Bird Community Composition in a Shaded Coffee Agro-ecological Matrix in Puebla,Mexico: The Effects of Landscape Heterogeneity at Multiple Spatial Scales

This study examined the importance of habitat heterogeneity on the avian community composition, and investigated the scale at which species abundances respond to habitat variables. The study was conducted within a diverse landscape matrix of a shaded coffee region in Mexico. To detect at which characteristic spatial scale different species and foraging guilds respond most strongly we analyzed the effect of plot-, patch- and landscape-level variables at different spatial extent (i.e., different kilometer radii) on species composition and foraging guilds. We used redundancy analysis to identify species–environment correlations, and to identify predictor variables that best explained the bird community structure, quantified the influence of plot-, patch- and landscape-level variables on the bird community composition. In addition, we used the 4th-corner method to detect significant relationships between the dietary guilds and plot-, patch- and landscape-level variables. We recorded 12,335 individuals of 181 bird species; 105 bird species were recorded foraging within the shaded coffee plantations. We found that plot- and landscape-level variables significantly explained the bird community composition best across all scales, and were significantly correlated with the abundance of the dietary guilds. In contrast, patch-level variables were less important. Habitat composition variables (i.e., coffee, forest and agricultural area) were among the most important predictors. Canopy structure was more important than other vegetation structure variables in explaining dietary guild structure. Hence, the maintenance of a heterogeneous landscape with a high-quality matrix within an agro-ecological region enhances bird conservation.     

Dynamic Landscapes, Stability and Ecological Modeling

The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are possible. These include the particle on an energy landscape, the potential landscape, and the Lyapunov function landscape. I discuss the dynamics that these representations admit, and the application of each to ecological modeling and the analysis and representation of stability. CWP is a Postdoctoral Fellow with the Oak Ridge Institute for Science and Education     

Coexistence in metacommunities: a tree-species model

Simple patch-occupancy models of competitive metacommunities have shown that coexistence is possible as long as there is a competition-colonization tradeoff such as that of superior competitors and dispersers. In this paper, we present a model of competition between three species in a dynamic landscape, where patches are being created and destroyed at a different rate. In our model, species interact according to a linear non-transitive hierarchy, such that species Y(3) outcompetes and can invade patches occupied by species Y(2) and this species in turn can outcompete and invade patches occupied by the inferior competitor Y(1). In this hierarchy, inferior competitors cannot invade patches of species with higher competitive ability. Analytical results show that there are regions in the parameter space where coexistence can occur, as well as regions where each of the species exists in isolation depending on species' life-history traits associated with their colonization abilities and extinction proneness as well as with the dynamics of habitat patches. In our model, the condition for coexistence depends explicitly on patch dynamics, which in turn modulate the limiting similarity for species coexistence. Coexistence in metacommunities inhabiting dynamic landscapes although possible is harder to attain than in static ones.     

Using citizen science data to inform the relative sensitivity of waterbirds to natural versus human‐dominated landscapes in China

Habitat loss is widely regarded as one of the most destructive factors threatening native biodiversity. Because migratory waterbirds include some of the most globally endangered species, information on their sensitivity to landscape would benefit their conservation. While citizen science data on waterbird species occurrence are subjected to various biases, their appropriate interpretation can provide information of benefit to species conservation. We apply a bootstrapping procedure to citizen science data to reduce sampling biases and report the relative sensitivity of waterbird species to natural versus human‐dominated landscapes. Analyses are performed on 30,491 data records for 69 waterbird species referred to five functional groups observed in China between 2000 and 2018. Of these taxa, 30 species (43.5%) are significantly associated with natural landscapes, more so for cranes, geese, and ducks than for shorebirds and herons. The relationship between land association and the threat status of waterbirds is significant when the range size of species is considered as the mediator, and the higher the land association, the higher the threat status. Sensitive species significantly associated with natural landscapes are eight times more likely to be classified as National Protected Species (NPS) Classes I or II than less sensitive species significantly associated with human‐dominated landscapes. We demonstrate the potential for citizen science data to assist in conservation planning in the context of landscape changes. Our methods might assist others to obtain information to help relieve species decline and extinction.     

The influence of landscape on gene flow in the eastern massasauga rattlesnake (Sistrurus c. catenatus): insight from computer simulations

Understanding how gene flow shapes contemporary population structure requires the explicit consideration of landscape composition and configuration. New landscape genetic approaches allow us to link such heterogeneity to gene flow within and among populations. However, the attribution of cause is difficult when landscape features are spatially correlated, or when genetic patterns reflect past events. We use spatial Bayesian clustering and landscape resistance analysis to identify the landscape features that influence gene flow across two regional populations of the eastern massasauga rattlesnake, Sistrurus c. catenatus. Based on spatially explicit simulations, we inferred how habitat distribution modulates gene flow and attempted to disentangle the effects of spatially confounded landscape features. We found genetic clustering across one regional landscape but not the other, and also local differences in the effect of landscape on gene flow. Beyond the effects of isolation‐by‐distance, water bodies appear to underlie genetic differentiation among individuals in one regional population. Significant effects of roads were additionally detected locally, but these effects are possibly confounded with the signal of water bodies. In contrast, we found no signal of isolation‐by‐distance or landscape effects on genetic structure in the other regional population. Our simulations imply that these local differences have arisen as a result of differences in population density or tendencies for juvenile rather than adult dispersal. Importantly, our simulations also demonstrate that the ability to detect the consequences of contemporary anthropogenic landscape features (e.g. roads) on gene flow may be compromised when long‐standing natural features (e.g. water bodies) co‐exist on the landscape.     

The strength of genetic interactions scales weakly with mutational effects

Background

Genetic interactions pervade every aspect of biology, from evolutionary theory, where they determine the accessibility of evolutionary paths, to medicine, where they can contribute to complex genetic diseases. Until very recently, studies on epistatic interactions have been based on a handful of mutations, providing at best anecdotal evidence about the frequency and the typical strength of genetic interactions. In this study, we analyze a publicly available dataset that contains the growth rates of over five million double knockout mutants of the yeast Saccharomyces cerevisiae.

Results

We discuss a geometric definition of epistasis that reveals a simple and surprisingly weak scaling law for the characteristic strength of genetic interactions as a function of the effects of the mutations being combined. We then utilized this scaling to quantify the roughness of naturally occurring fitness landscapes. Finally, we show how the observed roughness differs from what is predicted by Fisher''s geometric model of epistasis, and discuss the consequences for evolutionary dynamics.

Conclusions

Although epistatic interactions between specific genes remain largely unpredictable, the statistical properties of an ensemble of interactions can display conspicuous regularities and be described by simple mathematical laws. By exploiting the amount of data produced by modern high-throughput techniques, it is now possible to thoroughly test the predictions of theoretical models of genetic interactions and to build informed computational models of evolution on realistic fitness landscapes.     

Inter- and intra-specific diversity of Cuban Pinguicula (Lentibulariaceae) based on morphometric analyses and its relation with geographical distribution

Background: Phenotypic variations have been observed in populations of west Cuban Pinguicula species. Such populations occur in patches under different ecological conditions associated with specialised habitats and separated by geographical and ecological barriers, which can lead to morphological differentiation.

Aims: To analyse morphological diversity among species and populations of Cuban Pinguicula; and to test if morphological variability is associated with geographical distribution and distance between populations.

Methods: We sampled a total of eight populations of P. albida, P. cubensis and P. filifolia and tested for morphometric differences among them by Principal Component Analysis (PCA) and analysis of variance (ANOVA) based on 31 quantitative traits. We also assessed the geographical isolation with respect to morphological distance.

Results: The studied species showed high morphological variability at both species and population level. Reproductive characteristics appeared to be more promissory than vegetative ones in distinguishing geographical groups since they clearly defined populations; nevertheless a strong component of individual variation was observed. According to the distance analysis, such morphological variations were correlated with fragmented populations and isolation and allowed the differentiation of two morphotypes of P. albida and two of P. filifolia.

Conclusions: We conclude that high phenotypic variation of the analysed species is related to geographical and ecological isolation which have led to the differentiation of morphotypes within species.     

The evolution of a highly speciose group in a changing environment: are we witnessing speciation in the Iberá wetlands?

Delimiting species is very conflicting in the case of very young taxa that are in the process of diversification, and even more difficult if the species inhabit a heterogeneous environment. In this case, even population delimitation is controversial. The South American genus of subterranean rodents Ctenomys is highly speciose, with 62 species that appeared in the lapse of 3 Myr. Within the genus, the ‘perrensi’ group, formed by three named species and a group of forms of unknown taxonomic status, inhabits the Iberá wetland, in northern Argentina. Almost every locality shows a particular chromosomal complement. To understand the relationships and the evolutionary process among species and populations, we examined mitochondrial DNA sequences and microsatellite genotypes. We found an isolation‐by‐distance pattern with evidence of cluster‐like behaviour of the system. The mitochondrial DNA network revealed two different groups, separated by one of the main rivers of the region. Clustering methods delimited 12 different populations and five metapopulation lineages that seem to be evolving independently. We found evidence of ancient migration among localities at the centre of the distribution but no signals of current migration among the 12 delimited clusters. Some of the genetic clusters found included localities with different chromosomal numbers, which points to the existence of gene flow despite chromosomal variation. The evolutionary future of these five lineages is controlled by the dynamics of their habitat: if stable, they may become distinct species; otherwise, they may collapse into a hybrid swarm, forming a single evolving metapopulation.