Climate-based empirical models show biased predictions of butterfly communities along environmental gradients

A better understanding of the factors that mould ecological community structure is required to accurately predict community composition and to anticipate threats to ecosystems due to global changes. We tested how well stacked climate-based species distribution models (S-SDMs) could predict butterfly communities in a mountain region. It has been suggested that climate is the main force driving butterfly distribution and community structure in mountain environments, and that, as a consequence, climate-based S-SDMs should yield unbiased predictions. In contrast to this expectation, at lower altitudes, climate-based S-SDMs overpredicted butterfly species richness at sites with low plant species richness and underpredicted species richness at sites with high plant species richness. According to two indices of composition accuracy, the Sorensen index and a matching coefficient considering both absences and presences, S-SDMs were more accurate in plant-rich grasslands. Butterflies display strong and often specialised trophic interactions with plants. At lower altitudes, where land use is more intense, considering climate alone without accounting for land use influences on grassland plant richness leads to erroneous predictions of butterfly presences and absences. In contrast, at higher altitudes, where climate is the main force filtering communities, there were fewer differences between observed and predicted butterfly richness. At high altitudes, even if stochastic processes decrease the accuracy of predictions of presence, climate-based S-SDMs are able to better filter out butterfly species that are unable to cope with severe climatic conditions, providing more accurate predictions of absences. Our results suggest that predictions should account for plants in disturbed habitats at lower altitudes but that stochastic processes and heterogeneity at high altitudes may limit prediction success of climate-based S-SDMs.

Anàlisi de la modelització hidrològica com a eina per la predicció d'inundacions i la gestió del territori

Les inundacions són actualment les catàstrofes naturals més recurrents i les que generen un major nombre de danys i víctimes arreu del món. L'ocupació de les zones inundables a les lleres del riu és la causa principal d’aquests desastres naturals. En aquest article es descriu la realització de models hidrològics com a mecanisme per la predicció d’inundacions i la gestió del territori. S’han estudiat les conques de la Riera de Santa Coloma (Catalunya) i del riu San Francisco (Guatemala) mitjançant els programes HEC-HMS i HEC-RAS, dels quals s’avalua la seva capacitat com eina per a la gestió del territori. S’ha analitzat l’efecte de la urbanització en el risc d’inundació en el cas de la Riera de Santa Coloma en base a la previsió del Plà d’Ordenament Urbanístic Municipal. S’han determinat les zones inundables resultants de episodis de precipitació extrems al Riu San Francisco per als episodis de les tempestes Stan(2005) i Agatha(2010).

Anàlisi multidisciplinària de la vulnerabilitat a la contaminació de les aigües subterrànies: la conca de l'Onyar (Gironès)

En el present projecte s’ha emprat la metodologia DRASTIC per evaluar la vulnerabilitat a la contaminació de les aigües subterrànies de la conca de l’Onyar. El fet de ser una zona de tradició agrícola i ramadera i amb un creixement urbanístic significatiu, la fa ser una zona de gran interès per l’estudi de la vulnerabilitat. Després d’obtenir l’índex DRASTIC s’ha realitzat una campanya al mes de maig de 2011 per analitzar les concentracions de nitrats a la zona per validar l’estudi. Conjuntament amb el mapa d’usos del sòl i la informació de la localització de les depuradores més properes, s’han comparat els resultats d’ambdós mapes. L’anàlisi dels resultats obtinguts ha permès comprovar que la metodologia dóna bons resultats quan s’analitza la vulnerabilitat a nivell de conca. A més a més, utensilis de fàcil abast aporten informació sobre el perill de contaminació, ajudant a la validació del mètode.

Can Remotely Sensed Meteorological Data Significantly Contribute to Reduce Costs of Tsetse Surveys?

A 0.125 degree raster or grid-based Geographic Information System with data on tsetse, trypanosomosis, animal production, agriculture and land use has recently been developed in Togo. This paper addresses the problem of generating tsetse distribution and abundance maps from remotely sensed data, using a restricted amount of field data. A discriminant analysis model is tested using contemporary tsetse data and remotely sensed, low resolution data acquired from the National Oceanographic and Atmospheric Administration and Meteosat platforms. A split sample technique is adopted where a randomly selected part of the field measured data (training set) serves to predict the other part (predicted set). The obtained results are then compared with field measured data per corresponding grid-square. Depending on the size of the training set the percentage of concording predictions varies from 80 to 95 for distribution figures and from 63 to 74 for abundance. These results confirm the potential of satellite data application and multivariate analysis for the prediction, not only of the tsetse distribution, but more importantly of their abundance. This opens up new avenues because satellite predictions and field data may be combined to strengthen or substitute one another and thus reduce costs of field surveys.

Seminar Report: Translating Research into Better Public Health: What Does it Mean for the CoE(NI)?

The workshop was attended by 13 people excluding facilitators. Most were from outside QUB (including Belfast City Council, NHSSB, BHSCT, Centre for Public Health, NICR, Institute of Agri-food and Land Use (QUB), etc).Programme was:Introductions Part 1: What’s “knowledge brokerage” all about?Presentation and Q&A (Kevin Balanda)Small group discussions Part 2: What the Centre of Excellence is doingPresentation and Q&A (Kevin Balanda)Small group discussions

Treeline and climate change : analyzing and modeling patterns and shifts in the Swiss Alps

Summary: Global warming has led to an average earth surface temperature increase of about 0.7 °C in the 20th century, according to the 2007 IPCC report. In Switzerland, the temperature increase in the same period was even higher: 1.3 °C in the Northern Alps anal 1.7 °C in the Southern Alps. The impacts of this warming on ecosystems aspecially on climatically sensitive systems like the treeline ecotone -are already visible today. Alpine treeline species show increased growth rates, more establishment of young trees in forest gaps is observed in many locations and treelines are migrating upwards. With the forecasted warming, this globally visible phenomenon is expected to continue. This PhD thesis aimed to develop a set of methods and models to investigate current and future climatic treeline positions and treeline shifts in the Swiss Alps in a spatial context. The focus was therefore on: 1) the quantification of current treeline dynamics and its potential causes, 2) the evaluation and improvement of temperaturebased treeline indicators and 3) the spatial analysis and projection of past, current and future climatic treeline positions and their respective elevational shifts. The methods used involved a combination of field temperature measurements, statistical modeling and spatial modeling in a geographical information system. To determine treeline shifts and assign the respective drivers, neighborhood relationships between forest patches were analyzed using moving window algorithms. Time series regression modeling was used in the development of an air-to-soil temperature transfer model to calculate thermal treeline indicators. The indicators were then applied spatially to delineate the climatic treeline, based on interpolated temperature data. Observation of recent forest dynamics in the Swiss treeline ecotone showed that changes were mainly due to forest in-growth, but also partly to upward attitudinal shifts. The recent reduction in agricultural land-use was found to be the dominant driver of these changes. Climate-driven changes were identified only at the uppermost limits of the treeline ecotone. Seasonal mean temperature indicators were found to be the best for predicting climatic treelines. Applying dynamic seasonal delimitations and the air-to-soil temperature transfer model improved the indicators' applicability for spatial modeling. Reproducing the climatic treelines of the past 45 years revealed regionally different attitudinal shifts, the largest being located near the highest mountain mass. Modeling climatic treelines based on two IPCC climate warming scenarios predicted major shifts in treeline altitude. However, the currently-observed treeline is not expected to reach this limit easily, due to lagged reaction, possible climate feedback effects and other limiting factors. Résumé: Selon le rapport 2007 de l'IPCC, le réchauffement global a induit une augmentation de la température terrestre de 0.7 °C en moyenne au cours du 20e siècle. En Suisse, l'augmentation durant la même période a été plus importante: 1.3 °C dans les Alpes du nord et 1.7 °C dans les Alpes du sud. Les impacts de ce réchauffement sur les écosystèmes - en particuliers les systèmes sensibles comme l'écotone de la limite des arbres - sont déjà visibles aujourd'hui. Les espèces de la limite alpine des forêts ont des taux de croissance plus forts, on observe en de nombreux endroits un accroissement du nombre de jeunes arbres s'établissant dans les trouées et la limite des arbres migre vers le haut. Compte tenu du réchauffement prévu, on s'attend à ce que ce phénomène, visible globalement, persiste. Cette thèse de doctorat visait à développer un jeu de méthodes et de modèles pour étudier dans un contexte spatial la position présente et future de la limite climatique des arbres, ainsi que ses déplacements, au sein des Alpes suisses. L'étude s'est donc focalisée sur: 1) la quantification de la dynamique actuelle de la limite des arbres et ses causes potentielles, 2) l'évaluation et l'amélioration des indicateurs, basés sur la température, pour la limite des arbres et 3) l'analyse spatiale et la projection de la position climatique passée, présente et future de la limite des arbres et des déplacements altitudinaux de cette position. Les méthodes utilisées sont une combinaison de mesures de température sur le terrain, de modélisation statistique et de la modélisation spatiale à l'aide d'un système d'information géographique. Les relations de voisinage entre parcelles de forêt ont été analysées à l'aide d'algorithmes utilisant des fenêtres mobiles, afin de mesurer les déplacements de la limite des arbres et déterminer leurs causes. Un modèle de transfert de température air-sol, basé sur les modèles de régression sur séries temporelles, a été développé pour calculer des indicateurs thermiques de la limite des arbres. Les indicateurs ont ensuite été appliqués spatialement pour délimiter la limite climatique des arbres, sur la base de données de températures interpolées. L'observation de la dynamique forestière récente dans l'écotone de la limite des arbres en Suisse a montré que les changements étaient principalement dus à la fermeture des trouées, mais aussi en partie à des déplacements vers des altitudes plus élevées. Il a été montré que la récente déprise agricole était la cause principale de ces changements. Des changements dus au climat n'ont été identifiés qu'aux limites supérieures de l'écotone de la limite des arbres. Les indicateurs de température moyenne saisonnière se sont avérés le mieux convenir pour prédire la limite climatique des arbres. L'application de limites dynamiques saisonnières et du modèle de transfert de température air-sol a amélioré l'applicabilité des indicateurs pour la modélisation spatiale. La reproduction des limites climatiques des arbres durant ces 45 dernières années a mis en évidence des changements d'altitude différents selon les régions, les plus importants étant situés près du plus haut massif montagneux. La modélisation des limites climatiques des arbres d'après deux scénarios de réchauffement climatique de l'IPCC a prédit des changements majeurs de l'altitude de la limite des arbres. Toutefois, l'on ne s'attend pas à ce que la limite des arbres actuellement observée atteigne cette limite facilement, en raison du délai de réaction, d'effets rétroactifs du climat et d'autres facteurs limitants.

Information systems for water resources management improvement in developing countries

Water resources management, as also water service provision projects in developing countries have difficulties to take adequate decisions due to scarce reliable information, and a lack of proper information managing. Some appropriate tools need to be developed in order to improve decision making to improve water management and access of the poorest, through the design of Decision Support Systems (DSS). On the one side, a DSS for developing co-operation projects on water access improvement has been developed. Such a tool has specific context constrains (structure of the system, software requirements) and needs (Logical Framework Approach monitoring, organizational-learning, accountability and evaluation) that shall be considered for its design. Key aspects for its successful implementation have appeared to be a participatory design of the system and support of the managerial positions at the inception phase. A case study in Tanzania was conducted, together with the Spanish NGO ONGAWA – Ingeniería para el Desarrollo. On the other side, DSS are required also to improve decision making on water management resources in order to achieve a sustainable development that not only improves the living conditions of the population in developing countries, but that also does not hinder opportunities of the poorest on those context. A DSS made to fulfil these requirements shall be using information from water resources modelling, as also on the environment and the social context. Through the research, a case study has been conducted in the Central Rift Valley of Ethiopia, an endhorreic basin 160 km south of Addis Ababa. There, water has been modelled using ArcSWAT, a physically based model which can assess the impact of land management practices on large complex watersheds with varying soils, land use and management conditions over long periods of time. Moreover, governance on water and environment as also the socioeconomic context have been studied.

Will climate change drive alien invasive plants into areas of high protection value? An improved model-based regional assessment to prioritise the management of invasions.

Species distribution models (SDMs) studies suggest that, without control measures, the distribution of many alien invasive plant species (AIS) will increase under climate and land-use changes. Due to limited resources and large areas colonised by invaders, management and monitoring resources must be prioritised. Choices depend on the conservation value of the invaded areas and can be guided by SDM predictions. Here, we use a hierarchical SDM framework, complemented by connectivity analysis of AIS distributions, to evaluate current and future conflicts between AIS and high conservation value areas. We illustrate the framework with three Australian wattle (Acacia) species and patterns of conservation value in Northern Portugal. Results show that protected areas will likely suffer higher pressure from all three Acacia species under future climatic conditions. Due to this higher predicted conflict in protected areas, management might be prioritised for Acacia dealbata and Acacia melanoxylon. Connectivity of AIS suitable areas inside protected areas is currently lower than across the full study area, but this would change under future environmental conditions. Coupled SDM and connectivity analysis can support resource prioritisation for anticipation and monitoring of AIS impacts. However, further tests of this framework over a wide range of regions and organisms are still required before wide application.

Tegumentary leishmaniasis outbreak in Bella Vista City, Corrientes, Argentina during 2003

Bella Vista City, Corrientes, Argentina, reported an epidemic outbreak of tegumentary leishmaniasis during 2003. The mean age of the 31 cases was 25.0 ± 13.7 years old, with a sex ratio male:female 1.8, and without mucosal involvement. They clustered in two contiguous neighbourhoods, 96% in the periurban border and 4% in the peripheral outskirts. The transmission peak was estimated to have occurred during April 2003. Four species (3608 sand flies) were captured in nine sites: Lutzomyia neivai (90.1%), Lu. pessoai (8.9%), Lu. migonei (0.8 %), and Brumptomyia avellari (0.2 %). The outskirts/rural capture ratio of Lu. neivai was up to 3, and the outskirts/periurban up to 200. Therefore, the 'urban' transmission in this southernmost known focus is still an ecotone-border associated risk. The changes in human distribution or activities, patches of the secondary vegetation, periurban streams, rainfall of the previous year, and river period floods could all contribute to 'urban' outbreaks in the region. Tegumentary leishmaniasis risk should be assessed for any project that involves changes in land use throughout an endemic area.

An ecoregional classification for the state of Roraima, Brazil: the importance of landscape in malaria biology

Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.

Air pollution exposure during pregnancy and reduced birth size: a prospective birth cohort study in Valencia, Spain

Background Maternal exposure to air pollution has been related to fetal growth in a number of recent scientific studies. The objective of this study was to assess the association between exposure to air pollution during pregnancy and anthropometric measures at birth in a cohort in Valencia, Spain. Methods Seven hundred and eighty-five pregnant women and their singleton newborns participated in the study. Exposure to ambient nitrogen dioxide (NO2) was estimated by means of land use regression. NO2 spatial estimations were adjusted to correspond to relevant pregnancy periods (whole pregnancy and trimesters) for each woman. Outcome variables were birth weight, length, and head circumference (HC), along with being small for gestational age (SGA). The association between exposure to residential outdoor NO2 and outcomes was assessed controlling for potential confounders and examining the shape of the relationship using generalized additive models (GAM). Results For continuous anthropometric measures, GAM indicated a change in slope at NO2 concentrations of around 40 μg/m3. NO2 exposure >40 μg/m3 during the first trimester was associated with a change in birth length of -0.27 cm (95% CI: -0.51 to -0.03) and with a change in birth weight of -40.3 grams (-96.3 to 15.6); the same exposure throughout the whole pregnancy was associated with a change in birth HC of -0.17 cm (-0.34 to -0.003). The shape of the relation was seen to be roughly linear for the risk of being SGA. A 10 μg/m3 increase in NO2 during the second trimester was associated with being SGA-weight, odds ratio (OR): 1.37 (1.01-1.85). For SGA-length the estimate for the same comparison was OR: 1.42 (0.89-2.25). Conclusions Prenatal exposure to traffic-related air pollution may reduce fetal growth. Findings from this study provide further evidence of the need for developing strategies to reduce air pollution in order to prevent risks to fetal health and development.