Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Forest connectivity restoration through reforestation: an integrated methodology for prioritizing agricultural lands and selecting reforestation species

Forest connectivity restoration is a major goal in natural resource planning. Given the high amount of abandoned cultivated lands, setting efficient methods for the reforestation of agricultural lands offers a good opportunity to face this issue. However, reforestations must be carefully planned, which poses two main challenges. In first place, to determine those agricultural lands that, once reforested, would meet more effectively the planning goals. As a further step, in order to grant the success of the activity, it is fairly advisable to select those tree species that are more adapted to each particular environment. Here we intend to give response to both requirements by proposing a sequential and integrated methodology that has been implemented in two Spanish forest districts, which are formed by several landscape types that were previously defined and characterized. Using the software Conefor Sensinode, a powerful tool for quantifying habitat availability that is based on graph theory concepts, we determined the landscapes where forest planning should have connectivity as a major concern and, afterwards, we detected the agricultural patches that would contribute most to enhance connectivity if they were reforested. The subsequent reforestation species assessment was performed within these priority patches. Using penalized logistic regressions we fitted ecological niche models for the Spanish native tree species. The models were trained with species distribution data from the Spanish Forest Map and used climatic and lithological variables as predictors. Model predictions were used to build ordered lists of suitable species for each priority patch. The lists include dominant and non dominant tree species and allow adding biodiversity goals to the reforestation planning. The result of this combined methodology is a map of agricultural patches that would contribute most to uphold forest connectivity if they were reforested and a list of suitable tree species for each patch ordered by occurrence probability. Therefore the proposed methodology may be useful for suitable and efficient forest planning and landscape designing.

Bases metodológicas para un sistema de apoyo a la selección de especies en la restauración de la vegetación

RESUMEN El apoyo a la selección de especies a la restauración de la vegetación en España en los últimos 40 años se ha basado fundamentalmente en modelos de distribución de especies, también llamados modelos de nicho ecológico, que estiman la probabilidad de presencia de las especies en función de las condiciones del medio físico (clima, suelo, etc.). Con esta tesis se ha intentado contribuir a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodológicas adaptadas a los datos disponibles actualmente en España y enfocadas al uso de los modelos en la selección de especies. No siempre se dispone de datos a una resolución espacial adecuada para la escala de los proyectos de restauración de la vegetación. Sin embrago es habitual contar con datos de baja resolución espacial para casi todas las especies vegetales presentes en España. Se propone un método de recalibración que actualiza un modelo de regresión logística de baja resolución espacial con una nueva muestra de alta resolución espacial. El método permite obtener predicciones de calidad aceptable con muestras relativamente pequeñas (25 presencias de la especie) frente a las muestras mucho mayores (más de 100 presencias) que requería una estrategia de modelización convencional que no usara el modelo previo. La selección del método estadístico puede influir decisivamente en la capacidad predictiva de los modelos y por esa razón la comparación de métodos ha recibido mucha atención en la última década. Los estudios previos consideraban a la regresión logística como un método inferior a técnicas más modernas como las de máxima entropía. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de máxima entropía incluyen técnicas de regularización y la versión de la regresión logística usada en las comparaciones no. Una vez incorporada la regularización a la regresión logística usando penalización, las diferencias en cuanto a capacidad predictiva desaparecen. La regresión logística penalizada es, por tanto, una alternativa más para el ajuste de modelos de distribución de especies y está a la altura de los métodos modernos con mejor capacidad predictiva como los de máxima entropía. A menudo, los modelos de distribución de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades físicas o químicas. La incorporación de datos de baja resolución espacial proveniente de mapas de suelo nacionales o continentales podría ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribución de especies de alta resolución espacial mejoran de forma ligera pero estadísticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resolución espacial. La validación es una de las etapas fundamentales del desarrollo de cualquier modelo empírico como los modelos de distribución de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluación no responde a una cuestión clave en la restauración de la vegetación ¿cuales son las n especies más idóneas para el lugar a restaurar? Se ha propuesto un método de evaluación de modelos adaptado a esta cuestión que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El método se ha aplicado con éxito a la validación de 188 modelos de distribución de especies leñosas orientados a la selección de especies para la restauración de la vegetación en España. Las mejoras metodológicas propuestas permiten mejorar la capacidad predictiva de los modelos de distribución de especies aplicados a la selección de especies en la restauración de la vegetación y también permiten ampliar el número de especies para las que se puede contar con un modelo que apoye la toma de decisiones. SUMMARY During the last 40 years, decision support tools for plant species selection in ecological restoration in Spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.g., climate, soil). In this Thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in Spain and focusing in the application of the models to selection of species for ecological restoration. Fine grained species distribution data are required to train models to be used at the scale of the ecological restoration projects, but this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in Spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data. The choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this Thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions. Usually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this Thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps. Model validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.e., comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in Spain. The proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.

Natural regeneration in mediterranean mixed forests: effect of environmental conditions on the physiological optimum niche of the species = Regeneración natural en masas mixtas mediterráneas: efecto de las condiciones ambientales en el nicho óptimo fisiológico de las especies

Los montes Mediterráneos han experimentado múltiples cambios en las últimas décadas (tanto en clima como en usos), lo que ha conducido a variaciones en la distribución de especies. El aumento previsto de las temperaturas medias junto con la mayor variabilidad intra e inter anual en cuanto a la ocurrencia de eventos extremos o disturbios naturales (como periodos prolongados de sequía, olas de frío o calor, incendios forestales o vendavales) pueden dañar significativamente al regenerado, llevándolo hasta la muerte, y jugando un papel decisivo en la composición de especies y en la dinámica del monte. La amplitud ecológica de muchas especies forestales puede verse afectada, de forma que se esperan cambios en sus nichos actuales de regeneración. Sin embargo, la migración latitudinal de las especies en busca de mejores condiciones, podría ser una explicación demasiado simplista de un proceso mucho más complejo de interacción entre la temperatura y la precipitación, que afectaría a cada especie de un modo distinto. En este sentido tanto la capacidad de adaptación al estrés ambiental de una determinada especie, así como su habilidad para competir por los recursos limitados, podría significar variaciones dentro de una comunidad. Las características fisiológicas y morfológicas propias de cada especie se encuentran fuertemente relacionadas con el lugar donde cada una puede surgir, qué especies pueden convivir y como éstas responden a las condiciones ambientales. En este sentido, el conocimiento sobre las distintas respuestas ecofisiológicas observadas ante cambios ambientales puede ser fundamentales para la predicción de variaciones en la distribución de especies, composición de la comunidad y productividad del monte ante el cambio global. En esta tesis investigamos el grado de tolerancia y sensibilidad que cada una de las tres especies de estudio, coexistentes en el interior peninsular ibérico (Pinus pinea, Quercus ilex y Juniperus oxycedrus), muestra ante los factores abióticos de estrés típicos de la región Mediterránea. Nuestro trabajo se ha basado en la definición del nicho óptimo fisiológico para el regenerado de cada especie a través de la investigación en profundidad del efecto de la sequía, la temperatura y el ambiente lumínico. Para ello, hemos desarrollado un modelo de predicción de la tasa de asimilación de carbono que nos ha permitido identificar las condiciones óptimas ambientales donde el regenerado de cada especie podría establecerse con mayor facilidad. En apoyo a este trabajo y con la idea de estudiar el efecto de la sequía a nivel de toda la planta hemos desarrollado un experimento paralelo en invernadero. Aquí se han aplicado dos regímenes hídricos para estudiar las características fisiológicas y morfológicas de cada especie, sobre todo a nivel de raíz y crecimiento del tallo, y relacionarlas con las diferentes estrategias en el uso del agua de las especies. Por último, hemos estudiado los patrones de aclimatación y desaclimatación al frio de cada especie, identificando los periodos de sensibilidad a heladas, así como cuellos de botella donde la competencia entre especies podría surgir. A pesar de que el pino piñonero ha sido la especie objeto de la gestión de estas masas durante siglos, actualmente se encuentra en la posición más desfavorable para combatir el cambio global, presentado el nicho fisiológico más estrecho de las tres especies. La encina sin embargo, ha resultado ser la especie mejor cualificada para afrontar este cambio, seguida muy de cerca por el enebro. Nuestros resultados sugieren una posible expansión en el rango de distribución de la encina, un aumento en la presencia del enebro y una disminución progresiva del pino piñonero a medio plazo en estas masas. ABSTRACT Mediterranean forests have undergone multiple changes over the last decades (in both climate and land use), which have lead to variations in the distribution of species. The expected increase in mean annual temperature together with the greater inter and intra-annual variability in extreme events and disturbances occurrence (such as prolonged drought periods, cold or heat waves, wildfires or strong winds) can significantly damage natural regeneration, up to causing death, playing a decisive role on species composition and forest dynamics. The ecological amplitude for adaptation of many species can be affected in such a way that changes in the current regeneration niches of many species are expected. However, the forecasted poleward migration of species seeking better conditions could be an oversimplification of what is a more complex phenomenon of interactions among temperature and precipitation, that would affect different species in different ways. In this regard, either the ability to adapt to environmental stresses or to compete for limited resources of a single species in a mixed forest could lead to variations within a community. The ecophysiological and morphological traits specific to each species are strongly related to the place where each species can emerge, which species can coexist, and how they respond to environmental conditions. In this regard, the understanding of the ecophysiological responses observed against changes in environmental conditions can be essential for predicting variations in species distribution, community composition, and forest productivity in the context of global change. In this thesis we investigated the degree of tolerance and sensitivity that each of the three studied species, co-occurring in central of the Iberian Peninsula (Pinus pinea, Quercus ilex and Juniperus oxycedrus), show against the typical abiotic stress factors in the Mediterranean region. Our work is based on the optimal physiological niche for regeneration of each species through in-depth research on the effect of drought, temperature and light environment. For this purpose, we developed a model to predict the carbon assimilation rate which allows us to identify the optimal environmental conditions where regeneration from each species could establish itself more easily. To obtain a better understanding about the effect of low temperature on regeneration, we studied the acclimation and deacclimation patterns to cold of each species, identifying period of frost sensitivity, as well as bottlenecks where competition between species can arise. Finally, to support our results about the effect of water availabilty, we conducted a greenhouse experiment with a view of studying the drought effect at the whole plant level. Here, two watering regimes were applied in order to study the physiological and morphological traits of each species, mainly at the level of the root system and stem growth, and so relate them to the different water use strategies of the species. Despite the fact that stone pine has been the target species for centuries, nowadays this species is in the most unfavorable position to cope with climate change. Holm oak, however, resulted the species that is best adapted to tolerate the predicted changes, followed closely by prickly juniper. Our results suggest a feasible expansion of the distribution range in holm oak, an increase in the prickly juniper presence and a progressive decreasing of stone pine presence in the medium term in these stone pine-holm oak-prickly juniper mixed forests.

Mapping species distributions : A comparison of skilled naturalist and lay citizen science recording

Acknowledgements We are grateful to Elaine O’Mahony, Imogen Pearce, Richard Comont, Anthony McCluskey and other BBCT staff for the many hours of BeeWatch species identification and for all people who submitted sightings to BeeWatch, OPAL, BWARS and the various local recording schemes and societies. We thank the NBN for allowing us to download the bumblebee records without strings attached, and the Essex, Greater London, Cumbria and Sussex based recording centres for providing records upon request. Finally, we are indebted to Tom August and two anonymous reviewers for their valuable critique on an earlier version of this work.

Description of eight new Anomala species from Costa Rica (Coleoptera: Scarabaeidae: Rutelinae)

Eight new species of Anomala from Costa Rica are described: A. arthuri new species, A. cupreovariolosa new species, A. ferrea new species, A. nigroflava new species, A. semilla new species, A. solisi new species, A. volsellata new species, A. zumbadoi new species and a distribution map of each is given. The male genitalia (aedeagus and endophallus) of the species covered are illustrated.

Description of two cryptic species of Anomala Samouelle (Coleoptera: Scarabaeidae: Rutelinae) from Costa Rica

Two new species of Anomala Samouelle from Costa Rica are described: Anomala moroni new species and A. parvaeucoma new species. Habitus, protibia, distribution map, and male genitalia (aedeagus and endophallus) of each species are illustrated. A key for the dorsally setose species from the Neotropical region is provided.

Saproxylic Beetle Assemblage Selection as Determining Factor of Species Distributional Patterns: Implications for Conservation

The knowledge of the distributional patterns of saproxylic beetles is essential for conservation biology due to the relevance of this fauna in the maintenance of ecological processes and the endangerment of species. The complex community of saproxylic beetles is shaped by different assemblages that are composed of species linked by the microhabitats they use. We evaluate how different the species distribution patterns that are obtained can be, depending on the analyzed assemblage and to what extent these can affect conservation decisions. Beetles were sampled using hollow emergence and window traps in three protected areas of the Iberian Peninsula. Species richness, composition, and diversity turnover were analyzed for each sampling method and showed high variation depending on the analyzed assemblage. Beta diversity was clearly higher among forests for the assemblage captured using window traps. This method collects flying insects from different tree microhabitats and its captures are influenced by the forest structuring. Within forests, the assemblages captured by hollow emergence traps, which collect the fauna linked to tree hollows, showed the largest turnover of species, as they are influenced by the characteristics of each cavity. Moreover, the selection of the forest showing the highest species richness strongly depended on the studied assemblage. This study demonstrates that differences in the studied assemblages (group of species co-occurring in the same habitat) can also lead to significant differences in the identified patterns of species distribution and diversity turnover. This fact will be necessary to take into consideration when making decisions about conservation and management.

Ensemble prediction distribution maps of macroalgae for current conditions and four climate change scenarios and high resultion bathymetry for Potter Cove, WAP, Antarctica

Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.

Tradeoffs of different types of species occurrence data for use in systematic conservation planning

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.

Georeferenced standardized apparent wave power along the coastline of Cabrera National Park for analysis of essential habitats of littoral species

Wind- induced exposure is one of the major forces shaping the geomorphology and biota in coastal areas. The effect of wave exposure on littoral biota is well known in marine environments (Ekebon et al., 2003; Burrows et al., 2008). In the Cabrera Archipelago National Park wave exposure has demostrated to have an effect on the spatial distribution of different stages of E.marginatus (Alvarez et al., 2010). Standarized average wave exposures during 2008 along the Cabrera Archipelago National park coast line were calculated to be applied in studies of littoral species distribution within the archipelago. Average wave exposure (or apparent wave power) was calculated for points located 50 m equidistant on the coastline following the EXA methodology (EXposure estimates for fragmented Archipelagos) (Ekebon et al., 2003). The average wave exposures were standardized from 1 to 100 (minimum and maximum in the area), showing coastal areas with different levels of mea wave exposure during the year. Input wind data (direction and intensity) from 2008 was registered at the Cabrera mooring located north of Cabrera Archipelago. Data were provided by IMEDEA (CSIC-UIB, TMMOS http://www.imedea.uib-csic.es/tmoos/boyas/). This cartography has been developed under the framework of the project EPIMHAR, funded by the National Park's Network (Spanish Ministry of Environment, Maritime and Rural Affairs, reference: 012/2007 ). Part of this work has been developed under the research programs funded by "Fons de Garantia Agrària i Pesquera de les Illes Balears (FOGAIBA)".

Ecophysiology of Adonis distorta, a high-mountain species endemic of the Central Apennines

Morphological, anatomical and physiological plant and leaf traits of A. distorta, an endemic species of the Central Apennines on the Majella Massif, growing at 2,675 m a.s.l, were analyzed. The length of the phenological cycle starts immediately after the snowmelt at the end of May, lasting 128 ± 10 days. The low A. distorta height  (Hmax= 64 ± 4 mm) and total leaf area (TLA= 38 ± 9 cm2) associated to a high leaf mass area (LMA =11.8±0.6 mg cm−2) and a relatively high leaf tissue density (LTD = 124.6±14.3 mg cm−3) seem to be adaptive traits to the stress factors of the environment where it grows. From a physiological point of view, the high A. distorta photosynthetic rates (PN =19.6 ± 2.3 µmol m−2 s−1) and total chlorophyll content (Chla+b = 0.88 ± 0.13 mg g−1) in July are justified by the favorable temperature. PN decreases by 87% in September at the beginning of plant senescence. Photosynthesis and leaf respiration (RD) variations allow A. distorta to maintain a positive carbon balance during the growing season becoming indicative of the efficiency of plant carbon use. The results could be an important tool for conservation programmes of the A. distorta wild populations.

fuzzySim: Fuzzy similarity in species distributions

fuzzySim is an R package for calculating fuzzy similarity in species occurrence patterns. It includes functions for data preparation, such as converting species lists (long format) to presence-absence tables (wide format), obtaining unique abbreviations of species names, or transposing (parts of) complex data frames; and sample data sets for providing practical examples. It can convert binary presence-absence to fuzzy occurrence data, using e.g. trend surface analysis, inverse distance interpolation or prevalence-independent environmental favourability modelling, for multiple species simultaneously. It then calculates fuzzy similarity among (fuzzy) species distributions and/or among (fuzzy) regional species compositions. Currently available similarity indices are Jaccard, Sørensen, Simpson, and Baroni-Urbani & Buser.