Genetic spatial structure in a butterfly metapopulation correlates better with past than present demographic structure

The Glanville fritillary butterfly ( Melitaea cinxia ) has been studied in the Åland Islands in Finland since 1991, where it occurs as a classic metapopulation in a large network of 4000 dry meadows. Much ecological work has been conducted on this species, but population genetic studies have been hampered by paucity of suitable genetic markers. Here, using single nucleotide polymorphisms and microsatellites developed for the Glanville fritillary, we examine the correspondence between the demographic and genetic spatial structures. Given the dynamic nature of the metapopulation, the current genetic spatial structure may bear a signal of past changes in population sizes and past patterns of gene flow rather than reflect the current demographic structure or landscape structure. We analyse this question with demographic data for 10 years, using the Rand index to assess the similarity between the genetic, demographic, and landscape spatial structures. Our results show that the current genetic spatial structure is better explained by the past rather than by the current demographic spatial structure or by the spatial configuration of the habitat in the landscape. Furthermore, current genetic diversity is significantly explained by past metapopulation sizes. The time lag between major demographic events and change in the genetic spatial structure and diversity has implications for the study of spatial dynamics.     

Developmental Dynamics and G-Matrices: Can Morphometric Spaces be Used to Model Phenotypic Evolution?

Modern morphometrics, especially geometric morphometrics, is a powerful tool for modeling the evolution and development of the phenotype. Complicated morphological transformations can be simulated by using standard evolutionary genetic equations for processes such as selection and drift in the same morphospaces that are used for empirical morphometric studies. Such applications appear to be consistent with the theory of quantitative evolution of the phenotype. Nevertheless, concerns exist whether simulations of phenotypic changes directly in morphospaces is realistic because trajectories traced in such spaces describe continuous gradations in the phenotype and because the gain and loss of structures is often impossible because morphospaces are necessarily constructed from variables shared in common by all the phenotypes being considered. Competing models of phenotypic change emphasize morphological discontinuity and novelty. Recently developed models of phenotypic evolution that introduce a “phenotypic landscape” between evolutionary genetic constructs like the adaptive landscape and morphospace may correct this shortcoming.     

Not all non‐natives are equally unequal: reductions in herbivore β‐diversity depend on phylogenetic similarity to native plant community

Effects of host plant α‐ and β‐diversity often confound studies of herbivore β‐diversity, hindering our ability to predict the full impact of non‐native plants on herbivores. Here, while controlling host plant diversity, we examined variation in herbivore communities between native and non‐native plants, focusing on how plant relatedness and spatial scale alter the result. We found lower absolute magnitudes of β‐diversity among tree species and among sites on non‐natives in all comparisons. However, lower relative β‐diversity only occurred for immature herbivores on phylogenetically distinct non‐natives vs. natives. Locally in that comparison, non‐native gardens had lower host specificity; while among sites, the herbivores supported were a redundant subset of species on natives. Therefore, when phylogenetically distinct non‐natives replace native plants, the community of immature herbivores is likely to be homogenised across landscapes. Differences in communities on closely related non‐natives were subtler, but displayed community shifts and increased generalisation on non‐natives within certain feeding guilds.     

Spatial early warning signals for impending regime shifts: A practical framework for application in real‐world landscapes

Prediction of ecosystem response to global environmental change is a pressing scientific challenge of major societal relevance. Many ecosystems display nonlinear responses to environmental change, and may even undergo practically irreversible ‘regime shifts’ that initiate ecosystem collapse. Recently, early warning signals based on spatiotemporal metrics have been proposed for the identification of impending regime shifts. The rapidly increasing availability of remotely sensed data provides excellent opportunities to apply such model‐based spatial early warning signals in the real world, to assess ecosystem resilience and identify impending regime shifts induced by global change. Such information would allow land‐managers and policy makers to interfere and avoid catastrophic shifts, but also to induce regime shifts that move ecosystems to a desired state. Here, we show that the application of spatial early warning signals in real‐world landscapes presents unique and unexpected challenges, and may result in misleading conclusions when employed without careful consideration of the spatial data and processes at hand. We identify key practical and theoretical issues and provide guidelines for applying spatial early warning signals in heterogeneous, real‐world landscapes based on literature review and examples from real‐world data. Major identified issues include (1) spatial heterogeneity in real‐world landscapes may enhance reversibility of regime shifts and boost landscape‐level resilience to environmental change (2) ecosystem states are often difficult to define, while these definitions have great impact on spatial early warning signals and (3) spatial environmental variability and socio‐economic factors may affect spatial patterns, spatial early warning signals and associated regime shift predictions. We propose a novel framework, shifting from an ecosystem perspective towards a landscape approach. The framework can be used to identify conditions under which resilience assessment with spatial remotely sensed data may be successful, to support well‐informed application of spatial early warning signals, and to improve predictions of ecosystem responses to global environmental change.     

Modelling riparian forest distribution and composition to entire river networks

Aim: Developing a methodology to map the distribution of riparian forests to entire river networks and determining the main environmental factors controlling their spatial patterns. Location: Cantabrian region, northern Spain. Methods: We mapped the riparian forests at a physiognomic and phytosociological level by delimiting riparian zones and generating vegetation distribution models based on remote sensing data (Landsat 8 OLI and LiDAR PNOA). We built virtual watersheds to define a spatial framework where the catchment environmental information can be specified for each river reach, in combination with the vegetation map. In order to determine the drivers that play a significant role in the observed spatial patterns in riparian forests, based on our data sets we modelled interactions between environmental information and riparian vegetation by using the Random Forest algorithm. Results: The modelling results obtained reliably reproduced the variation of riparian forest structure and composition across Cantabrian watersheds. The produced maps were highly accurate, with a more than 70% overall accuracy for forest occurrence. A clear differentiation between Eurosiberian (habitats 91E0 and 9160) and Mediterranean (92E0) riparian forests was shown on both sides of the mountain range. Topography and land use were the main drivers defining the distribution of riparian forest as a physiognomic unit. In turn, altitude, climate and percentage of pasture were the most relevant factors determining their composition (phytosociological approach). Conclusions: Our study confirms that anthropic control ultimately defines the distribution of vegetation in the riparian area at a regional to local scale. Human disturbances constrain the extension of forest patches across their potential distribution defined by topoclimatic boundaries, which establish a clear limit between Mediterranean and Eurosiberian biogeographical regions.     

西北干旱城市破碎化绿地生境的植物群落设计途径研究

中国西北干旱城市建成环境绿地生境主要特征表现为破碎化、规模大、尺度小和生境多样化,但在现实中其设计方式单一,绿地空间和生境资源被浪费,亟待找到适宜的生态设计途径。以西安建筑科技大学2个生境花园的实践和实验研究为例,提出以1m×1m作为基本尺度单元的“生境营造+地被群落” 设计模式。“生境营造”以光照和水作为主导生境因子划分生境类型,并在场地设计时优化生境条件。“地被群落”设计可以师法西北地区多样化的自然草地群落原型,结合8种群落设计的基本模式,营造多样性、动态性的城市植物群落景观,降低管理维护成本,提高群落的生态效益和可持续性。     

Feeding ecology of bonobos living in forest‐savannah mosaics: Diet seasonal variation and importance of fallback foods

Primates along with many other animal taxa are forced to cope with large shifts in basic ecological conditions because of rapid anthropogenically induced changes of their habitats. One of the coping strategies for primates is to adjust their diet to these changes, and several studies have demonstrated the importance of fallback resources for this. Bonobos, like chimpanzees, might be particularly vulnerable to habitat fragmentation because of their high dependence on fruit availability. Little is known, however, about bonobo feeding ecology in fragmented habitats and their use of fallback resources. In this study, we investigate diet seasonal variation and the exploitation of preferred and fallback foods in a bonobo population living in forest‐savannah mosaics. Results show that bonobos have adapted to this fragmented habitat by feeding on only a few fruit species, including an important number of non‐tree species (liana, herb and savannah shrub), in comparison to populations living in dense forests. These non‐tree plants have been defined as fallback and non‐preferred foods, which are most probably consumed to maintain high frugivory. Interestingly, we identified that preferred foods are all typical of mature forests while fallback resources are mainly found in forest edges or disturbed areas. This finding indicates that bonobos prefer to use mature forests when feeding, as they do for nesting, but extend their range use to forest areas in close proximity to humans when the availability of preferred fruits is low. Finally, we show that bonobo diet relies heavily on two abundant fallback fruits: Musanga cecropioides and Marantochloa leucantha. Other studies have demonstrated that the selection of abundant fallback resources enables primates to subsist at high densities and to maintain cohesive groups, as observed at this study site. Our findings suggest that bonobos living in forest‐savannah mosaics can be considered as staple fallback food consumers. Am. J. Primatol. 77:948–962, 2015. © 2015 Wiley Periodicals, Inc.

     

Computational proteomics of biomolecular interactions in the sequence and structure space of the tyrosine kinome: deciphering the molecular basis of the kinase inhibitors selectivity

Understanding and predicting the molecular basis of protein kinases specificity against existing therapeutic agents remains highly challenging and deciphering this complexity presents an important problem in discovery and development of effective cancer drugs. We explore a recently introduced computational approach for in silico profiling of the tyrosine kinases binding specificity with a class of the pyrido-[2,3-d]pyrimidine kinase inhibitors. Computational proteomics analysis of the ligand-protein interactions using parallel simulated tempering with an ensemble of the tyrosine kinases crystal structures reveals an important molecular determinant of the kinase specificity. The pyrido-[2,3-d]pyrimidine inhibitors are capable of dynamically interacting with both active and inactive forms of the tyrosine kinases, accommodating structurally different kinase conformations with a similar binding affinity. Conformational tolerance of the protein tyrosine kinases binding with the pyrido[2,3-d]pyrimidine inhibitors provides the molecular basis for the broad spectrum of potent activities and agrees with the experimental inhibition profiles. The analysis of the pyrido[2,3-d]pyrimidine sensitivities against a number of clinically relevant ABL kinase mutants suggests an important role of conformational adaptability of multitargeted kinase inhibitors in developing drug resistance mechanisms. The presented computational approach may be useful in complementing proteomics technologies to characterize activity signatures of small molecules against a large number of potential kinase targets.