Metapopulation capacity determines food chain length in fragmented landscapes

Quantitative evaluation of the global impacts of human land modification on raptors

Raptors are threatened by anthropogenic land modifications, but targeted quantitative assessment of these impacts is lacking. We conducted the first global quantitative evaluation of the impacts of human-modified land on raptors. We used eBird data from 2001 to 2020 on 425 raptor species and occupancy models to assess the impacts of human-modified land on raptor distribution. The mean spatiotemporal correlations of human settlement, cropland, and pasture with raptor occupancy probability were -0.048 (SE 0.031), -0.134 (0.032), and -0.145 (0.032), respectively. The mean sensitivity of raptor occupancy probability to settlement, cropland, and pasture was -5.760 (2.266), -3.128 (1.540), and -2.402 (1.551), respectively. The occupancy probability of raptors with a large body mass was more negatively correlated with cropland (phylogenetic generalized least squares regressions: slope = -0.052 [SE 0.022], t = -2.335, df = 1, 407, p = 0.020, λ = 0.006) and more positively correlated with pasture (slope = 0.047 [0.022], t = 2.118, df = 1, 407, p = 0.035, λ = 0.013). The occupancy probability of raptors with a more extensive range size was more positively correlated with cropland (slope = 0.002 [0.004], t = 0.399, df = 1, 407, p < 0.001, λ = 0.000). Raptors that prefer open habitats were more positively correlated with cropland (analysis of variance: F = 3.424, df = 2, p = 0.034, λ = 0.000) and pasture (F = 6.577, df = 2, p = 0.002, λ = 0.000). In Africa and South America, where raptor species are most abundant, raptor occupancy probability decreased over 20 years, most likely due to habitat fragmentation associated with human land modification. Although raptors with different ecological characteristics had different responses to human land modification, the impacts of settlement, cropland, and pasture on mean raptor occupancy probability were negative, regardless of space and time.

Assessing mutualistic metacommunity capacity by integrating spatial and interaction networks

We develop a spatially realistic model of mutualistic metacommunities that exploits the joint structure of spatial and interaction networks. Assuming that all species have the same colonisation and extinction parameters, this model exhibits a sharp transition between stable non-null equilibrium states and a global extinction state. This behaviour allows defining a threshold on colonisation/extinction parameters for the long-term metacommunity persistence. This threshold, the 'metacommunity capacity', extends the metapopulation capacity concept and can be calculated from the spatial and interaction networks without needing to simulate the whole dynamics. In several applications we illustrate how the joint structure of the spatial and the interaction networks affects metacommunity capacity. It results that a weakly modular spatial network and a power-law degree distribution of the interaction network provide the most favourable configuration for the long-term persistence of a mutualistic metacommunity. Our model that encodes several explicit ecological assumptions should pave the way for a larger exploration of spatially realistic metacommunity models involving multiple interaction types.

Coevolution of species colonisation rates controls food-chain length in spatially structured food webs

How the complexity of food webs depends on environmental variables is a long-standing ecological question. It is unclear though how food-chain length should vary with adaptive evolution of the constitutive species. Here we model the evolution of species colonisation rates and its consequences on occupancies and food-chain length in metacommunities. When colonisation rates can evolve, longer food-chains can persist. Extinction, perturbation and habitat loss all affect evolutionarily stable colonisation rates, but the strength of the competition-colonisation trade-off has a major role: weaker trade-offs yield longer chains. Although such eco-evo dynamics partly alleviates the spatial constraint on food-chain length, it is no magic bullet: the highest, most vulnerable, trophic levels are also those that least benefit from evolution. We provide qualitative predictions regarding how trait evolution affects the response of communities to disturbance and habitat loss. This highlights the importance of eco-evolutionary dynamics at metacommunity level in determining food-chain length.

Maintenance of biodiversity in multitrophic metacommunities: Dispersal mode matters

Although metacommunity models generally formulate dispersal as a random, passive process, mounting evidence suggests that dispersal can be an active process depending on species fitness over the landscape, particularly in multitrophic communities. How different dispersal modes (i.e. from random to increasingly fitness-dependent dispersal) modulate the effect of dispersal on biodiversity remains unclear. Here, we used a metacommunity model of food webs to investigate the effects of dispersal and habitat heterogeneity on biodiversity and how these effects may be dependent on dispersal mode. Our results showed that compared to isolated systems, random dispersal increased local food web diversity ( α $$ \upalpha $$ diversity) but decreased across-community dissimilarity ( β $$ \upbeta $$ diversity) and regional food web diversity ( γ $$ \upgamma $$ diversity), consistent with findings from competitive metacommunity models. However, fitness-dependency could alter the effects of dispersal on biodiversity. Both β $$ \upbeta $$ and γ $$ \upgamma $$ diversity increased with the strength of fitness-dependency of dispersal, while α $$ \upalpha $$ diversity peaked at intermediate fitness-dependency. Notably, strong fitness-dependent dispersal maintained levels of β $$ \upbeta $$ and γ $$ \upgamma $$ diversity similar to those observed in isolated systems. Thus, random dispersal and isolation (i.e. no dispersal) can be considered as two extremes along the continuum of fitness-dependent dispersal, in terms of their effects on biodiversity. Moreover, both biodiversity-habitat heterogeneity and biodiversity-habitat connectivity relationships depended on the dispersal mode. Strikingly, under random dispersal, γ $$ \upgamma $$ diversity decreased with habitat heterogeneity and connectivity, but under strong fitness-dependent dispersal, it increased with habitat heterogeneity and remained unchanged as habitat connectivity increased. Our study highlights the context dependence of dispersal effects on biodiversity in heterogeneous landscapes. Our findings have useful implications for biodiversity conservation and landscape management, where management strategies should account for different modes of dispersal across taxa, thus different responses of biodiversity to habitat heterogeneity and connectivity.

Metapopulation persistence can be inferred from incomplete surveys

Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation-populations inhabiting habitat patches connected by dispersal-can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (Amazilia boucardi). On the basis of our statistical framework, we provide some sampling suggestion for monitoring metapopulation persistence. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete patch surveys.

Effects of habitat destruction on coevolving metacommunities

Habitat destruction is a growing threat to biodiversity and ecosystem services. The ecological consequences of habitat loss and fragmentation involve reductions in species abundance and even the extinction of species and their interactions. However, we do not yet understand how habitat loss alters the coevolutionary trajectories of the remaining species or how coevolution, in turn, affects their response to habitat loss. To investigate this, we develop a spatially explicit model which couples metacommunity and coevolutionary dynamics. We show that, by changing the size, composition and structure of local networks, habitat destruction increases the diversity of coevolutionary trajectories of mutualists across the landscape. Conversely, in antagonistic communities, some species increase while others reduce their spatial trait heterogeneity. Furthermore, we show that while coevolution dampens the negative effects of habitat destruction in mutualistic networks, its effects on the persistence of antagonistic communities tend to be smaller and less predictable.

Multispecies coexistence in fragmented landscapes

Spatial dynamics have long been recognized as an important driver of biodiversity. However, our understanding of species' coexistence under realistic landscape configurations has been limited by lack of adequate analytical tools. To fill this gap, we develop a spatially explicit metacommunity model of multiple competing species and derive analytical criteria for their coexistence in fragmented heterogeneous landscapes. Specifically, we propose measures of niche and fitness differences for metacommunities, which clarify how spatial dynamics and habitat configuration interact with local competition to determine coexistence of species. We parameterize our model with a Bayesian approach using a 36-y time-series dataset of three Daphnia species in a rockpool metacommunity covering >500 patches. Our results illustrate the emergence of interspecific variation in extinction and recolonization processes, including their dependencies on habitat size and environmental temperature. We find that such interspecific variation contributes to the coexistence of Daphnia species by reducing fitness differences and increasing niche differences. Additionally, our parameterized model allows separating the effects of habitat destruction and temperature change on species extinction. By integrating coexistence theory and metacommunity theory, our study provides platforms to increase our understanding of species' coexistence in fragmented heterogeneous landscapes and the response of biodiversity to environmental changes.