Environmental fluctuations explain the universal decay of species-abundance correlations with phylogenetic distance.

Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches-which combine phylogenetic relationships between species with community ecology-have the potential to disentangle such forces but are often hard to connect with quantitative predictions from theoretical models. On the other hand, macroecology, which focuses on statistical patterns of abundance and diversity, provides natural connections with theoretical models but often neglects interspecific correlations and interactions. Here, we propose a unified framework combining both such approaches to analyze microbial communities. In particular, by using both cross-sectional and longitudinal metagenomic data for species abundances, we reveal the existence of an empirical macroecological law establishing that correlations in species-abundance fluctuations across communities decay from positive to null values as a function of phylogenetic dissimilarity in a consistent manner across ecologically distinct microbiomes. We formulate three variants of a mechanistic model-each relying on alternative ecological forces-that lead to radically different predictions. From these analyses, we conclude that the empirically observed macroecological pattern can be quantitatively explained as a result of shared population-independent fluctuating resources, i.e., environmental filtering and not as a consequence of, e.g., species competition. Finally, we show that the macroecological law is also valid for temporal data of a single community and that the properties of delayed temporal correlations can be reproduced as well by the model with environmental filtering.

Inferring the Evolutionary Model of Community-Structuring Traits with Convolutional Kitchen Sinks.

When communities are assembled through processes such as filtering or limiting similarity acting on phylogenetically conserved traits, the evolutionary signature of those traits may be reflected in patterns of community membership. We show how the model of trait evolution underlying community-structuring traits can be inferred from community membership data using both a variation of a traditional eco-phylogenetic metric-the mean pairwise distance (MPD) between taxa-and a recent machine learning tool, Convolutional Kitchen Sinks (CKS). Both methods perform well across a range of phylogenetically informative evolutionary models, but CKS outperforms MPD as tree size increases. We demonstrate CKS by inferring the evolutionary history of freeze tolerance in angiosperms. Our analysis is consistent with a late burst model, suggesting freeze tolerance evolved recently. We suggest that multiple data types that are ordered on phylogenies, such as trait values, species interactions, or community presence/absence, are good candidates for CKS modeling because the generative models produce structured differences between neighboring points that CKS is well-suited for. We introduce the R package kitchen to perform CKS for generic application of the technique.

Using individual-based trait frequency distributions to forecast plant-pollinator network responses to environmental change.

Determining how and why organisms interact is fundamental to understanding ecosystem responses to future environmental change. To assess the impact on plant-pollinator interactions, recent studies have examined how the effects of environmental change on individual interactions accumulate to generate species-level responses. Here, we review recent developments in using plant-pollinator networks of interacting individuals along with their functional traits, where individuals are nested within species nodes. We highlight how these individual-level, trait-based networks connect intraspecific trait variation (as frequency distributions of multiple traits) with dynamic responses within plant-pollinator communities. This approach can better explain interaction plasticity, and changes to interaction probabilities and network structure over spatiotemporal or other environmental gradients. We argue that only through appreciating such trait-based interaction plasticity can we accurately forecast the potential vulnerability of interactions to future environmental change. We follow this with general guidance on how future studies can collect and analyse high-resolution interaction and trait data, with the hope of improving predictions of future plant-pollinator network responses for targeted and effective conservation.

Uncovering Broad Macroecological Patterns by Comparing the Shape of Species' Distributions along Environmental Gradients.

AbstractSpecies' distributions can take many different forms. For example, fat-tailed or skewed distributions are very common in nature, as these can naturally emerge as a result of individual variability and asymmetric environmental tolerances, respectively. Studying the basic shape of distributions can teach us a lot about the ways climatic processes and historical contingencies shape ecological communities. Yet we still lack a general understanding of how their shapes and properties compare to each other along gradients. Here, we use Bayesian nonlinear models to quantify range shape properties in empirical plant distributions. With this approach, we are able to distil the shape of plant distributions and compare them along gradients and across species. Studying the relationship between distribution properties, we revealed the existence of broad macroecological patterns along environmental gradients-such as those expected from Rapoport's rule and the abiotic stress limitation hypothesis. We also find that some aspects of the shape of observed ranges-such as kurtosis and skewness of the distributions-could be intrinsic properties of species or the result of their historical contexts. Overall, our modeling approach and results untangle the general shape of plant distributions and provide a mapping of how this changes along environmental gradients.

Impacts of climate timescale on the stability of trait-environment relationships.

Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait-environment model predictions if timescale is not accounted for. Here, the timescale dependence of trait-environment relationships is investigated by regressing in situ trait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales. We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub-optimal climate timescales reduces the accuracy of the resulting trait-environment relationships. This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long-term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait-environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.

Root phosphatase activity is coordinated with the root conservation gradient across a phosphorus gradient in a lowland tropical forest.

Soil phosphorus (P) is a growth-limiting nutrient in tropical ecosystems, driving diverse P-acquisition strategies among plants. Particularly, mining for inorganic P through phosphomonoesterase (PME) activity is essential, given the substantial proportion of organic P in soils. Yet, the relationship between PME activity and other nutrient-acquisition root traits remains unclear. We measured root PME activity and commonly measured root traits, including root diameter, specific root length (SRL), root tissue density (RTD), and nitrogen concentration ([N]) in 18 co-occurring species across soils with varying P availability to better understand trees response to P supply. Root [N] and RTD were inversely related, and that axis was not clearly related to soil P supply. Both traits, however, correlated positively and negatively with PME activity, which responded strongly to P supply. Conversely, root diameter was inversely related to SRL, but this axis was not related to P supply. This pattern suggests that limiting similarity influenced variation along the diameter-SRL axis, explaining local trait diversity. Meanwhile, variation along the root [N]-RTD axis might best reflect environmental filtering. Overall, P availability indicator traits such as PME activity and root hairs only tended to be associated with these axes, highlighting limitations of these axes in describing convergent adaptations at local sites.

Life goes on: Spatial heterogeneity promotes biodiversity in an urbanized coastal marine ecosystem.

Both human populations and marine biodiversity are concentrated along coastlines, with growing conservation interest in how these ecosystems can survive intense anthropogenic impacts. Tropical urban centres provide valuable research opportunities because these megacities are often adjacent to mega-diverse coral reef systems. The Pearl River Delta is a prime exemplar, as it encompasses one of the most densely populated and impacted regions in the world and is located just northwest of the Coral Triangle. However, the spatial and taxonomic complexity of this biodiversity, most of which is small, cryptic in habitat and poorly known, make comparative analyses challenging. We deployed standardized settlement structures at seven sites differing in the intensity of human impacts and used COI metabarcoding to characterize benthic biodiversity, with a focus on metazoans. We found a total of 7184 OTUs, with an average of 665 OTUs per sampling unit; these numbers exceed those observed in many previous studies using comparable methods, despite the location of our study in an urbanized environment. Beta diversity was also high, with 52% of the OTUs found at just one site. As expected, we found that the sites close to point sources of pollution had substantially lower diversity (44% less) relative to sites bathed in less polluted oceanic waters. However, the polluted sites contributed substantially to the total animal diversity of the region, with 25% of all OTUs occurring only within polluted sites. Further analysis of Arthropoda, Annelida and Mollusca showed that phylogenetic clustering within a site was common, suggesting that environmental filtering reduced biodiversity to a subset of lineages present within the region, a pattern that was most pronounced in polluted sites and for the Arthropoda. The water quality gradients surrounding the PRD highlight the unique role of in situ studies for understanding the impacts of complex urbanization pressures on biodiversity.

Near-natural streams: Spatial factors are key in shaping multiple facets of zooplankton α and ß diversity.

In near-natural basins, zooplankton are key hubs for maintaining aquatic food webs and organic matter cycles. However, the spatial patterns and drivers of zooplankton in streams are poorly understood. This study registered 165 species of zooplankton from 147 sampling sites (Protozoa, Rotifers, Cladocera and Copepods), integrating multiple dimensions (i.e., taxonomic, functional, and phylogenetic) and components (i.e., total, turnover, and nestedness) of α and ß diversity. This study aims to reveal spatial patterns, mechanisms, correlations, and relative contribution of abiotic factors (i.e., local environment, geo-climatic, land use, and spatial factors) through spatial interpolation (ordinary kriging), mantel test, and variance partitioning analysis (VPA). The study found that α diversity is concentrated in the north, while ß diversity is more in the west, which may be affected by typical habitat, hydrological dynamics and underlying mechanisms. Taxonomic and phylogenetic ß diversity is dominated by turnover, and metacommunity heterogeneity is the result of substitution of species and phylogeny along environmental spatial gradients. Taxonomic and phylogenetic ß diversity were strongly correlated (r from 0.91 to 0.95), mainly explained by historical/spatial isolation processes, community composition, generation time, and reproductive characteristics, and this correlation provides surrogate information for freshwater conservation priorities. In addition, spatial factors affect functional and phylogenetic α diversity (26%, 28%), and environmental filtering and spatial processes combine to drive taxonomic α diversity (10%) and phylogenetic ß diversity (11%). Studies suggest that spatial factors are key to controlling the community structure of zooplankton assemblages in near-natural streams, and that the relative role of local environments may depend on the dispersal capacity of species. In terms of diversity conservation, sites with high variation in uniqueness should be protected (i) with a focus on the western part of the thousand islands lake catchment and (ii) increasing effective dispersal between communities to facilitate genetic and food chain transmission.

An extended novel approach of river health analysis using nonmetric scaling ordination of fish ecological entities and functional identity indices.

As river ecosystems continue to face environmental pressures, it is crucial to develop and apply new biologically relevant statistical tools to support river health assessments. This study aimed to test the potential significance of nonmetric ordination scores and multidimensional functional indices of fish communities for analyzing river ecological health linked to variations in environmental factors. We conducted a nonmetric multidimensional scaling (NMDS) to derive ordination scores based on twenty fish ecological entities (FEs) that we newly defined, along with their relative abundance (RA). These FEs were determined through a unique combination of trophic, habitat, and tolerance guilds. Additionally, we calculated the functional diversity and identity (F-Ide) indices using the RA-weighted distances between FEs defined by the guild identities in a multidimensional space. The results showed that these novel analyses were helpful in assessing river ecological health and spatial changes in the environment. The dominant F-Ide in each community was largely responsible for the variation of river health scores, driven by the combined impact of chemical water quality, alterations in substrate composition, land use changes, and the gradient of elevation. These environmental factors significantly influenced the site scores in the first axis of NMDS, F-Ide indices, and river health scores. Therefore, our study highlights the practical value of utilizing nonmetric scaling ordination scores of FEs and F-Ide indices as tools for evaluating the health of river ecosystems. By elucidating fish community variance, these tools can aid in determining the extent of river health degradation attributable to environmental stressors, including chemical water pollution and changes in substrate resulting from changes in land use and at different elevations.

A spatially explicit trait-based approach uncovers changes in assembly processes under warming.

The re-assembly of plant communities during climate warming depends on several concurrent processes. Here, we present a novel framework that integrates spatially explicit sampling, plant trait information and a warming experiment to quantify shifts in these assembly processes. By accounting for spatial distance between individuals, our framework allows separation of potential signals of environmental filtering from those of different types of competition. When applied to an elevational transplant experiment in the French Alps, we found common signals of environmental filtering and competition in all communities. Signals of environmental filtering were generally stronger in alpine than in subalpine control communities, and warming reduced this filter. Competition signals depended on treatments and traits: Symmetrical competition was dominant in control and warmed alpine communities, while hierarchical competition was present in subalpine communities. Our study highlights how distance-dependent frameworks can contribute to a better understanding of transient re-assembly dynamics during environmental change.

Urbanization alters the spatiotemporal dynamics of plant-pollinator networks in a tropical megacity.

Urbanization is a major driver of biodiversity change but how it interacts with spatial and temporal gradients to influence the dynamics of plant-pollinator networks is poorly understood, especially in tropical urbanization hotspots. Here, we analysed the drivers of environmental, spatial and temporal turnover of plant-pollinator interactions (interaction ß-diversity) along an urbanization gradient in Bengaluru, a South Indian megacity. The compositional turnover of plant-pollinator interactions differed more between seasons and with local urbanization intensity than with spatial distance, suggesting that seasonality and environmental filtering were more important than dispersal limitation for explaining plant-pollinator interaction ß-diversity. Furthermore, urbanization amplified the seasonal dynamics of plant-pollinator interactions, with stronger temporal turnover in urban compared to rural sites, driven by greater turnover of native non-crop plant species (not managed by people). Our study demonstrates that environmental, spatial and temporal gradients interact to shape the dynamics of plant-pollinator networks and urbanization can strongly amplify these dynamics.

Fruit Size in Indo-Malayan Island Plants Is More Strongly Influenced by Filtering than by In Situ Evolution.

AbstractCommunity trait assembly, the formation of distributions of phenotypic characteristics across coexisting species, can occur via two main processes: filtering of trait distributions from the regional pool and in situ phenotypic evolution in local communities. But the relative importance of these processes remains unclear, largely because of the difficulty in determining the timing of evolutionary trait changes and biogeographic dispersal events in phylogenies. We assessed evolutionary and biogeographic transitions in woody plant species across the Indo-Malay archipelago, a series of island groups where the same plant lineages interact with different seed disperser and seed predator assemblages. Fruit size in 2,650 taxa spanning the angiosperm tree of life tended to be smaller in the Sulawesi and Maluku island groups, where frugivores are less diverse and smaller bodied, than in the regional source pool. While numerous plant lineages (not just small-fruited ones) reached the isolated islands, colonists tended to be the smaller-fruited members of each clade. Nearly all of the evolutionary transitions to smaller fruit size predated, often substantially, organismal dispersal to the islands. Our results suggest that filtering rather than within-island evolution largely determined the distribution of fruit sizes in these regions.

DNA metabarcoding reveals impact of local recruitment, dispersal, and hydroperiod on assembly of a zooplankton metacommunity.

Understanding the environmental impact on the assembly of local communities in relation to their spatial and temporal connectivity is still a challenge in metacommunity ecology. This study aims to unravel underlying metacommunity processes and environmental factors that result in observed zooplankton communities. Unlike most metacommunity studies, we jointly examine active and dormant zooplankton communities using a DNA metabarcoding approach to overcome limitations of morphological species identification. We applied two-fragment (COI and 18S) metabarcoding to monitor communities of 24 kettle holes over a two-year period to unravel (i) spatial and temporal connectivity of the communities, (ii) environmental factors influencing local communities, and (iii) dominant underlying metacommunity processes in this system. We found a strong separation of zooplankton communities from kettle holes of different hydroperiods (degree of permanency) throughout the season, while the community composition within single kettle holes did not differ between years. Species richness was primarily dependent on pH and permanency, while species diversity (Shannon Index) was influenced by kettle hole location. Community composition was impacted by kettle hole size and surrounding field crops. Environmental processes dominated temporal and spatial processes. Sediment communities showed a different composition compared to water samples but did not differ between ephemeral and permanent kettle holes. Our results suggest that communities are mainly structured by environmental filtering based on pH, kettle hole size, surrounding field crops, and permanency. Environmental filtering based on specific conditions in individual kettle holes seems to be the dominant process in community assembly in the studied zooplankton metacommunity.

Zeta diversity differentiates factors driving community assembly of rare and common ectomycorrhizal fungi.

A fundamental goal in community ecology is to understand what factors drive community assembly processes. The factors affecting ectomycorrhizal fungal communities are unknown in many regions, particularly in the southern hemisphere. We investigate community assembly using ITS2 metabarcoding of ectomycorrhizal fungi sampled from 3943 hyphal ingrowth bags buried in 81 Nothofagus forests across New Zealand's South Island. By applying zeta diversity analysis and multisite generalized dissimilarity modelling (MS-GDM) we quantify the effects of 43 biotic and environmental variables on community turnover. Unlike traditional beta diversity analyses that are heavily influenced by rare species, the zeta diversity framework differentiates between factors driving turnover of rare and common species, providing a more complete picture of community dynamics. We found that community assembly was dominated by deterministic rather than stochastic processes and identified ecological factors affecting all taxa, as well as others that were specifically important to rare or common taxa. Soil variables were important drivers of turnover for all species, whereas ground cover variables, forest patch size, precipitation and host tree identity had greater effects on rarer species, and tree size and temperature effects were specific to more common species. Interestingly, the effect of temperature on common species is in line with recent evidence from other Kingdoms, pointing to possible generality, and highlighting the importance of considering common species. Applying these methods to fungi has allowed us to identify the distinct ecological processes that structure rare and common taxa during community assembly. This has important implications for understanding the functional effects of community responses to environmental change.

Biodiversity patterns diverge along geographic temperature gradients.

Models applying space-for-time substitution, including those projecting ecological responses to climate change, generally assume an elevational and latitudinal equivalence that is rarely tested. However, a mismatch may lead to different capacities for providing climatic refuge to dispersing species. We compiled community data on zooplankton, ectothermic animals that form the consumer basis of most aquatic food webs, from over 1200 mountain lakes and ponds across western North America to assess biodiversity along geographic temperature gradients spanning nearly 3750 m elevation and 30° latitude. Species richness, phylogenetic relationships, and functional diversity all showed contrasting responses across gradients, with richness metrics plateauing at low elevations but exhibiting intermediate latitudinal maxima. The nonmonotonic/hump-shaped diversity trends with latitude emerged from geographic interactions, including weaker latitudinal relationships at higher elevations (i.e. in alpine lakes) linked to different underlying drivers. Here, divergent patterns of phylogenetic and functional trait dispersion indicate shifting roles of environmental filters and limiting similarity in the assembly of communities with increasing elevation and latitude. We further tested whether gradients showed common responses to warmer temperatures and found that mean annual (but not seasonal) temperatures predicted elevational richness patterns but failed to capture consistent trends with latitude, meaning that predictions of how climate change will influence diversity also differ between gradients. Contrasting responses to elevation- and latitude-driven warming suggest different limits on climatic refugia and likely greater barriers to northward range expansion.

Global net biome CO2 exchange predicted comparably well using parameter-environment relationships and plant functional types.

Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model-data fusion framework of the terrestrial carbon cycle (CARDAMOM) at a global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels-a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between terrestrial biosphere model performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.

Archaeal and Bacterial Diversity and Distribution Patterns in Mediterranean-Climate Vernal Pools of Mexico and the Western USA.

Biogeographic patterns in microorganisms are poorly understood, despite the importance of microbial communities for a range of ecosystem processes. Our knowledge of microbial ecology and biogeography is particularly deficient in rare and threatened ecosystems. We tested for three ecological patterns in microbial community composition within ephemeral wetlands-vernal pools-located across Baja California (Mexico) and California (USA): (1) habitat filtering; (2) a latitudinal diversity gradient; and (3) distance decay in community composition. Paired water and soil samples were collected along a latitudinal transect of vernal pools, and bacterial and archaeal communities were characterized using 16S rDNA sequencing. We identified two main microbial communities, with one community present in the soil matrix that included archaeal and bacterial soil taxa, and another community present in the overlying water that was dominated by common freshwater bacterial taxa. Aquatic microbial communities were more diverse in the north, and displayed a significant but inverted latitudinal diversity pattern. Aquatic communities also exhibited a significant distance-decay pattern, with geographic proximity, and precipitation explaining part of the community variation. Collectively these results indicate greater sensitivity to spatial and environmental variation in vernal pool aquatic microbial communities than in soil microbial communities. We conclude that vernal pool aquatic microbial communities can display distribution patterns similar to those exhibited by larger organisms, but differ in some key aspects, such as the latitudinal gradient in diversity.

Divergence in functional traits in seven species of neotropical palms of different forest strata.

Functional traits are morphological and physiological characteristics that determine growth, reproduction, and survival strategies. The leaf economics spectrum proposes two opposing life history strategies: species with an "acquisitive" strategy grow fast and exploit high-resource environments, while species with a "conservative" strategy emphasize survival and slow growth under low resource conditions. We analyzed intra and interspecific variation in nine functional traits related to biomass allocation and tissue quality in seven Neotropical palm species from understory and canopy strata. We expected that the level of resources of a stratum that a species typically exploits would determine the dominance of either the exploitative or conservative strategy, as well as degree of divergence in functional traits between species. If this is correct, then canopy species will show an acquisitive strategy emphasizing traits targeting a larger size, whereas understory species will show a conservative strategy with traits promoting efficient biomass allocation and survival in the shade. Two principal components (57.22% of the variation) separated palm species into: (a) canopy species whose traits were congruent with the acquisitive strategy and emphasized large size (i.e., diameter, height, carbon content, and leaf area), and (b) understory species whose traits were associated with efficient biomass allocation (i.e., dry mass fraction -DMF- and tissue density). As we unravel the variation in functional traits in palms, which make up a substantial proportion of the tropical flora, we gain a deeper understanding of how plants adapt to environmental gradients.

Darwin's naturalization conundrum can be explained by spatial scale.

Darwin proposed two seemingly contradictory hypotheses regarding factors influencing the outcome of biological invasions. He initially posited that nonnative species closely related to native species would be more likely to successfully establish, because they might share adaptations to the local environment (preadaptation hypothesis). However, based on observations that the majority of naturalized plant species in the United States belonged to nonnative genera, he concluded that the lack of competitive exclusion would facilitate the establishment of alien invaders phylogenetically distinct from the native flora (competition-relatedness hypothesis). To date, no consensus has been reached regarding these opposing hypotheses. Here, following Darwin, we use the flora of the United States to examine patterns of taxonomic and phylogenetic relatedness between native and nonnative taxa across thousands of nested locations ranging in size and extent, from local to regional scales. We find that the probability of observing the signature of environmental filtering over that of competition increases with spatial scale. Further, native and nonnative species tended to be less related in warm, humid environments. Our work provides an empirical assessment of the role of observation scale and climate in biological invasions and demonstrates that Darwin's two opposing hypotheses need not be mutually exclusive.

A test of Darwin's naturalization conundrum in birds reveals enhanced invasion success in the presence of close relatives.

Biological invasions pose one of the most severe environmental challenges of the twenty-first century. A longstanding idea is that invasion risk is predictable based on the phylogenetic distance - and hence ecological resemblance - between non-native and native species. However, current evidence is contradictory. To explain these mixed results, it has been proposed that the effect is scale-dependent, with invasion inhibited by phylogenetic similarity at small spatial scales but enhanced at larger scales. Analyzing invasion outcomes in a global sample of bird communities, we find no evidence to support this hypothesis. Instead, our results suggest that invaders are locally more successful in the presence of closely related and ecologically similar species, at least in human-altered environments where the majority of invasions have occurred. Functional trait analyses further confirm that the ecological niches of invaders are phylogenetically conserved, supporting the notion that successful invasion in the presence of close relatives is driven by shared adaptations to the types of niches available in novel environments.