A Method for Detecting Population Genetic Structure in Diverse, High Gene-Flow Species

Detecting small amounts of genetic subdivision across geographic space remains a persistent challenge. Often a failure to detect genetic structure is mistaken for evidence of panmixia, when more powerful statistical tests may uncover evidence for subtle geographic differentiation. Such slight subdivision can be demographically and evolutionarily important as well as being critical for management decisions. We introduce here a method, called spatial analysis of shared alleles (SAShA), that detects geographically restricted alleles by comparing the spatial arrangement of allelic co-occurrences with the expectation under panmixia. The approach is allele-based and spatially explicit, eliminating the loss of statistical power that can occur with user-defined populations and statistical averaging within populations. Using simulated data sets generated under a stepping-stone model of gene flow, we show that this method outperforms spatial autocorrelation (SA) and UST under common real-world conditions: at relatively high migration rates when diversity is moderate or high, especially when sampling is poor. We then use this method to show clear differences in the genetic patterns of 2 nearshore Pacific mollusks, Tegula funebralis (5 Chlorostoma funebralis) and Katharina tunicata, whose overall patterns of within-species differentiation are similar according to traditional population genetics analyses. SAShA meaningfully complements UST/FST, SA, and other existing geographic genetic analyses and is especially appropriate for evaluating species with high gene flow and subtle genetic differentiation.

Geographic information system-based decision support for soil conservation planning in Tajikistan

Soil erosion on sloping agricultural land poses a serious problem for the environment, as well as for production. In areas with highly erodible soils, such as those in loess zones, application of soil and water conservation measures is crucial to sustain agricultural yields and to prevent or reduce land degradation. The present study, carried out in Faizabad, Tajikistan, was designed to evaluate the potential of local conservation measures on cropland using a spatial modelling approach to provide decision-making support for the planning of spatially explicit sustainable land use. A sampling design to support comparative analysis between well-conserved units and other field units was established in order to estimate factors that determine water erosion, according to the Revised Universal Soil Loss Equation (RUSLE). Such factor-based approaches allow ready application using a geographic information system (GIS) and facilitate straightforward scenario modelling in areas with limited data resources. The study showed first that assessment of erosion and conservation in an area with inhomogeneous vegetation cover requires the integration of plot-based cover. Plot-based vegetation cover can be effectively derived from high-resolution satellite imagery, providing a useful basis for plot-wise conservation planning. Furthermore, thorough field assessments showed that 25.7% of current total cropland is covered by conservation measures (terracing, agroforestry and perennial herbaceous fodder). Assessment of the effectiveness of these local measures, combined with the RUSLE calculations, revealed that current average soil loss could be reduced through low-cost measures such as contouring (by 11%), fodder plants (by 16%), and drainage ditches (by 53%). More expensive measures such as terracing and agroforestry can reduce erosion by as much as 63% (for agroforestry) and 93% (for agroforestry combined with terracing). Indeed, scenario runs for different levels of tolerable erosion rates showed that more cost-intensive and technologically advanced measures would lead to greater reduction of soil loss. However, given economic conditions in Tajikistan, it seems advisable to support the spread of low-cost and labourextensive measures.

Potential drought stress in a Swiss mountain catchment-Ensemble forecasting of high mountain soil moisture reveals a drastic decrease, despite major uncertainties

Climate change is expected to profoundly influence the hydrosphere of mountain ecosystems. The focus of current process-based research is centered on the reaction of glaciers and runoff to climate change; spatially explicit impacts on soil moisture remain widely neglected. We spatio-temporally analyzed the impact of the climate on soil moisture in a mesoscale high mountain catchment to facilitate the development of mitigation and adaptation strategies at the level of vegetation patterns. Two regional climate models were downscaled using three different approaches (statistical downscaling, delta change, and direct use) to drive a hydrological model (WaSiM-ETH) for reference and scenario period (1960–1990 and 2070–2100), resulting in an ensemble forecast of six members. For all ensembles members we found large changes in temperature, resulting in decreasing snow and ice storage and earlier runoff, but only small changes in evapotranspiration. The occurrence of downscaled dry spells was found to fluctuate greatly, causing soil moisture depletion and drought stress potential to show high variability in both space and time. In general, the choice of the downscaling approach had a stronger influence on the results than the applied regional climate model. All of the results indicate that summer soil moisture decreases, which leads to more frequent declines below a critical soil moisture level and an advanced evapotranspiration deficit. Forests up to an elevation of 1800 m a.s.l. are likely to be threatened the most, while alpine areas and most pastures remain nearly unaffected. Nevertheless, the ensemble variability was found to be extremely high and should be interpreted as a bandwidth of possible future drought stress situations.

Dynamics of Shifting Cultivation Landscapes in Northern Lao PDR Between 2000 and 2009 Based on an Analysis of MODIS Time Series and Landsat Images

The rotational nature of shifting cultivation poses several challenges to its detection by remote sensing. Consequently, there is a lack of spatial data on the dynamics of shifting cultivation landscapes on a regional, i.e. sub-national, or national level. We present an approach based on a time series of Landsat and MODIS data and landscape metrics to delineate the dynamics of shifting cultivation landscapes. Our results reveal that shifting cultivation is a land use system still widely and dynamically utilized in northern Laos. While there is an overall reduction in the areas dominated by shifting cultivation, some regions also show an expansion. A review of relevant reports and articles indicates that policies tend to lead to a reduction while market forces can result in both expansion and reduction. For a better understanding of the different factors affecting shifting cultivation landscapes in Laos, further research should focus on spatially explicit analyses.

Golden-winged Warbler habitat model validation for northern Wisconsin and central Minnesota

Between 1966 and 2003, the Golden-winged Warbler (Vermivora chrysoptera) experienced declines of 3.4% per year in large parts of the breeding range and has been identified by Partners in Flight as one of 28 land birds requiring expedient action to prevent its continued decline. It is currently being considered for listing under the Endangered Species Act. A major step in advancing our understanding of the status and habitat preferences of Golden-winged Warbler populations in the Upper Midwest was initiated by the publication of new predictive spatially explicit Golden-winged Warbler habitat models for the northern Midwest. Here, I use original data on observed Golden-winged Warbler abundances in Wisconsin and Minnesota to compare two population models: the hierarchical spatial count (HSC) model with the Habitat Suitability Index (HSI) model. I assessed how well the field data compared to the model predictions and found that within Wisconsin, the HSC model performed slightly better than the HSI model whereas both models performed relatively equally in Minnesota. For the HSC model, I found a 10% error of commission in Wisconsin and a 24.2% error of commission for Minnesota. Similarly, the HSI model has a 23% error of commission in Minnesota; in Wisconsin due to limited areas where the HSI model predicted absences, there was incomplete data and I was unable to determine the error of commission for the HSI model. These are sites where the model predicted presences and the Golden-winged Warbler did not occur. To compare predicted abundance from the two models, a 3x3 contingency table was used. I found that when overlapped, the models do not complement one another in identifying Golden-winged Warbler presences. To calculate discrepancy between the models, the error of commission shows that the HSI model has only a 6.8% chance of correctly classifying absences in the HSC model. The HSC model has only 3.3% chance of correctly classifying absences in the HSI model. These findings highlight the importance of grasses for nesting, shrubs used for cover and foraging, and trees for song perches and foraging as key habitat characteristics for breeding territory occupancy by singing males.

Does Sex Speed Up Evolutionary Rate and Increase Biodiversity?

Most empirical and theoretical studies have shown that sex increases the rate of evolution, although evidence of sex constraining genomic and epigenetic variation and slowing down evolution also exists. Faster rates with sex have been attributed to new gene combinations, removal of deleterious mutations, and adaptation to heterogeneous environments. Slower rates with sex have been attributed to removal of major genetic rearrangements, the cost of finding a mate, vulnerability to predation, and exposure to sexually transmitted diseases. Whether sex speeds or slows evolution, the connection between reproductive mode, the evolutionary rate, and species diversity remains largely unexplored. Here we present a spatially explicit model of ecological and evolutionary dynamics based on DNA sequence change to study the connection between mutation, speciation, and the resulting biodiversity in sexual and asexual populations. We show that faster speciation can decrease the abundance of newly formed species and thus decrease long-term biodiversity. In this way, sex can reduce diversity relative to asexual populations, because it leads to a higher rate of production of new species, but with lower abundances. Our results show that reproductive mode and the mechanisms underlying it can alter the link between mutation, evolutionary rate, speciation and biodiversity and we suggest that a high rate of evolution may not be required to yield high biodiversity.

Chapter Six – Individual Trait Variation and Diversity in Food Webs

In recent years, there has been a renewed interest in the ecological consequences of individual trait variation within populations. Given that individual variability arises from evolutionary dynamics, to fully understand eco-evolutionary feedback loops, we need to pay special attention to how standing trait variability affects ecological dynamics. There is mounting empirical evidence that intra-specific phenotypic variation can exceed species-level means, but theoretical models of multi-trophic species coexistence typically neglect individual-level trait variability. What is needed are multispecies datasets that are resolved at the individual level that can be used to discriminate among alternative models of resource selection and species coexistence in food webs. Here, using one the largest individual-based datasets of a food web compiled to date, along with an individual trait-based stochastic model that incorporates Approximate Bayesian computation methods, we document intra-population variation in the strength of prey selection by different classes or predator phenotypes which could potentially alter the diversity and coexistence patterns of food webs. In particular, we found that strongly connected individual predators preferentially consumed common prey, whereas weakly connected predators preferentially selected rare prey. Such patterns suggest that food web diversity may be governed by the distribution of predator connectivity and individual trait variation in prey selection. We discuss the consequences of intra-specific variation in prey selection to assess fitness differences among predator classes (or phenotypes) and track longer term food web patterns of coexistence accounting for several phenotypes within each prey and predator species.

A systematized workflow for assessing land resources using readily available spatial datasets

Land degradation as well as land conservation maps at a (sub-) national scale are critical for pro-ject planning for sustainable land management. It has long been recognized that online accessible and low-cost raster data sets (e.g. Landsat imagery, SRTM-DEM’s) provide a readily available basis for land resource assessments for developing countries. However, choice of spatial, tempo-ral and spectral resolution of such data is often limited. Furthermore, while local expert knowl-edge on land degradation processes is abundant, difficulties are often encountered when linking existing knowledge with modern approaches including GIS and RS. The aim of this study was to develop an easily applicable, standardized workflow for preliminary spatial assessments of land degradation and conservation, which also allows the integration of existing expert knowledge. The core of the developed method consists of a workflow for rule-based land resource assess-ment. In a systematic way, this workflow leads from predefined land degradation and conserva-tion classes to field indicators, to suitable spatial proxy data, and finally to a set of rules for clas-sification of spatial datasets. Pre-conditions are used to narrow the area of interest. Decision tree models are used for integrating the different rules. It can be concluded that the workflow presented assists experts from different disciplines in col-laboration GIS/RS specialists in establishing a preliminary model for assessing land degradation and conservation in a spatially explicit manner. The workflow provides support when linking field indicators and spatial datasets, and when determining field indicators for groundtruthing.

Distance from Sub-Saharan Africa Predicts Mutational Load in Diverse Human Genomes

The Out-of-Africa (OOA) dispersal ∼50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.

An examination of the relationship between maternal and neighborhood-level characteristics and intrauterine growth retardation in Harris County, Texas, 1999--2001

The persistence of low birth weight and intrauterine growth retardation (IUGR) in the United States has puzzled researchers for decades. Much of the work that has been conducted on adverse birth outcomes has focused on low birth weight in general and not on IUGR. Studies that have examined IUGR specifically thus far have focused primarily on individual-level maternal risk factors. These risk factors have only been able to explain a small portion of the variance in IUGR. Therefore, recent work has begun to focus on community-level risk factors in addition to the individual-level maternal characteristics. This study uses Social Ecology to examine the relationship of individual and community-level risk factors and IUGR. Logistic regression was used to establish an individual-level model based on 155, 856 births recorded in Harris County, TX during 1999-2001. IUGR was characterized using a fetal growth ratio method with race/ethnic and sex specific mean birth weights calculated from national vital records. The spatial distributions of 114,460 birth records spatially located within the City of Houston were examined using choropleth, probability and density maps. Census tracts with higher than expected rates of IUGR and high levels of neighborhood disadvantage were highlighted. Neighborhood disadvantage was constructed using socioeconomic variables from the 2000 U.S. Census. Factor analysis was used to create a unified single measure. Lastly, a random coefficients model was used to examine the relationship between varying levels of community disadvantage, given the set of individual-level risk factors for 152,997 birth records spatially located within Harris County, TX. Neighborhood disadvantage was measured using three different indices adapted from previous work. The findings show that pregnancy-induced hypertension, previous preterm infant, tobacco use and insufficient weight gain have the highest association with IUGR. Neighborhood disadvantage only slightly further increases the risk of IUGR (OR 1.12 to 1.23). Although community level disadvantage only helped to explain a small proportion of the variance of IUGR, it did have a significant impact. This finding suggests that community level risk factors should be included in future work with IUGR and that more work needs to be conducted. ^

World distribution of land cover changes, model in NetCDF format

The role of Pre- and Protohistoric anthropogenic land cover changes needs to be quantified i) to establish a baseline for comparison with current human impact on the environment and ii) to separate it from naturally occurring changes in our environment. Results are presented from the simple, adaptation-driven, spatially explicit Global Land Use and technological Evolution Simulator (GLUES) for pre-Bronze age demographic, technological and economic change. Using scaling parameters from the History Database of the Global Environment as well as GLUES-simulated population density and subsistence style, the land requirement for growing crops is estimated. The intrusion of cropland into potentially forested areas is translated into carbon loss due to deforestation with the dynamic global vegetation model VECODE. The land demand in important Prehistoric growth areas - converted from mostly forested areas - led to large-scale regional (country size) deforestation of up to 11% of the potential forest. In total, 29 Gt carbon were lost from global forests between 10 000 BC and 2000 BC and were replaced by crops; this value is consistent with other estimates of Prehistoric deforestation. The generation of realistic (agri-)cultural development trajectories at a regional resolution is a major strength of GLUES. Most of the pre-Bronze age deforestation is simulated in a broad farming belt from Central Europe via India to China. Regional carbon loss is, e.g., 5 Gt in Europe and the Mediterranean, 6 Gt on the Indian subcontinent, 18 Gt in East and Southeast Asia, or 2.3 Gt in subsaharan Africa.

HF spectrum activity prediction model based on HMM for cognitive radio applications

Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.

Flood frequency analysis by a bivariate model based on copulas

La adecuada estimación de avenidas de diseño asociadas a altos periodos de retorno es necesaria para el diseño y gestión de estructuras hidráulicas como presas. En la práctica, la estimación de estos cuantiles se realiza normalmente a través de análisis de frecuencia univariados, basados en su mayoría en el estudio de caudales punta. Sin embargo, la naturaleza de las avenidas es multivariada, siendo esencial tener en cuenta características representativas de las avenidas, tales como caudal punta, volumen y duración del hidrograma, con el fin de llevar a cabo un análisis apropiado; especialmente cuando el caudal de entrada se transforma en un caudal de salida diferente durante el proceso de laminación en un embalse o llanura de inundación. Los análisis de frecuencia de avenidas multivariados han sido tradicionalmente llevados a cabo mediante el uso de distribuciones bivariadas estándar con el fin de modelar variables correlacionadas. Sin embargo, su uso conlleva limitaciones como la necesidad de usar el mismo tipo de distribuciones marginales para todas las variables y la existencia de una relación de dependencia lineal entre ellas. Recientemente, el uso de cópulas se ha extendido en hidrología debido a sus beneficios en relación al contexto multivariado, permitiendo superar los inconvenientes de las técnicas tradicionales. Una copula es una función que representa la estructura de dependencia de las variables de estudio, y permite obtener la distribución de frecuencia multivariada de dichas variables mediante sus distribuciones marginales, sin importar el tipo de distribución marginal utilizada. La estimación de periodos de retorno multivariados, y por lo tanto, de cuantiles multivariados, también se facilita debido a la manera en la que las cópulas están formuladas. La presente tesis doctoral busca proporcionar metodologías que mejoren las técnicas tradicionales usadas por profesionales para estimar cuantiles de avenida más adecuados para el diseño y la gestión de presas, así como para la evaluación del riesgo de avenida, mediante análisis de frecuencia de avenidas bivariados basados en cópulas. Las variables consideradas para ello son el caudal punta y el volumen del hidrograma. Con el objetivo de llevar a cabo un estudio completo, la presente investigación abarca: (i) el análisis de frecuencia de avenidas local bivariado centrado en examinar y comparar los periodos de retorno teóricos basados en la probabilidad natural de ocurrencia de una avenida, con el periodo de retorno asociado al riesgo de sobrevertido de la presa bajo análisis, con el fin de proporcionar cuantiles en una estación de aforo determinada; (ii) la extensión del enfoque local al regional, proporcionando un procedimiento completo para llevar a cabo un análisis de frecuencia de avenidas regional bivariado para proporcionar cuantiles en estaciones sin aforar o para mejorar la estimación de dichos cuantiles en estaciones aforadas; (iii) el uso de cópulas para investigar tendencias bivariadas en avenidas debido al aumento de los niveles de urbanización en una cuenca; y (iv) la extensión de series de avenida observadas mediante la combinación de los beneficios de un modelo basado en cópulas y de un modelo hidrometeorológico. Accurate design flood estimates associated with high return periods are necessary to design and manage hydraulic structures such as dams. In practice, the estimate of such quantiles is usually done via univariate flood frequency analyses, mostly based on the study of peak flows. Nevertheless, the nature of floods is multivariate, being essential to consider representative flood characteristics, such as flood peak, hydrograph volume and hydrograph duration to carry out an appropriate analysis; especially when the inflow peak is transformed into a different outflow peak during the routing process in a reservoir or floodplain. Multivariate flood frequency analyses have been traditionally performed by using standard bivariate distributions to model correlated variables, yet they entail some shortcomings such as the need of using the same kind of marginal distribution for all variables and the assumption of a linear dependence relation between them. Recently, the use of copulas has been extended in hydrology because of their benefits regarding dealing with the multivariate context, as they overcome the drawbacks of the traditional approach. A copula is a function that represents the dependence structure of the studied variables, and allows obtaining the multivariate frequency distribution of them by using their marginal distributions, regardless of the kind of marginal distributions considered. The estimate of multivariate return periods, and therefore multivariate quantiles, is also facilitated by the way in which copulas are formulated. The present doctoral thesis seeks to provide methodologies that improve traditional techniques used by practitioners, in order to estimate more appropriate flood quantiles for dam design, dam management and flood risk assessment, through bivariate flood frequency analyses based on the copula approach. The flood variables considered for that goal are peak flow and hydrograph volume. In order to accomplish a complete study, the present research addresses: (i) a bivariate local flood frequency analysis focused on examining and comparing theoretical return periods based on the natural probability of occurrence of a flood, with the return period associated with the risk of dam overtopping, to estimate quantiles at a given gauged site; (ii) the extension of the local to the regional approach, supplying a complete procedure for performing a bivariate regional flood frequency analysis to either estimate quantiles at ungauged sites or improve at-site estimates at gauged sites; (iii) the use of copulas to investigate bivariate flood trends due to increasing urbanisation levels in a catchment; and (iv) the extension of observed flood series by combining the benefits of a copula-based model and a hydro-meteorological model.

Deforestación y Pérdida de hábitat en Bosques de montaña en la Cuenca alta del Río Zamora (Loja, Ecuador)

Los bosques húmedos de montaña se encuentran reconocidos como uno de los ecosistemas más amenazados en el mundo, llegando inclusive a ser considerado como un “hotspot” por su alta diversidad y endemismo. La acelerada pérdida de cobertura vegetal de estos bosques ha ocasionado que, en la actualidad, se encuentren restringidos a una pequeña fracción de su área de distribución histórica. Pese a esto, los estudios realizados sobre cual es efecto de la deforestación, fragmentación, cambios de uso de suelo y su efecto en las comunidades de plantas presentes en este tipo de vegetación aún son muy escuetos, en comparación a los realizados con sus similares amazónicos. En este trabajo, el cual se encuentra dividido en seis capítulos, abordaremos los siguientes objetivos: a) Comprender cuál es la dinámica que han seguido los diferentes tipos de bosques montanos andinos de la cuenca del Rio Zamora, Sur de Ecuador durante entre 1976 y 2002. b) Proveer de evidencia de las tasas de deforestación y fragmentación de todos los tipos diferentes de bosques montanos andinos presentes en la cuenca del Rio Zamora, Sur de Ecuador entre 1976 y 2002. c) Determinar qué factores inducen a la fragmentación de bosques de montaña en la cuenca alta del río Zamora entre 1976 y 2002. d) Determinar cuáles son y cómo afectan los factores ambientales y socioeconómicos a la dinámica de la deforestación y regeneración (pérdida y recuperación del hábitat) sufrida por los bosques de montaña dentro de la zona de estudio y e) Determinar si la deforestación y fragmentación actúan sobre la diversidad y estructura de las comunidades de tres tipos de organismos (comunidades de árboles, comunidades de líquenes epífitos y comunidades de hepáticas epífitas). Este estudio se centró en el cuenca alta del río Zamora, localizada al sur de Ecuador entre las coordenadas 3º 00´ 53” a 4º 20´ 24.65” de latitud sur y 79º 49´58” a 78º 35´ 38” de longitud oeste, que cubre alrededor de 4300 km2 de territorio situado entre las capitales de las provincias de Loja y Zamora-Chinchipe. Con objeto de predecir la dinámica futura de la deforestación en la región de Loja y cómo se verán afectados los diferentes tipos de hábitat, así como para detectar los factores que más influyen en dicha dinámica, se han construido modelos basados en la historia de la deforestación derivados de fotografías aéreas e imágenes satelitales de tres fechas (1976, 1989 y 2002). La cuantificación de la deforestación se realizó mediante la tasa de interés compuesto y para la caracterización de la configuración espacial de los fragmentos de bosque nativo se calcularon índices de paisaje los cuales fueron calculados utilizando el programa Fragstats 3.3. Se ha clasificado el recubrimiento del terreno en forestal y no forestal y se ha modelado su evolución temporal con Modelos Lineales Generalizados Mixtos (GLMM), empleando como variables explicativas tanto variables ambientales espacialmente explícitas (altitud, orientación, pendiente, etc) como antrópicas (distancia a zonas urbanizadas, deforestadas, caminos, entre otras). Para medir el efecto de la deforestación sobre las comunidades modelo (de árboles, líquenes y hepáticas) se monitorearon 11 fragmentos de vegetación de distinto tamaño: dos fragmentos de más de cien hectáreas, tres fragmentos de entre diez y noventa ha y seis fragmentos de menos de diez hectáreas. En ellos se instalaron un total de 38 transectos y 113 cuadrantes de 20 x 20 m a distancias que se alejaban progresivamente del borde en 10, 40 y 80 m. Nuestros resultados muestran una tasa media anual de deforestación del 1,16% para todo el período de estudio, que el tipo de vegetación que más alta tasa de destrucción ha sufrido, es el páramo herbáceo, con un 2,45% anual. El análisis de los patrones de fragmentación determinó un aumento en 2002 de más del doble de fragmentos presentes en 1976, lo cual se repite en el análisis del índice de densidad promedio. El índice de proximidad media entre fragmentos muestra una reducción progresiva de la continuidad de las áreas forestadas. Si bien las formas de los fragmentos se han mantenido bastante similares a lo largo del período de estudio, la conectividad entre estos ha disminuido en un 84%. Por otro lado, de nuestros análisis se desprende que las zonas con mayor probabilidad de deforestarse son aquellas que están cercanas a zonas previamente deforestadas; la cercanía a las vías también influye significativamente en la deforestación, causando un efecto directo en la composición y estructura de las comunidades estudiadas, que en el caso de los árboles viene mediado por el tamaño del fragmento y en el caso del componente epífito (hepáticas y líquenes), viene mediado tanto por el tamaño del fragmento como por la distancia al borde del mismo. Se concluye la posibilidad de que, de mantenerse esta tendencia, este tipo de bosques desaparecerá en corto tiempo y los servicios ecosistémicos que prestan, se verán seriamente comprometidos. ABSTRACT Mountain rainforests are recognized as one of the most threatened ecosystems in the world, and have even come to be considered as a “hotspot” due to their high degree of diversity and endemism. The accelerated loss of plant cover of these forests has caused them to be restricted today to a small fraction of their area of historic distribution. In spite of this, studies done on the effect of deforestation, fragmentation, changes in soil use and their effect on the plant communities present in this type of vegetation are very brief compared to those done on their analogues in the Amazon region. In this study, which is divided into six chapters, we will address the following objectives: a) To understand what the dynamic followed by the different types of Andean mountain forests in the Zamora River watershed of southern Ecuador has been between 1976 and 2002. b) To provide evidence of the rates of deforestation and fragmentation of all the different types of Andean mountain forests existing in the upper watershed of the Zamora River between 1976 and 2002. c) To determine the factors that induces fragmentation of all different types of Andean mountain forests existing in the upper watershed of the Zamora River between 1976 and 2002. d) To determine what the environmental and anthropogenic factors are driving the dynamic of deforestation and regeneration (loss and recuperation of the habitat) suffered by the mountain forests in the area of the study and e) To determine if the deforestation and fragmentation act upon the diversity and structure of three model communities: trees, epiphytic lichens and epiphytic liverworts. This study is centered on the upper Zamora River watershed, located in southern Ecuador between 3º 00´ 53” and 4º 20´ 24.65 south latitude and 79º 49´ 58” to 78º 35´ 38” west longitude, and covers around 4,300 km2 of territory located between Loja and Zamora-Chinchipe provinces. For the purpose of predicting the future dynamic of deforestation in the Loja region and how different types of habitats will be affected, as well as detecting the environmental and socioeconomic factors that influence landscape dynamics, models were constructed based on deforestation history, derived from aerial photographs and satellite images for three dates (1976, 1989 and 2002). Quantifying the deforestation was done using the compound interest rate; to characterize the spatial configuration of fragments of native forest, landscape indices were calculated with Fragstats 3.3 program. Land cover was classified as forested and not forested and its evolution over time was modeled with Generalized Linear Mixed Models (GLMM), using spatially explicit environmental variables (altitude, orientation, slope, etc.) as well as anthropic variables (distance to urbanized, deforested areas and roads, among others) as explanatory variables. To measure the effects of fragmentation on three types of model communities (forest trees and epiphytic lichen and liverworts), 11 vegetation fragments of different sizes were monitored: two fragments of more than one hundred hectares, three fragments of between ten and ninety ha and six fragments of fewer than ten hectares . In these fragments, a total of 38 transects and 113 20 x 20 m quadrats were installed at distances that progressively moved away from the edge of the fragment by 10, 40 and 80 m. Our results show an average annual rate of deforestation of 1.16% for the entire period of the study, and that the type of vegetation that suffered the highest rate of destruction was grassy paramo, with an annual rate of 2.45%. The analysis of fragmentation patterns determined the number of fragments in 2002 more than doubled the number of fragments present in 1976, and the same occurred for the average density index. The variation of the average proximity index among fragments showed a progressive reduction of the continuity of forested areas. Although fragment shapes have remained quite similar over the period of the study, connectivity among them has diminished by 84%. On the other hand, it emerged from our analysis that the areas of greatest probability of deforestation were those that are close to previously deforested areas; proximity to roads also significantly favored the deforestation causing a direct effect on the composition of our model communities, that in the case of forest trees is determined by the size of the fragment, and in the case of the epiphyte communities (liverworts and lichens), is determined, by the size of the fragment as well as the distance to edge. A subject under discussion is the possibility that if this tendency continues, this type of forest will disappear in a short time, and the ecological services it provides, will be seriously endangered.