This volume investigates the contemporary fauna that inhabit the Cuatro Ciénegas Basin. Divided into 15 chapters, it addresses and describes their diversity, taxonomic and biogeogaphic affinities, and ecological characteristics. The Cuatro Ciénegas Valley is a unique oasis in the south-central region of the State of Coahuila, part of the Sonoran Desert, in Mexico. Several clues, specially derived from the study of the microbiota, suggest a very ancient origin of the valley and its permanence through time. This condition had promoted a high level of endemism and led to unique interactions between the resident species.

The Neotropical area is a main setting of the earliest experiences of domestication ofplants, and evolutionary processes guided by humans, which continue being active inthe area. Studies comprised in this Research Topic show a general panorama aboutsimilarities and particularities of processes of domestication for different plant groupsand regions, some of them illustrate how the domestication processes originated anddiffused, how landscape domestication has operated and continues being practicedand others discuss some of the main challenges for designing policies for biosafetyand conservation of plant genetic resources. It is an attempt to identify main topicsfor research on evolution under domestication, and opportunities that researcherscan find in the Neotropics to understand how and why these processes occurredin the past and present.

Reliable predictions of how changing climate and disturbance regimes will affect forest ecosystems are crucial for effective forest management. Current fire and climate research in forest ecosystem and community ecology offers data and methods that can inform such predictions. However, research in these fields occurs at different scales, with disparate goals, methods, and context. Often results are not readily comparable among studies and defy integration. We discuss the strengths and weaknesses of three modeling paradigms: empirical gradient models, mechanistic ecosystem models, and stochastic landscape disturbance models. We then propose a synthetic approach to multi-scale analysis of the effects of climatic change and disturbance on forest ecosystems. Empirical gradient models provide an anchor and spatial template for stand-level forest ecosystem models by quantifying key parameters for individual species and accounting for broad-scale geographic variation among them. Gradient imputation transfers predictions of fine-scale forest composition and structure across geographic space. Mechanistic ecosystem dynamic models predict the responses of biological variables to specific environmental drivers and facilitate understanding of temporal dynamics and disequilibrium. Stochastic landscape dynamics models predict frequency, extent, and severity of broad-scale disturbance. A robust linkage of these three modeling paradigms will facilitate prediction of the effects of altered fire and other disturbance regimes on forest ecosystems at multiple scales and in the context of climatic variability and change.