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Forests on oceanic islands, such as the Azores archipelago, enable interesting dendroclimatic research, given their pronounced climatic gradients over short geographical distances, despite the less pronounced seasonality. The Lauraceae play an essential ecological role in Macaronesian natural forests. An example is Laurus azorica (Seub.) Franco, a relevant species given its high frequency and physiognomic dominance in Azorean laurel forests. This study aims to quantify climate–growth relationships in L. azorica using a dendroecological approach. We sampled four stands at São Miguel and two stands at Terceira islands, for a total of 206 trees. Following standard dendrochronological methods and rigorous sample selection procedures, we obtained relatively low rbar values and high temporal autocorrelation. Using a stepwise Random Forest analysis followed by Generalized Linear Models calculation, we found prominent effects of present and previous year temperature, but a low precipitation signal on growth rings, with some model variation between stands. Our results agreed with previous observations for broad-leaved species with diffuse porous wood, contributing to increase the baseline dendroecological knowledge about Azorean forests. Due to the high levels of within- and between-stand variation, and to refine the climatic signal analysis, complementary approaches should be explored in the future. [ABSTRACT FROM AUTHOR]

Climate change is causing shifts in species distributions worldwide. Understanding how species distributions will change with future climate change is thus critical for conservation planning. Impacts on oceanic islands are potentially major given the disproportionate number of endemic species and the consequent risk that local extinctions might become global ones. In this study, we use species climate envelope models to evaluate the current and future potential distributions of Azorean endemic species of bryophytes, vascular plants, and arthropods on the Islands of Terceira and São Miguel in the Azores archipelago (Macaronesia). We examined projections of climate change effects on the future distributions of species with particular focus on the current protected areas. We then used spatial planning optimization software (PRION) to evaluate the effectiveness of protected areas at preserving species both in the present and future. We found that contractions of species distributions in protected areas are more likely in the largest and most populated island of São Miguel, moving from the coastal areas towards inland where the current protected areas are insufficient and inadequate to tackle species distribution shifts. There will be the need for a revision of the current protected areas in São Miguel to allow the sustainable conservation of most species, while in Terceira Island the current protected areas appear to be sufficient. Our study demonstrates the importance of these tools for informing long-term climate change adaptation planning for small islands. [ABSTRACT FROM AUTHOR]

Invasive alien species are among the most important, least controlled, and least reversible of human impacts on the world's ecosystems, with negative consequences affecting biodiversity and socioeconomic systems. Species distribution models have become a fundamental tool in assessing the potential spread of invasive species in face of their native counterparts. In this study we compared two different modeling techniques: (i) fixed effects models accounting for the effect of ecogeographical variables (EGVs); and (ii) mixed effects models including also a Gaussian random field (GRF) to model spatial correlation (Matérn covariance function). To estimate the potential distribution of Pittosporum undulatum and Morella faya (respectively, invasive and native trees), we used geo-referenced data of their distribution in Pico and São Miguel islands (Azores) and topographic, climatic and land use EGVs. Fixed effects models run with maximum likelihood or the INLA (Integrated Nested Laplace Approximation) approach provided very similar results, even when reducing the size of the presences data set. The addition of the GRF increased model adjustment (lower Deviance Information Criterion), particularly for the less abundant tree, M. faya. However, the random field parameters were clearly affected by sample size and species distribution pattern. A high degree of spatial autocorrelation was found and should be taken into account when modeling species distribution. [ABSTRACT FROM AUTHOR]

Tree density is an important parameter affecting ecosystems functions and management decisions, while tree distribution patterns affect sampling design. Pittosporum undulatum stands in the Azores are being targeted with a biomass valorization program, for which efficient tree density estimators are required. We compared T-Square sampling, Point Centered Quarter Method (PCQM), and N-tree sampling with benchmark quadrat (QD) sampling in six 900 m2 plots established at P. undulatum stands in São Miguel Island. A total of 15 estimators were tested using a data resampling approach. The estimated density range (344–5056 trees/ha) was found to agree with previous studies using PCQM only. Although with a tendency to underestimate tree density (in comparison with QD), overall, T-Square sampling appeared to be the most accurate and precise method, followed by PCQM. Tree distribution pattern was found to be slightly aggregated in 4 of the 6 stands. Considering (1) the low level of bias and high precision, (2) the consistency among three estimators, (3) the possibility of use with aggregated patterns, and (4) the possibility of obtaining a larger number of independent tree parameter estimates, we recommend the use of T-Square sampling in P. undulatum stands within the framework of a biomass valorization program. [ABSTRACT FROM AUTHOR]

Laurus azorica is an endemic tree species from Azores archipelago. In this study, we generated the plastome sequence as a first step in a global assessment of island endemic Lauraceae. The total chloroplast genome was 153,061 bp in length, with a large single copy (LSC) region of 87,226 bp and a small single copy (SSC) region of 18,033 bp, separated by two inverted repeats (IRs) regions of 23,901 bp. The overall GC content was 37.3%, and 43.1%, 35.4%, and 31.1% in the IRs, LSC, and SSC regions, respectively. It contained 106 genes, including 79 coding genes, 24 tRNA genes, and four rRNA genes. A phylogenetic analysis confirmed that L. azorica was clustered with L. nobilis within the family Lauraceae. [ABSTRACT FROM AUTHOR]