Receiving coastal waters and estuaries are among the most nutrient‐enriched environments on earth, and one of the symptoms of the resulting eutrophication is the proliferation of opportunistic, fast‐growing marine seaweeds. Here, we used a widespread macroalga often involved in blooms, Ulva spp., to investigate how supply of nitrogen (N) and phosphorus (P), the two main potential growth‐limiting nutrients, influence macroalgal growth in temperate and tropical coastal waters ranging from low‐ to high‐nutrient supplies. We carried out N and P enrichment field experiments on Ulva spp. in seven coastal systems, with one of these systems represented by three different subestuaries, for a total of nine sites. We showed that rate of growth of Ulva spp. was directly correlated to annual dissolved inorganic nitrogen (DIN) concentrations, where growth increased with increasing DIN concentration. Internal N pools of macroalgal fronds were also linked to increased DIN supply, and algal growth rates were tightly coupled to these internal N pools. The increases in DIN appeared to be related to greater inputs of wastewater to these coastal waters as indicated by high δ¹⁵N signatures of the algae as DIN increased. N and P enrichment experiments showed that rate of macroalgal growth was controlled by supply of DIN where ambient DIN concentrations were low, and by P where DIN concentrations were higher, regardless of latitude or geographic setting. These results suggest that understanding the basis for macroalgal blooms, and management of these harmful phenomena, will require information as to nutrient sources, and actions to reduce supply of N and P in coastal waters concerned.

Invasion by alien species is a worldwide phenomenon with negative consequences at both natural and production areas. Acacia longifolia is an invasive shrub/small tree well known for its negative ecological impacts in several places around the world. The recent introduction of a biocontrol agent (Trichilogaster acaciaelongifoliae), an Australian bud-galling wasp which decreases flowering of A. longifolia, in Portugal, demands the development of a cost-efficient method to monitor its establishment. We tested how Unmanned Aerial Vehicles (UAV) can be used to map A. longifolia flowering. Our core assumption is as the population of the biocontrol agent increases, its impacts on the reduction of A. longifolia flowering will be increasingly visible. Additionally, we tested if there is a simple linear correlation between the number of flowers of A. longifolia counted in field and the area covered by flowers in the UAV imagery. UAV imagery was acquired over seven coastal areas including frontal dunes, interior sand dunes and pine forests considering two phenological stages: peak and off-peak flowering season. The number of flowers of A. longifolia was counted, in a minimum of 60 1m2 quadrats per study area. For each study area, flower presence/absence maps were obtained using supervised Random Forest. The correlation between the number of flowers and the area covered by flowering plants could then be tested. The flowering of A. longifolia was mapped using UAV mounted with RGB and CIR Cannon IXUS/ELPH cameras (Overall Accuracy > 0.96; Cohen’s Kappa > 0.85) varying according to habitat type and flowering season. The correlation between the number of flowers counted and the area covered by flowering was weak (r2 between 0.0134 and 0.156). This is probably explained, at least partially, by the high variability of A. longifolia in what regards flowering morphology and distribution. The very high accuracy of our approach to map A. longifolia flowering proved to be cost efficient and replicable, showing great potential for detecting the future decrease in flowering promoted by the biocontrol agent. The attempt to provide a low-cost method to estimate A. longifolia flower productivity using UAV failed, but it provided valuable insights on the future steps.

Innovation is known to be an important and influential factor in fostering sustainable development. Yet, there is a paucity of literature on the extent to which universities are successfully implementing innovation in this field. This paper addresses this gap, by examining the role of innovation in the field of environmental sustainability in universities, and by reporting on the results of an international study, in which examples of successful experiences and good practice were identified. The paper outlines the lessons learned from such examples, with the aim of motivating other universities to engage in this rapidly growing field.

Invasive plant management is both challenging and expensive and as such strategic and well-informed decisions may contribute for a more effective management. Remote sensing time series can inform decision-making, improving management strategies. Acacia longifolia is one of the most widespread invasive plants in Portuguese coastal areas. We used this species to test a new approach to assess how different management practices and disturbances may influence invasive plants' distribution. The Mann-Kendall statistical test was applied to a 15-year time series (2000-2015) of Landsat TM/ETM+ derived normalized difference vegetation index to detect statistically significant vegetation trends. These maps were interpreted together with a land-cover map derived from a combined rule-based and supervised classification of a Landsat OLI image from November 27th 2013; this interpretation was then complemented with information about management practices and disturbances allowing to identify the processes influencing the current distribution of A. longifolia. The overall accuracy of the classification was 0.785 (Kappa 0.753) and A. longifolia was detected in 9% (8691 ha) of the study area. Of the nine processes of land cover change identified, “vegetation cover intensification” and “vegetation recovery after removal” were the main drivers of expansion. Pine forests were vulnerable to invasion but offered resistance to conversion into A. longifolia monospecific stands, while herbaceous and shrub habitats seemed less resistant to invasion. Some interventions aiming to control A. longifolia were shown to aggravate the invasion. This approach facilitates monitoring the invasion and allows managers to allocate resources to areas where management may be most effective.