Pablo Guerrero

Evolutionary lag times and recent origin of the biota of an ancient desert (Atacama-Sechura).

The assembly of regional biotas and organismal responses to anthropogenic climate change both depend on the capacity of organisms to adapt to novel ecological conditions. Here we demonstrate the concept of evolutionary lag time, the time between when a climatic regime or habitat develops in a region and when it is colonized by a given clade. We analyzed the time of colonization of four clades (three plant genera and one lizard genus) into the Atacama–Sechura Desert of South America, one of Earth’s driest and oldest deserts. We reconstructed time-calibrated phylogenies for each clade and analyzed the timing of shifts in climatic distributions and biogeography and compared these estimates to independent geological estimates of the time of origin of these deserts. Chaetanthera and Malesherbia (plants) and Liolaemus (animal) invaded arid regions of the Atacama–Sechura Desert in the last 10 million years, some 20 million years after the initial onset of aridity in the region. There are also major lag times between when these clades colonized the region and when they invaded arid habitats within the region (typically 4–14 million years). Similarly, hyperarid climates developed ∼8 million years ago, but the most diverse plant clade in these habitats (Nolana) only colonized them ∼2 million years ago. Similar evolutionary lag times may occur in other organisms and habitats, but these results are important in suggesting that many lineages may require very long time scales to adapt to modern desertification and climatic change.

Evolving Visual Object Recognition for Legged Robots

Recognition of relevant game field objects, such as the ball and landmarks, is usually based upon the application of a set of decision rules over candidate image regions. Rule selection and parameters tuning are often arbitrarily done. We propose a method for evolving the selection of these rules as well as their parameters with basis on real game field images, and a supervised learning approach. The learning approach is implemented using genetic algorithms. Results of the application of our method are presented.

Phylogenetics and predictive distribution modeling provide insights into the geographic divergence of Eriosyce subgen. Neoporteria (Cactaceae)

The classification of Eriosyce subgenus Neoporteria (“subsection” in the sense of Kattermann) and the role of allopatry/sympatry in the diversification of the group were studied by use of cladistic and predictive distribution modeling methods. We reconstructed the phylogenetic relationships of subgenus Neoporteria by analyzing 38 morphological characters and DNA sequences from two chloroplast regions of 21 taxa from the Chilean subsections of Eriosyce using a Bayesian and maximum likelihood phylogenetic framework. Also, we attempted to find out if the divergence between the sister taxa in the Neoporteria group had been caused by allopatric or sympatric mechanisms. The morphology-based analysis placed E. chilensis basal within the Neoporteria clade and suggested a further broadening of the group by including E. taltalensis var. taltalensis, formerly considered a member of subsection Horridocactus. However, the combined DNA data placed E. sociabilis and E. taltalensis var. taltalensis within the Horridocactus clade, and placed E. chilensis with E. subgibbosa var. litoralis. The broad concept of E. subgibbosa sensu Kattermann (comprising seven infraspecific taxa), was rejected by our combined molecular results. Finally, our results corroborated changes in subsection Neoporteria proposed by various authors and suggested further modifications within Neoporteria. The analyses of the degree of geographic overlap of the predicted distributions indicated null overlap between the sister taxa, and one probable hybrid origin of E. chilensis, indicating that evolutionary divergence is mainly caused by an allopatric process associated with climatic tolerance.

Ecology and evolution of negative and positive interactions in Cactaceae: lessons and pending tasks

Background: The Cactaceae is a diverse and conspicuous Neotropical family that has evolved a wide variety of adaptations during co-evolution with their interacting species. Recent research has indicated complex ecological and evolutionary interactions involving cacti and other organisms. Aims: We reviewed four studies involving cacti that have important implications for our understanding of the evolution of life traits and maintenance of cactus diversity. Also, these studies illustrate how the modern theoretical background of the ecology and evolution of species interactions is influencing the research in Cactaceae. Methods: The studies showed here are (1) the evolutionary ecology of a mistletoe-cactus parasitism in central Chile, (2) the effect of an exotic grass on the demography of a threatened cactus in Puerto Rico, (3) the herpetochory in a tropical genus of cacti in Venezuela, and (4) the role of abiotic and biotic factors on the floral morphology in globose cacti species in northern Chile. Results: The parasitic interaction between the mistletoe and a columnar cactus highlights the importance of spine length as a defensive co-evolving trait. Reproductive success in the endemic cactus in Puerto Rico was depressed by the presence of the exotic grass. Lizards actively fed on fruits of a tropical group of cacti, increasing the germination percentages of seeds. Climatic gradients might induce morphological change in the flowers of Mediterranean cactus species. Conclusions: Interactions involving cacti reflect a complex scenario of ecological and evolutionary processes which may account for several patterns of the diversity of Cactaceae. In this sense, to enhance the on-going research, we emphasise the necessity of the development of a cactus interaction database; the assessment of detrimental effects of invasive species on cactus diversity; and the quantification of multi-species interactions.

Climatic niche conservatism and biogeographical non-equilibrium in Eschscholzia californica (Papaveraceae), an invasive plant in the Chilean Mediterranean region.

Species climate requirements are useful for predicting their geographic distribution. It is often assumed that the niche requirements for invasive plants are conserved during invasion, especially when the invaded regions share similar climate conditions. California and central Chile have a remarkable degree of convergence in their vegetation structure, and a similar Mediterranean climate. Such similarities make these geographic areas an interesting natural experiment for testing climatic niche dynamics and the equilibrium of invasive species in a new environment. We tested to see if the climatic niche of Eschscholzia californica is conserved in the invaded range (central Chile), and we assessed whether the invasion process has reached a biogeographical equilibrium, i.e., occupy all the suitable geographic locations that have suitable conditions under native niche requirements. We compared the climatic niche in the native and invaded ranges as well as the projected potential geographic distribution in the invaded range. In order to compare climatic niches, we conducted a Principal Component Analysis (PCA) and Species Distribution Models (SDMs), to estimate E. californicas potential geographic distribution. We also used SDMs to predict altitudinal distribution limits in central Chile. Our results indicated that the climatic niche occupied by E. californica in the invaded range is firmly conserved, occupying a subset of the native climatic niche but leaving a substantial fraction of it unfilled. Comparisons of projected SDMs for central Chile indicate a similarity, yet the projection from native range predicted a larger geographic distribution in central Chile compared to the prediction of the model constructed for central Chile. The projected niche occupancy profile from California predicted a higher mean elevation than that projected from central Chile. We concluded that the invasion process of E. californica in central Chile is consistent with climatic niche conservatism but there is potential for further expansion in Chile.

Explicitly Task Oriented Probabilistic Active Vision for a Mobile Robot

A mobile robot has always uncertainty about the world model. Reducing this uncertainty is very hard because there is a huge amount of information and the robot must focus on the most relevant one. The selection of the most relevant information must be based on the task the robot is executing, but there could be several sources of information where the robot would like to focus on. This is also true in robot soccer where the robot must pay attention to landmarks in order to self-localize and to the ball and robots in order to follow the status of the game. In the presented work, an explicitly task oriented probabilistic active vision system is proposed. The system tries to minimize the most relevant components of the uncertainty for the task that is been performed and it is explicitly task oriented in the sense that it explicitly considers a task specific value function. As a result, the system estimates the convenience of looking towards each of the available objects. As a test-bed for the presented active vision approach, we selected a robot soccer attention problem: goal covering by a goalie player.

An integrative approach to understanding the evolution and diversity of Copiapoa (Cactaceae), a threatened endemic Chilean genus from the Atacama Desert

PREMISE OF THE STUDY Species of the endemic Chilean cactus genus Copiapoa have cylindrical or (sub)globose stems that are solitary or form (large) clusters and typically yellow flowers. Many species are threatened with extinction. Despite being icons of the Atacama Desert and well loved by cactus enthusiasts, the evolution and diversity of Copiapoa has not yet been studied using a molecular approach. METHODS Sequence data of three plastid DNA markers (rpl32-trnL, trnH-psbA, ycf1) of 39 Copiapoa taxa were analyzed using maximum likelihood and Bayesian inference approaches. Species distributions were modeled based on geo-referenced localities and climatic data. Evolution of character states of four characters (root morphology, stem branching, stem shape, and stem diameter) as well as ancestral areas were reconstructed using a Bayesian and maximum likelihood framework, respectively. KEY RESULTS Clades of species are revealed. Though 32 morphologically defined species can be recognized, genetic diversity between some species and infraspecific taxa is too low to delimit their boundaries using plastid DNA markers. Recovered relationships are often supported by morphological and biogeographical patterns. The origin of Copiapoa likely lies between southern Peru and the extreme north of Chile. The Copiapó Valley limited colonization between two biogeographical areas. CONCLUSIONS Copiapoa is here defined to include 32 species and five heterotypic subspecies. Thirty species are classified into four sections and two subsections, while two species remain unplaced. A better understanding of evolution and diversity of Copiapoa will allow allocating conservation resources to the most threatened lineages and focusing conservation action on real biodiversity.

Bayesian Spatiotemporal Context Integration Sources in Robot Vision Systems

Having as a main motivation the development of robust and high performing robot vision systems that can operate in dynamic environments, we propose a bayesian spatiotemporal context-based vision system for a mobile robot with a mobile camera, which uses three different context-coherence instances: current frame coherence, last frame coherence and high level tracking coherence (coherence with tracked objects). We choose as a first application for this vision system, the detection of static objects in the RoboCup Standard Platform League domain. The system has been validated using real video sequences and has presented satisfactory results. A relevant conclusion is that the last frame coherence appears to be not very important in the tested cases, while the coherence with the tracked objects appears to be the most important context level considered.

Landmark-Based Histograms of Oriented Gradients for Facial Emotion Recognition

The automatic recognition of human emotions is used to support several computing paradigms, like affective, positive and pervasive computing. Histograms of oriented gradients HOG have been successfully used with such a purpose, by processing facial images. However, the results of using HOG vary depending on the position of the facial components in the image used as input. This paper presents an extension to the HOG method, which was named Landmark-based Histograms of Oriented Gradients LaHOG, that not only calculates HOG blocks in the whole face, but also in specific positions around selected facial landmarks. In this sense, the new method is more robust than its predecessor. In order to evaluate the capabilities and limitations of this proposal, we used it to recognize emotions in face images from the FACES database. In such a process we used two classification strategies: support vector machines and logistic regression. The results show that the extended method significantly surpasses the performance of HOG in the tested database.

A portable ground-truth system based on a laser sensor

State estimation is of crucial importance to mobile robotics since it determines in a great measure its ability to model the world from noisy observations. In order to quantitatively evaluate state-estimation methods, the availability of ground-truth data is essential since it provides a target that the result of the state-estimation methods should approximate. Most of the reported ground-truth systems require a complex assembly which limit their applicability and make their set-up long and complicated. Furthermore, they often require a long calibration procedure. Additionally, they do not present measures of their accuracy. This paper proposes a portable laser-based ground-truth system. The proposed system can be easily ported from one environment to other and requires almost no calibration. Quantitative results are presented with the purpose of encouraging future comparisons among different groundtruth systems. The presented method has shown to be accurate enough to evaluate state-estimation methods and works in real time.