Wastewater-irrigated vegetables are a significant source of heavy metal contaminants : toxicity and health risks

Water contaminated with heavy metals constitutes an important threat. This threat is a real problem with a negative impact in some developing countries where untreated industrial effluents are used for irrigation. The present study examines heavy metals in wastewater-irrigated vegetables (apple gourd, spinach, cauliflower, sponge gourd, and coriander) water, and soil from Chenab Nagar, Chiniot, Pakistan. In particular, the metals quantified were cadmium (Cd), chromium (Cr), cobalt (Co), nickel (Ni), lead (Pb), and manganese (Mn). Among them, Cr and Co in crops irrigated -wastewater exceeded the levels recommended by the World Health Organization (WHO). In contrast, Ni, Cu, Pb, and Mn concentrations were in line with WHO standards. Compared with the limits established by the Food and Agriculture Organization of the United Nations (FAO), all the study vegetables presented higher (thus unsafe) concentrations of Cd (0.38 to 1.205 mg/Kg). There were also unsafe concentrations of Cr in coriander, sponge gourd, and cauliflower. Pb was found at an unsafe concentration (0.59 mg/Kg) in cauliflower. Conversely, Ni and Mn concentrations were below the maximum permissible limits by WHO, and FAO in all of the analyzed samples. The contamination load index (CLI) in soil, bioconcentration factor (BCF) in plants, daily intake of metals (DIM), and health risk index (HRI) have also been evaluated to estimate the potential risk to human health in that area. We have found an important risk of transitions of Pb, Cd, Cr, and Co from water/soil to the edible part of the plant. The highest HRI value associated with Cd (6.10–13.85) followed by Cr (1.25–7.67) for all vegetable samples presented them as high health risk metal contaminants. If the issue is not addressed, consumption of wastewater-irrigated vegetables will continue posing a health risk

SimiVal, a multi-criteria map comparison tool for land-change model projections

The multiple uses of land-cover models have led to validation with choice metrics or an ad hoc choice of the validation metrics available. To address this, we have identified the major dimensions of land-cover maps that ought to be evaluated and devised a Similarity Validation (SimiVal) tool. SimiVal uses a linear regression to test a modelled projection against benchmark cases of, perfect, observed and systematic-bias, calculated by rescaling the metrics from a random case relative to the observed, perfect case. The most informative regression coefficients, p-value and slope, are plot on a ternary graph of ‘similarity space’ whose extremes are the three benchmark cases. SimiVal is tested on projections of two deliberately contrasting land-cover models to show the similarity between intra- and inter-model parameterisations. We find metrics of landscape structure are important in distinguishing between different projections of the same model. Predictive and exploratory models can benefit from the tool

Agricultural land systems : modelling past, present and future regional dynamics

This thesis arises from the understanding of how the integration of concepts, tools, techniques, and methods from geographic information science (GIS) can provide a formalised knowledge base for agricultural land systems in response to future agricultural and food system challenges. To that end, this thesis focuses on understanding the potential application of GIS-based approaches and available spatial data sources for modelling regional agricultural land-use and production dynamics in Portugal. The specific objectives of this thesis are addressed in seven chapters in Parts II through V, each corresponding to one scientific article that was either published or is being considered for publication in peer-reviewed international scientific journals. In Part II, Chapter 2 summarises the body of knowledge and provides the context for the contribution of this thesis within the scientific domain of agricultural land systems. In Part III, Chapters 3 and 4 explore remotely sensed and Volunteered Geographic Information (VGI) data, multitemporal and multisensory approaches, and a variety of statistical methods for mapping, quantifying, and assessing regional agricultural land dynamics in the Beja district. In Part IV, Chapters 5–7 explore the CA-Markov model, Markov chain model, machine learning, and model-agnostic approach, as well as a set of spatial metrics and statistical methods for modelling the factors and spatiotemporal changes of agricultural land use in the Beja district. In Part V, Chapter 8 explores an area-weighting GIS-based technique, a spatiotemporal data cube, and statistical methods to model the spatial distribution across time for regional agricultural production in Portugal. The case studies in the thesis contribute practical and theoretical knowledge by demonstrating the strengths and limitations of several GIS-based approaches. Together, the case studies demonstrate the underlying principles that underpin each approach in a way that allows us to infer their potentiality and appropriateness for modelling regional agricultural land-use and production dynamics, stimulating further research along this line. Generally, this thesis partly reflects the state-of-art of land-use modelling and contribute significantly to the introduction of advances in agricultural system modelling research and land-system science

Aproximación multiescalar al estudio biogeográfico de los impactos del cambio global en la ecorregión mediterránea. La Biogeografía en el Antropoceno.

Cambio global es una expresión que integra el conjunto de impactos causados por las actividades humanassobre elfuncionamiento del medio (eco)geográfico donde el propio ser humano se desenvuelve.Ha sido de tal magnitud la aceleración del proceso de antropización que ha experimentado nuestro planeta en los últimos siglos, que en el seno de la comunidad científica se ha llegado a proponer -en el contexto de una viva discusión que sigue abierta- el Antropoceno, comouna época funcional y estratigráficamente diferente del Hocoleno.En esta tesis doctoral,abordamos distintos casos de estudios y aplicamos un innovador conjunto de metodologíasespacialmente explícitasconcebidas para el estudio biogeográfico y multiescalar de cambios, patrones, tendencias y escenarios en un contexto de cambio global. OBJETIVOS El objetivo general de la presente tesis doctoral es el diseño y aplicación de una serie de metodologías de investigación espacialmente explícitas orientadas hacia el estudio biogeográfico multiescalar de los impactos locales del cambio global en la ecorregión mediterránea —como referencia de ecorregión vulnerable al cambio. Los objetivos metodológicos específicos de la tesis, que se abordan a través del análisis de casos de estudio, son los siguientes: Objetivo 1. Evaluar la utilidad del análisis espacialmente explicitico de cambios de usos y coberturas del suelo.Caso de estudio: Evolución de la superficie forestal en Andalucía. Objetivo 2. Desarrollar un flujo de trabajo integrado para calibrar modelos de nicho ecológico en el contexto de la Geografía física. Caso de estudio: Modelo de distribución potencial del alcornoque en Andalucía. Objetivo 3. Integrar escenarios de cambio climático y modelos de nicho ecológico para simular cambios ambientales.Caso de estudio: Impacto del calentamiento global en la distribución y supervivencia del pinsapo en la Serranía de Ronda. Objetivo 4. Implementar la monitorización de las respuestas ecofisiológicas de la vegetación mediante el uso de sensores remotos. Caso de estudio: Análisis de tendencia estacional e interanual de los pinsapares béticos. Objetivo 5. Estimar distribuciones potenciales y riesgos biológicos mediante la aplicación integrada de modelos de distribución de especies y técnicas de evaluación multicriterio. Caso de estudio: Distribución potencial global de Xylella fastidiosa y exposición de la península Ibérica e islas Balearesa la entrada y propagación del patógeno