Optimising a landscape visual quality protocol. A Method for reducing respondent fatigue and obtaining site-specific indicators.

Evaluation of landscape visual quality is crucial for policymaking and planning but is still challenging. A wide range of visual assessment protocols is available, but there is still no consensus on appropriate indicators or approaches. Also, evaluation protocols can encompass many indicators, being exhaustive and complex and making the evaluation lengthy. Furthermore, protocols tend to be catered to a particular type of landscape or site-specific, and it can be tricky to ensure the protocol developed is adequate for the landscape under study. This paper proposes a methodology to optimise the selection of indicators for landscape visual assessments. There are two main goals: i) reduce the evaluation time to avoid respondent fatigue, and ii) make the protocol site-specific, choosing indicators that perform better and avoiding redundant indicators. •The presented method optimises the selection of indicators in expert visual assessments;•Indicators are rated in situ on a 5-point scale and go through a performance and redundancy test;•It helps to adapt complex evaluation protocols to the study landscape and to choose robust indicators in a supported and scientific way.

Riparian forest response to extreme drought is influenced by climatic context and canopy structure.

Droughts significantly impact forest ecosystems, reducing forest health and productivity, compromising ecosystem functioning, and nature-based solutions for climate change. The response and resilience of riparian forests to drought are poorly understood despite their key role in the functioning of aquatic and terrestrial ecosystems. Here we investigate riparian forest drought responses and resilience to an extreme drought event at a regional scale. We also examine how drought event characteristics, average climate conditions, topography, soil, vegetation structure, and functional diversity shape the resilience of riparian forests to drought. We used a time series of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) to calculate the resistance to and recovery after an extreme drought (2017-2018) in 49 sites across an Atlantic-Mediterranean climate gradient in North Portugal. We used generalized additive models and multi-model inference to understand which factors best explained drought responses. We found a trade-off between drought resistance and recovery (maximum r = -0.5) and contrasting strategies across the climatic gradient of the study area. Riparian forests in the Atlantic regions showed comparatively higher resistance, while Mediterranean forests recovered more. Canopy structure and climate context were the most relevant predictors of resistance and recovery. However, median NDVI and NDWI had not returned to pre-drought levels (RcNDWI mean = 1.21, RcNDVI mean = 1.01) three years after the event. Our study shows that riparian forests have contrasting drought response strategies and may be susceptible to extended legacy effects associated with extreme and/or recurring droughts, similarly to upland forests. This work highlights the drought vulnerability of riparian ecosystems and emphasises the need for further studies on long-term resilience to droughts.

On the development of a regional climate change adaptation plan: Integrating model-assisted projections and stakeholders' perceptions.

Climate change is expected to have strong social-ecological implications, with global but especially regional and local challenges. To assess the climatic vulnerability of a given territory, it is necessary to evaluate its exposure to climate change and its adaptive capacity. This study describes the development of an Action Plan for Adapting to Climate Change in the Tâmega and Sousa Region, a mountainous inter-municipal community in the North of Portugal. The goals were to identify the main impacts of climate change on water resources, agriculture, forests, biodiversity, and socioeconomic sectors, as well as to develop a plan, merging local and scientific knowledge through a transdisciplinary lens. This study describes an approach that combines modelling methods, applied in the different sectors, and participatory methods, based on the analysis of the perceptions of local actors. Results indicate that the target region will experience a generalized increase in temperature and a decrease in precipitation, which will negatively impact all studied social-ecological dimensions. Overall, local business and institutional agents perceive the primary and tourism sectors as the most vulnerable in the region. The described framework demonstrates the engagement process between relevant scientific experts and local practitioners, as well as how it is critical to understand the impacts of climate change and to support the co-design of an adaptation plan, which in turn can guide political and economic decision-making towards effective implementation of the plan. In addition, the difficulties and challenges encountered during this process are discussed to support future plans and strategies for local adaptation.

Resilience of reptiles to megafires.

Extreme climate events, together with anthropogenic land-use changes, have led to the rise of megafires (i.e., fires at the top of the frequency size distribution) in many world regions. Megafires imply that the center of the burnt area is far from the unburnt; therefore, recolonization may be critical for species with low dispersal abilities such as reptiles. We aimed to evaluate the effect of megafires on a reptile community, exploring to what extent reptile responses are spatially shaped by the distance to the unburnt area. We examined the short-term spatiotemporal response of a Mediterranean reptile community after two megafires (>20,000 ha) that occurred in summer 2012 in eastern Spain. Reptiles were sampled over 4 years after the fire in burnt plots located at different distances from the fire perimeter (edge, middle, and center), and in adjacent unburnt plots. Reptile responses were modeled with fire history, as well as climate and remotely sensed environmental variables. In total, we recorded 522 reptiles from 12 species (11 species in the burnt plots and nine in the unburnt plots). Reptile abundance decreased in burnt compared with unburnt plots. The community composition and species richness did not vary either spatially (unburnt and burnt plots) or temporally (during the 4 years). The persistence of reptiles in the burnt area supported their resilience to megafires. The most common lizard species was Psammodromus algirus; both adults and juveniles were found in all unburnt and burnt plots. This species showed lower abundances in burnt areas compared with the unburnt and a slow short-term abundance recovery. The lizard Psammodromus edwarsianus was much less abundant and showed a tendency to increase its abundance in burnt plots compared with unburnt plots. Within the megafire area, P. algirus and P. edwarsianus abundances correlated with the thermal-moisture environment and vegetation recovery regardless of the distance from the fire edge. These results indicated the absence of a short-term reptile recolonization from the unburnt zone, demonstrating that reptiles are resilient (in situ persistence) to megafires when environmental conditions are favorable.

Projected climate changes are expected to decrease the suitability and production of olive varieties in southern Spain.

World olive production is based on the cultivation of different varieties that respond differently to abiotic factors. Climate change may affect the area of land suitable for olive cultivation and change production levels, thus causing serious damage to this economically-relevant and highly-productive olive grove agroecosystem. In Mediterranean regions such as Andalusia, one of the main areas of olive production, the effect of climate change seems threatening. Thus, our main aims are: (1) to examine the abiotic factors that characterise the current cultivated locations and predict the current and potential distribution of these locations; (2) to evaluate the effect of climate change (based on regional scenarios) on the future environmental suitability of each olive variety; and (3) to analyse the expected alteration in the annual olive production. We used the seven most-productive olive varieties in Andalusia and the wild olive species to develop Species Distribution Models (SDMs), coupled with soil properties, geomorphology, water balance and (bio-)climatic predictors at a fine scale. We also derived future climate projections to assess the effect of climate change on the environmental suitability and productivity of each olive variety. We found that soil pH was the most-important factor for most distribution models, while (bio-)climatic predictors - such as continentality index, summer and autumn precipitation and winter temperature - provided important contributions. In general, projections based on regional climate change scenarios point to a decrease in the area suitable for olive crops in Andalusia, due to an increase in evapotranspiration and a decrease in precipitation. These changes in suitable area are also projected to decrease olive production for almost all the olive-growing provinces investigated. Our findings may anticipate the effects of climate change on olive crops and provide early estimates of fruit production, at local and regional scales, as well as forming the basis of adaptation strategies.