• Energy Research
• 13. Climate action close

Sustainable Development Goals (SDGs) include a subset of targets that can be advanced through standard urban management activities. In particular, routine urban vegetation management comprises a number of activities with potential impact on Goal #4 (quality education), #11 (sustainable cities and communities), #13 (protect the planet), #15 (life on land), and, perhaps less obviously, but equally important, on Goal #8 (good jobs and economic growth). This paper discusses how urban vegetation management can help achieve the SDGs at a local level. Drawing on a case study (Talavera de la Reina, Spain), it is shown that an intelligent approach to urban vegetation management can leverage resources towards the SDGs at little or no cost to municipalities. Minor modifications and conceptual changes in how standard practices are carried out can make a difference. Including this dimension can even result in a positive balance for the municipal budget. Our analyses and proposals are of broad and direct applicability for urban areas worldwide and can help city authorities and officials to align their cities with the SDGs simply by making minor adjustments to how they currently deal with urban vegetation.

Climate change impacts particularly affect vulnerable populations such as children. Therefore, it is necessary to address the adaptation of educational buildings to prevent their negative impact on school performance and to increase their resilience. This study is part of an ongoing project, LIFE myBUILDINGisGREEN (LIFE17 CCA/ES/000088), which aims to optimise learning conditions in schools in Southern Europe affected by heat waves during warmer months. This first part of this project focuses on predicting the impact of Nature-Based Solutions (NBS) implementation. The main concern of this stage is to analyse the benefits on both interior comfort and energy efficiency. This paper presents the results of the influence on space cooling demand via dynamic building simulations after successively applying the different NBS. Further improvements in indoor environmental conditions such as CO2 concentration reductions will be evaluated later. For this purpose, a demonstration building, located in southern Spain, characterized in terms of thermophysical parameters of the envelope and air infiltrations was selected. The energy model was calibrated with actual monitoring data. Different scenarios have been analysed through an energy prediction software, leading to a wide range of outcomes in terms of improvements in both energy demand - assuming a cooling system - and temperature reduction.

AbstractOceanic islands are of fundamental importance for the conservation of biodiversity because they exhibit high endemism rates coupled with fast extinction rates. Nowhere in Europe is this pattern more conspicuous than in the Macaronesian biogeographic region. A large network of protected areas within the region has been developed, but the question of whether these areas will still be climatically suitable for the globally threatened endemic element in the coming decades remains open. Here, we make predictions on the fate of the Macaronesian endemic bryophyte flora in the context of ongoing climate change. The potential distribution of 35 Macaronesian endemic bryophyte species was assessed under present and future climate conditions using an ensemble modelling approach. Projections of the models under different climate change scenarios predicted an average decrease of suitable areas of 62–87% per species and a significant elevational increase by 2070, so that even the commonest species were predicted to fit either the Vulnerable or Endangered IUCN categories. Complete extinctions were foreseen for six of the studied Macaronesian endemic species. Given the uncertainty regarding the capacity of endemic species to track areas of suitable climate within and outside the islands, active management associated to an effective monitoring program is suggested.

AbstractClimate change is a key stressor for species. Two major consequences of climate‐induced range shifts are the formation of new areas of geographic overlap (i.e. sympatry) and an increased probability of hybridisation in thede novocreated contact zones.One method to effectively quantify the potential of hybridisation is to integrate ecological niche modelling and the propensity to hybridisation based on genetic divergence. In this paper, we have applied this methodology to predict hybridisation outcomes following different scenarios of climate change in 30 species ofArgiadamselflies.We (i) investigated how climate change may affect species’ distributions; (ii) quantified if changed distributions generate new areas of sympatry between species; (iii) calculated the propensity to hybridise based on genetic divergence between species; and (iv) integrated these data to predict the future potential of species to hybridise.We found that the distribution of 29 of the 30 species was affected by a change in climate which led to a general increase in sympatric overlap among species. The degree of genetic divergence among the 108 species’ combinations ranged from 0.06% to 0.36%. Based on the sympatric overlap and genetic divergence, it can be predicted that 97 of the species pairs are likely to hybridise in the future.Our results are useful to forecast how highly diverse and closely related groups, such asArgiadamselflies, may respond to a change in climate and how this can impact the potential of species mixing under a scenario of increased global warming.

Climate change impacts particularly affect vulnerable populations such as children. Therefore, addressing the adaptation of educational buildings is crucial in avoiding these negative effects on school performance. In this paper, three educational buildings, located in Badajoz (Spain), Evora (Portugal) and Porto (Portugal), serve as pilot samples to study the suitability of nature-based solutions (NBS), chosen for each one of three climatic zones. The NBS selected include green roofs, vertical structures with vegetation to shade holes, outdoor trees and free-cooling ventilation. The scenarios of the different NBS implemented in the three models were simulated with the software EnergyPlus, which allows optimising the appropriate decision before renovation operations begin. The results obtained from the simulations suggest energy performance improvements after applying the most adequate NBS selection to each one of the three buildings tested. Particularly, a reduction in radiation on both roofs and facades is required in the case of Evora and Badajoz, where both climate zones have similar features, that is, warm and dry. While in Porto, milder and more humid than the former ones, it is very effective to operate mainly on the roof, complemented by small ventilation operations. The authors gratefully acknowledge the support of this work by the LIFE+ Programme under the responsibility of the Directorate General for the Environment of the European Commission through the agreement LIFE17 CCA/ES/00088, LIFE myBUILDINGisGREEN.

In order to prevent future biological invasions, it is crucial to know non-native species distributions. We evaluated the potential global distribution of Azolla filiculoides, a free-floating macrophyte native to the Americas by using species distribution models and niche equivalency tests to analyze the degree of niche overlap between the native and invaded ranges of the species. The models were projected under two future emission scenarios, three global circulation models and two time periods. Our results indicate a possible niche shift between the distribution ranges of the species, indicating that A. filiculoides can adapt to novel environmental conditions derived from climatic differences during the invasion process. Our models also show that the future potential distribution of A. filiculoides will decrease globally, although the species could colonize new vulnerable regions where it is currently absent. We highlight that species occurrence records in the invaded area are necessary to generate accurate models, which will, in turn, improve our ability to predict potential invasion risk areas.