to complex JSDM structures that account for spatial dependencies or multi-level sampling designs remains challenging. In this study, we aim to enhance JSDM scalability by leveraging high-performance computing (HPC) resources for an existing fitting method. Our work focuses on the Hmsc R-package, a widely used JSDM framework that supports the integration of various dataset types into a single comprehensive model. We developed a GPU-compatible implementation of its model-fitting algorithm using Python and the TensorFlow library. Despite these changes, our enhanced framework retains the original user interface of the Hmsc R-package. We evaluated the performance of the proposed implementation across various model configurations and dataset sizes. Our results show a significant increase in model fitting speed for most models compared to the baseline Hmsc R-package. For the largest datasets, we achieved speed-ups of over 1000 times, demonstrating the substantial potential of GPU porting for previously CPU-bound JSDM software. This advancement opens promising opportunities for better utilizing the rapidly accumulating new biodiversity data resources for inference and prediction.

Resolving biology's dark matter: species richness, spatiotemporal distribution, and community composition of a dark taxon.

BACKGROUND: Zoology's dark matter comprises hyperdiverse, poorly known taxa that are numerically dominant but largely unstudied, even in temperate regions where charismatic taxa are well understood. Dark taxa are everywhere, but high diversity, abundance, and small size have historically stymied their study. We demonstrate how entomological dark matter can be elucidated using high-throughput DNA barcoding ("megabarcoding"). We reveal the high abundance and diversity of scuttle flies (Diptera: Phoridae) in Sweden using 31,800 specimens from 37 sites across four seasonal periods. We investigate the number of scuttle fly species in Sweden and the environmental factors driving community changes across time and space. RESULTS: Swedish scuttle fly diversity is much higher than previously known, with 549 putative specie) detected, compared to 374 previously recorded species. Hierarchical Modelling of Species Communities reveals that scuttle fly communities are highly structured by latitude and strongly driven by climatic factors. Large dissimilarities between sites and seasons are driven by turnover rather than nestedness. Climate change is predicted to significantly affect the 47% of species that show significant responses to mean annual temperature. Results were robust regardless of whether haplotype diversity or species-proxies were used as response variables. Additionally, species-level models of common taxa adequately predict overall species richness. CONCLUSIONS: Understanding the bulk of the diversity around us is imperative during an era of biodiversity change. We show that dark insect taxa can be efficiently characterised and surveyed with megabarcoding. Undersampling of rare taxa and choice of operational taxonomic units do not alter the main ecological inferences, making it an opportune time to tackle zoology's dark matter.

Experimental evidence that root-associated fungi improve plant growth at high altitude.

Unravelling how species communities change along environmental gradients requires a dual understanding: the direct responses of the species to their abiotic surroundings and the indirect variation of these responses through biotic interactions. Here, we focus on the interactive relationships between plants and their symbiotic root-associated fungi (RAF) along stressful abiotic gradients. We investigate whether variations in RAF community composition along altitudinal gradients influence plant growth at high altitudes, where both plants and fungi face harsher abiotic conditions. We established a translocation experiment between pairs of Bistorta vivipara populations across altitudinal gradients. To separate the impact of shifting fungal communities from the overall influence of changing abiotic conditions, we used a root barrier to prevent new colonization by RAF following translocation. To characterize the RAF communities, we applied DNA barcoding to the root samples. Through the utilization of joint species distribution modelling, we assessed the relationship between changes in plant functional traits resulting from experimental treatments and the corresponding changes in the RAF communities. Our findings indicate that RAF communities influence plant responses to stressful abiotic conditions. Plants translocated from low to high altitudes grew more when they were able to associate with the resident high-altitude RAF compared to those plants that were not allowed to associate with the resident RAF. We conclude that interactions with RAF impact how plants respond to stressful abiotic conditions. Our results provide experimental support that interactions with RAF improve plant stress tolerance to altitudinal stressors such as colder temperatures and less nutrient availability.

Macrosystem community change in lake phytoplankton and its implications for diversity and function.

Aim: We use lake phytoplankton community data to quantify the spatio-temporal and scale-dependent impacts of eutrophication, land-use and climate change on species niches and community assembly processes while accounting for species traits and phylogenetic constraints. Location: Finland. Time period: 1977-2017. Major taxa: Phytoplankton. Methods: We use hierarchical modelling of species communities (HMSC) to model metacommunity trajectories at 853 lakes over four decades of environmental change, including a hierarchical spatial structure to account for scale-dependent processes. Using a "region of common profile" approach, we evaluate compositional changes of species communities and trait profiles and investigate their temporal development. Results: We demonstrate the emergence of novel and widespread community composition clusters in previously more compositionally homogeneous communities, with cluster-specific community trait profiles, indicating functional differences. A strong phylogenetic signal of species responses to the environment implies similar responses among closely related taxa. Community cluster-specific species prevalence indicates lower taxonomic dispersion within the current dominant clusters compared with the historically dominant cluster and an overall higher prevalence of smaller species sizes within communities. Our findings denote profound spatio-temporal structuring of species co-occurrence patterns and highlight functional differences of lake phytoplankton communities. Main conclusions: Diverging community trajectories have led to a nationwide reshuffling of lake phytoplankton communities. At regional and national scales, lakes are not single entities but metacommunity hubs in an interconnected waterscape. The assembly mechanisms of phytoplankton communities are strongly structured by spatio-temporal dynamics, which have led to novel community types, but only a minor part of this reshuffling could be linked to temporal environmental change.

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems.

Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al. Nat Commun 10:4716, 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs' applicability in cancer research.

Scavenging in the realm of senses: smell and vision drive recruitment at carcasses in Neotropical ecosystems.

Social information, acquired through the observation of other individuals, is especially relevant among species belonging to the same guild. The unpredictable and ephemeral nature of carrion implies that social mechanisms may be selected among scavenger species to facilitate carcass location and consumption. Here, we apply a survival-modelling strategy to data obtained through the placement and monitoring of carcasses in the field to analyse possible information transmission cascades within a Neotropical scavenger community. Our study highlights how the use of different senses (smell and sight) within this guild facilitates carcass location through the transmission of social information between species with different carrion foraging efficiencies. Vultures with a highly developed sense of smell play a key role in this process, as they are the first to arrive at the carcasses and their presence seems to serve as a visual cue for other species to locate the resource. Our study supports the local enhancement hypothesis within scavengers, whereby individuals locate carcasses by following foraging heterospecifics, also suggesting the importance of the sense of smell in the maintenance of the community structure.

Measuring, comparing and interpreting phenotypic selection on floral scent.

Natural selection on floral scent composition is a key element of the hypothesis that pollinators and other floral visitors drive scent evolution. The measure of such selection is complicated by the high-dimensional nature of floral scent data and uncertainty about the cognitive processes involved in scent-mediated communication. We use dimension reduction through reduced-rank regression to jointly estimate a scent composite trait under selection and the strength of selection acting on this trait. To assess and compare variation in selection on scent across species, time and space, we reanalyse 22 datasets on six species from four previous studies. The results agreed qualitatively with previous analyses in terms of identifying populations and scent compounds subject to stronger selection but also allowed us to evaluate and compare the strength of selection on scent across studies. Doing so revealed that selection on floral scent was highly variable, and overall about as common and as strong as selection on other phenotypic traits involved in pollinator attraction or pollen transfer. These results are consistent with an important role of floral scent in pollinator attraction. Our approach should be useful for further studies of plant-animal communication and for studies of selection on other high-dimensional phenotypes. In particular, our approach will be useful for studies of pollinator-mediated selection on complex scent blends comprising many volatiles, and when no prior information on the physiological responses of pollinators to scent compounds is available.

Common gardens in teosintes reveal the establishment of a syndrome of adaptation to altitude.

In plants, local adaptation across species range is frequent. Yet, much has to be discovered on its environmental drivers, the underlying functional traits and their molecular determinants. Genome scans are popular to uncover outlier loci potentially involved in the genetic architecture of local adaptation, however links between outliers and phenotypic variation are rarely addressed. Here we focused on adaptation of teosinte populations along two elevation gradients in Mexico that display continuous environmental changes at a short geographical scale. We used two common gardens, and phenotyped 18 traits in 1664 plants from 11 populations of annual teosintes. In parallel, we genotyped these plants for 38 microsatellite markers as well as for 171 outlier single nucleotide polymorphisms (SNPs) that displayed excess of allele differentiation between pairs of lowland and highland populations and/or correlation with environmental variables. Our results revealed that phenotypic differentiation at 10 out of the 18 traits was driven by local selection. Trait covariation along the elevation gradient indicated that adaptation to altitude results from the assembly of multiple co-adapted traits into a complex syndrome: as elevation increases, plants flower earlier, produce less tillers, display lower stomata density and carry larger, longer and heavier grains. The proportion of outlier SNPs associating with phenotypic variation, however, largely depended on whether we considered a neutral structure with 5 genetic groups (73.7%) or 11 populations (13.5%), indicating that population stratification greatly affected our results. Finally, chromosomal inversions were enriched for both SNPs whose allele frequencies shifted along elevation as well as phenotypically-associated SNPs. Altogether, our results are consistent with the establishment of an altitudinal syndrome promoted by local selective forces in teosinte populations in spite of detectable gene flow. Because elevation mimics climate change through space, SNPs that we found underlying phenotypic variation at adaptive traits may be relevant for future maize breeding.

Temporal turnover of the soil microbiome composition is guild-specific.

Although spatial and temporal variation are both important components structuring microbial communities, the exact quantification of temporal turnover rates of fungi and bacteria has not been performed to date. In this study, we utilised repeated resampling of bacterial and fungal communities at specific locations across multiple years to describe their patterns and rates of temporal turnover. Our results show that microbial communities undergo temporal change at a rate of 0.010-0.025 per year (in units of Sorensen similarity), and the change in soil is slightly faster in fungi than in bacteria, with bacterial communities changing more rapidly in litter than soil. Importantly, temporal development differs across fungal guilds and bacterial phyla with different ecologies. While some microbial guilds show consistent responses across regional locations, others show site-specific development with weak general patterns. These results indicate that guild-level resolution is important for understanding microbial community assembly, dynamics and responses to environmental factors.

Frugivory Specialization in Birds and Fruit Chemistry Structure Mutualistic Networks across the Neotropics.

AbstractThe interaction between fruit chemistry and the physiological traits of frugivores is expected to shape the structure of mutualistic seed dispersal networks, but it has been understudied compared with the role of morphological trait matching in structuring interaction patterns. For instance, highly frugivorous birds (i.e., birds that have fruits as the main component of their diets), which characteristically have fast gut passage times, are expected to avoid feeding on lipid-rich fruits because of the long gut retention times associated with lipid digestion. Here, we compiled data from 84 studies conducted in the Neotropics that used focal plant methods to record 35,815 feeding visits made by 317 bird species (155 genera in 28 families) to 165 plant species (82 genera in 48 families). We investigated the relationship between the degree of frugivory of birds (i.e., how much of their diet is composed of fruit) at the genus level and their visits to plant genera that vary in fruit lipid content. We used a hierarchical modeling of species communities approach that accounted for the effects of differences in body size, bird and plant phylogeny, and spatial location of study sites. We found that birds with a low degree of frugivory (e.g., predominantly insectivores) tend to have the highest increase in visitation rates as fruits become more lipid rich, while birds that are more frugivorous tend to increase visits at a lower rate or even decrease visitation rates as lipids increase in fruits. This balance between degree of frugivory and visitation rates to lipid-poor and lipid-rich fruits provides a mechanism to explain specialized dispersal systems and the occurrence of certain physiological nutritional filters, ultimately helping us to understand community-wide interaction patterns between birds and plants.

Maternal effects shape the seed mycobiome in Quercus petraea.

The tree seed mycobiome has received little attention despite its potential role in forest regeneration and health. The aim of the present study was to analyze the processes shaping the composition of seed fungal communities in natural forests as seeds transition from the mother plant to the ground for establishment. We used metabarcoding approaches and confocal microscopy to analyze the fungal communities of seeds collected in the canopy and on the ground in four natural populations of sessile oak (Quercus petraea). Ecological processes shaping the seed mycobiome were inferred using joint species distribution models. Fungi were present in seed internal tissues, including the embryo. The seed mycobiome differed among oak populations and trees within the same population. Its composition was largely influenced by the mother, with weak significant environmental influences. The models also revealed several probable interactions among fungal pathogens and mycoparasites. Our results demonstrate that maternal effects, environmental filtering and biotic interactions all shape the seed mycobiome of sessile oak. They provide a starting point for future research aimed at understanding how maternal genes and environments interact to control the vertical transmission of fungal species that could then influence seed dispersal and germination, and seedling recruitment.

Temperature effects on the temporal dynamics of a subarctic invertebrate community.

Climate warming is predicted to have major impacts on the structure of terrestrial communities, particularly in high latitude ecosystems where growing seasons are short. Higher temperatures may dampen seasonal dynamics in community composition as a consequence of earlier snowmelt, with potentially cascading effects across all levels of biological organisation. Here, we examined changes in community assembly and structure along a natural soil temperature gradient in the Hengill geothermal valley, Iceland, during the summer of 2015. Sample collection over several time points within a season allowed us to assess whether temperature alters temporal variance in terrestrial communities and compositional turnover. We found that seasonal fluctuations in species richness, diversity and evenness were dampened as soil temperature increased, whereas invertebrate biomass varied more. Body mass was found to be a good predictor of species occurrence, with smaller species found at higher soil temperatures and emerging earlier in the season. Our results provide more in-depth understanding of the temporal nature of community and population-level responses to temperature, and indicate that climate warming will likely dampen the seasonal turnover of community structure that is characteristic of high latitude invertebrate communities.

Does trait-based joint species distribution modelling reveal the signature of competition in stream macroinvertebrate communities?

The occupancy and abundance of species are jointly driven by local factors, such as environmental characteristics and biotic interactions, and regional-scale factors, such as dispersal and climate. Recently, it has been shown that biotic interactions shape species occupancies and abundances beyond local extents. However, for small ectothermic animals, particularly for those occurring in freshwater environments, the importance of biotic interactions remains understudied. Species-to-species associations from joint species distribution models (i.e. species associations while controlling for environmental characteristics) are increasingly used to draw hypotheses of which species possibly show biotic interactions. We studied whether species-to-species associations from joint species distribution models show signs of competition using a hypothesis testing framework in stream macroinvertebrate communities at regional extent. We sampled aquatic macroinvertebrates from 105 stream sites in western Finland encompassing a latitudinal gradient of c. 500 kilometres. We hypothesized that if competition drives these associations (H1) functionally, similar species are mostly negatively associated, whereas functionally dissimilar species show random associations. We further hypothesized that the relationship between functional dissimilarity and the strength of association is more pronounced (H2) for abundances rather than occupancies, (H3) at small grain (i.e. stream site) rather than at large grain (i.e. river basin), and (H4) among species having weak dispersal ability than among species with high dispersal ability. Stream macroinvertebrates showed both negative and positive species-to-species associations while controlling for habitat characteristics. However, the negative associations were mostly at large grain (river basin) rather than at small grain (stream site), in occupancy rather than abundance, and not related to species functional dissimilarity or to their dispersal ability. Thus, all our hypotheses considering possible competition (H1-H4) were rejected. Competition does not appear to be a major driving force of stream macroinvertebrate communities at the spatial grain sizes considered. The observed positive associations in occupancy at small grain (stream site) may be attributed to species' similar microhabitat preferences, whereas at large grain (river basin), they may stem from metacommunity dynamics. Our results highlight that species traits were necessary to interpret whether or not species-to-species associations from joint species distribution models resulted from biotic interactions.

Habitat fragmentation and species diversity in competitive communities.

Habitat loss is one of the key drivers of the ongoing decline of biodiversity. However, ecologists still argue about how fragmentation of habitat (independent of habitat loss) affects species richness. The recently proposed habitat amount hypothesis posits that species richness only depends on the total amount of habitat in a local landscape. In contrast, empirical studies report contrasting patterns: some find positive and others negative effects of fragmentation per se on species richness. To explain this apparent disparity, we devise a stochastic, spatially explicit model of competitive species communities in heterogeneous habitats. The model shows that habitat loss and fragmentation have complex effects on species diversity in competitive communities. When the total amount of habitat is large, fragmentation per se tends to increase species diversity, but if the total amount of habitat is small, the situation is reversed: fragmentation per se decreases species diversity.

Dynamics of a host-parasitoid interaction clarified by modelling and DNA sequencing.

It has been hypothesised that the 2-year oscillations in abundance of Xestia moths are mediated by interactions with 1-year Ophion parasitoid wasps. We tested this hypothesis by modelling a 35-year time series of Xestia and Ophion from Northern Finland. Additionally, we used DNA barcoding to ascertain the species diversity of Ophion and targeted amplicon sequencing of their gut contents to confirm their larval hosts. Modelling of the time-series data strongly supported the hypothesised host-parasitoid dynamics and that periodic occurrence of Xestia moths is mediated by Ophion. DNA barcodes revealed that Ophion included five species rather than just one while targeted amplicon sequencing verified that Ophion does parasitise Xestia. At least one Ophion species employs 1-year Syngrapha interrogationis as an alternate host, but it did not detectably affect Xestia-Ophion dynamics. We also demonstrate the previously unrecognised complexity of this system due to cryptic parasitoid diversity.

Spatial synchrony is related to environmental change in Finnish moth communities.

Spatially distinct pairs of sites may have similarly fluctuating population dynamics across large geographical distances, a phenomenon called spatial synchrony. However, species rarely exist in isolation, but rather as members of interactive communities, linked with other communities through dispersal (i.e. a metacommunity). Using data on Finnish moth communities sampled across 65 sites for 20 years, we examine the complex synchronous/anti-synchronous relationships among sites using the geography of synchrony framework. We relate site-level synchrony to mean and temporal variation in climatic data, finding that colder and drier sites-and those with the most drastic temperature increases-are important for spatial synchrony. This suggests that faster-warming sites contribute most strongly to site-level estimates of synchrony, highlighting the role of a changing climate to spatial synchrony. Considering the spatial variability in climate change rates is therefore important to understand metacommunity dynamics and identify habitats which contribute most strongly to spatial synchrony.

Accounting for environmental variation in co-occurrence modelling reveals the importance of positive interactions in root-associated fungal communities.

Understanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co-occurrences that are not constrained by environmental conditions. In this study, we investigated co-occurrences among root-associated fungi, asking whether fungi co-occur more or less strongly than expected based on the environmental conditions and the host plant species examined. We generated molecular data on root-associated fungi of five plant species evenly sampled along an elevational gradient at a high arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co-occurrences that could be explained by the environmental conditions and the host plant species, as well as those co-occurrences that remained unexplained and thus more probably reflect interactive associations. Our results indicate that not only negative but also positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co-occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root-associated fungi are predominantly positive.

Adaptation to local climate in multi-trait space: evidence from silver fir (Abies alba Mill.) populations across a heterogeneous environment.

Heterogeneous environments, such as mountainous landscapes, create spatially varying selection pressure that potentially affects several traits simultaneously across different life stages, yet little is known about the general patterns and drivers of adaptation in such complex settings. We studied silver fir (Abies alba Mill.) populations across Switzerland and characterized its mountainous landscape using downscaled historical climate data. We sampled 387 trees from 19 populations and genotyped them at 374 single-nucleotide polymorphisms (SNPs) to estimate their demographic distances. Seedling morphology, growth and phenology traits were recorded in a common garden, and a proxy for water use efficiency was estimated for adult trees. We tested whether populations have more strongly diverged at quantitative traits than expected based on genetic drift alone in a multi-trait framework, and identified potential environmental drivers of selection. We found two main responses to selection: (i) populations from warmer and more thermally stable locations have evolved towards a taller stature, and (ii) the growth timing of populations evolved towards two extreme strategies, 'start early and grow slowly' or 'start late and grow fast', driven by precipitation seasonality. Populations following the 'start early and grow slowly' strategy had higher water use efficiency and came from inner Alpine valleys characterized by pronounced summer droughts. Our results suggest that contrasting adaptive life-history strategies exist in silver fir across different life stages (seedling to adult), and that some of the characterized populations may provide suitable seed sources for tree growth under future climatic conditions.

The relative importance of local and regional processes to metapopulation dynamics.

Metapopulation dynamics - patch occupancy, colonization and extinction - are the result of complex processes at both local (e.g. environmental conditions) and regional (e.g. spatial arrangement of habitat patches) scales. A large body of work has focused on habitat patch area and connectivity (area-isolation paradigm). However, these approaches often do not incorporate local environmental conditions or fully address how the spatial arrangement of habitat patches (and resulting connectivity) can influence metapopulation dynamics. Here, we utilize long-term data on a classic metapopulation system - the Glanville fritillary butterfly occupying a set of dry meadows and pastures in the Åland islands - to investigate the relative roles of local environmental conditions, geographic space and connectivity in capturing patch occupancy, colonization and extinction. We defined connectivity using traditional measures as well as graph-theoretic measures of centrality. Using boosted regression tree models, we find roughly comparable model performance among models trained on environmental conditions, geographic space or patch centrality. In models containing all of the covariates, we find strong and consistent evidence for the roles of resource abundance, longitude and centrality (i.e. connectivity) in predicting habitat patch occupancy and colonization, while patch centrality (connectivity) was relatively unimportant for predicting extinction. Relative variable importance did not change when geographic coordinates were not considered and models underwent spatially stratified cross-validation. Together, this suggests that the combination of regional-scale connectivity measures and local-scale environmental conditions is important for predicting metapopulation dynamics and that a stronger integration of ideas from network theory may provide insight into metapopulation processes.