Native diversity buffers against severity of non-native tree invasions.

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

A multitaxonomic assessment of Natura 2000 effectiveness across European biogeographic regions.

The Natura 2000 (N2K) protected area (PA) network is a crucial tool to limit biodiversity loss in Europe. Despite covering 18% of the European Union's (EU) land area, its effectiveness at conserving biodiversity across taxa and biogeographic regions remains uncertain. Testing this effectiveness is, however, difficult because it requires considering the nonrandom location of PAs, and many possible confounding factors. We used propensity score matching and accounted for the confounding effects of biogeographic regions, terrain ruggedness, and land cover to assess the effectiveness of N2K PAs on the distribution of 1769 species of conservation priority in the EU's Birds and Habitats Directives, including mammals, birds, amphibians, reptiles, arthropods, fishes, mollusks, and vascular and nonvascular plants. We compared alpha, beta, and gamma diversity between matched selections of protected and unprotected areas across EU's biogeographic regions with generalized linear models, generalized mixed models, and nonparametric tests for paired samples, respectively, for each taxonomic group and for the entire set of species. PAs in N2K hosted significantly more priority species than unprotected land, but this difference was not consistent across biogeographic regions or taxa. Total alpha diversity and alpha diversity of amphibians, arthropods, birds, mammals, and vascular plants were significantly higher inside PAs than outside, except in the Boreal biogeographical region. Beta diversity was in general significantly higher inside N2K PAs than outside. Similarly, gamma diversity had the highest values inside PAs, with some exceptions in Boreal and Atlantic regions. The planned expansion of the N2K network, as dictated by the European Biodiversity Strategy for 2030, should therefore target areas in the southern part of the Boreal region where species diversity of amphibians, arthropods, birds, mammals, and vascular plants is high and species are currently underrepresented in N2K.

Análisis multitaxonómico de la efectividad de Natura 2000 en las regiones biogeográficas de Europa Resumen La red de áreas protegidas (AP) de Natura 2000 (N2K) es una herramienta importante para reducir la pérdida de biodiversidad en Europa. A pesar de que cubre el 18% del área terrestre de la UE, todavía es incierta la efectividad que tiene para conservar la biodiversidad en los taxones y las regiones biogeográficas. Sin embargo, es complicado analizar esta efectividad porque requiere considerar la ubicación no azarosa de las AP y la posibilidad de muchos factores confusos. Usamos el pareamiento por puntaje de propensión y consideramos los efectos confusos de las regiones biogeográficas, lo accidentado del terreno y la cobertura del suelo para analizar la efectividad de las AP de N2K en la distribución de 1,769 especies (mamíferos, aves, anfibios, reptiles, artrópodos, peces, moluscos y plantas vasculares y no vasculares) con prioridad de conservación en las Directivas de Aves y Hábitats de la UE. Comparamos la diversidad alfa, beta y gamma entre las selecciones pareadas de las áreas protegidas y no protegidas en las regiones biogeográficas de la UE con los modelos generalizados lineales, mixtos y pruebas no paramétricas de las muestras pareadas, respectivamente, para cada grupo taxonómico y para el conjunto completo de especies. Las áreas protegidas en N2K tuvieron una mayoría significativa de especies prioritarias en comparación con el suelo no protegido, pero esta diferencia no fue coherente entre los taxones y las regiones biogeográficas. La diversidad alfa total y la diversidad alfa de anfibios, artrópodos, aves, mamíferos y plantas vasculares fue significativamente mayor dentro de las AP que fuera de ellas, excepto en la región biogeográfica boreal. La diversidad beta fue significativamente más alta dentro de las AP de N2K que fuera de ellas. De forma similar, la diversidad gamma tuvo los valores más altos dentro de las AP, salvo algunas excepciones en las regiones boreal y atlántica. Por lo tanto, la expansión planeada de la red N2K, como dicta la Estrategia de la UE sobre Biodiversidad para 2030, debería enfocarse en las áreas del sur de la región boreal, donde es alta la diversidad de especies de anfibios, artrópodos, aves, mamíferos y plantas vasculares y cuyas especies están poco representadas dentro de N2K.

An integrated pan-tropical biomass map using multiple reference datasets.

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

Impacts of noise pollution from high-speed rail and road on bird diversity: a case study in a protected area of Italy.

The disturbance of infrastructures may affect biological communities that are exposed to them. This study assesses the impact of high-speed (highway and railway) infrastructures in a protected study site, the Natural Reserve Fontanili di Corte Valle Re (Emilia-Romagna, Italy). We compared bird diversity with sound intensity and frequency in three sampling areas, increasingly distant from the infrastructures at the border with the reserve, during the last 4 years (2019-2022), monitoring sedentary, nesting, and migratory bird species. We hypothesize a decreasing diversity closer to the source of disturbance, which is mostly attributable to noise pollution. Our findings confirmed this trend, and we show that, in particular, disturbance seems to influence species richness more than the total abundance of birds. We also discovered that highway disturbance was much higher than railway in terms of frequency and duration. In light of these results, we suggest that some species, which have a behavioral ecology strongly based on singing to communicate with each other for their reproductive and defensive strategies, may suffer more from constant acoustic disturbance. The installation of effective noise barriers to shield the sound produced by the highways should be considered a mandatory request not only in proximity to houses but also in the vicinity of protected areas.

Grassland vertical height heterogeneity predicts flower and bee diversity: an UAV photogrammetric approach.

The ecosystem services offered by pollinators are vital for supporting agriculture and ecosystem functioning, with bees standing out as especially valuable contributors among these insects. Threats such as habitat fragmentation, intensive agriculture, and climate change are contributing to the decline of natural bee populations. Remote sensing could be a useful tool to identify sites of high diversity before investing into more expensive field survey. In this study, the ability of Unoccupied Aerial Vehicles (UAV) images to estimate biodiversity at a local scale has been assessed while testing the concept of the Height Variation Hypothesis (HVH). This hypothesis states that the higher the vegetation height heterogeneity (HH) measured by remote sensing information, the higher the vegetation vertical complexity and the associated species diversity. In this study, the concept has been further developed to understand if vegetation HH can also be considered a proxy for bee diversity and abundance. We tested this approach in 30 grasslands in the South of the Netherlands, where an intensive field data campaign (collection of flower and bee diversity and abundance) was carried out in 2021, along with a UAV campaign (collection of true color-RGB-images at high spatial resolution). Canopy Height Models (CHM) of the grasslands were derived using the photogrammetry technique "Structure from Motion" (SfM) with horizontal resolution (spatial) of 10 cm, 25 cm, and 50 cm. The accuracy of the CHM derived from UAV photogrammetry was assessed by comparing them through linear regression against local CHM LiDAR (Light Detection and Ranging) data derived from an Airborne Laser Scanner campaign completed in 2020/2021, yielding an [Formula: see text] of 0.71. Subsequently, the HH assessed on the CHMs at the three spatial resolutions, using four different heterogeneity indices (Rao's Q, Coefficient of Variation, Berger-Parker index, and Simpson's D index), was correlated with the ground-based flower and bee diversity and bee abundance data. The Rao's Q index was the most effective heterogeneity index, reaching high correlations with the ground-based data (0.44 for flower diversity, 0.47 for bee diversity, and 0.34 for bee abundance). Interestingly, the correlations were not significantly influenced by the spatial resolution of the CHM derived from UAV photogrammetry. Our results suggest that vegetation height heterogeneity can be used as a proxy for large-scale, standardized, and cost-effective inference of flower diversity and habitat quality for bees.

The global distribution and drivers of wood density and their impact on forest carbon stocks.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

A quixotic view of spatial bias in modelling the distribution of species and their diversity.

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

Climate change-induced salinity variation impacts on a stenoecious mangrove species in the Indian Sundarbans.

The alterations in the salinity profile are an indirect, but potentially sensitive, indicator for detecting changes in precipitation, evaporation, river run-off, glacier retreat, and ice melt. These changes have a high impact on the growth of coastal plant species, such as mangroves. Here, we present estimates of the variability of salinity and the biomass of a stenoecious mangrove species (Heritiera fomes, commonly referred to as Sundari) in the aquatic subsystem of the lower Gangetic delta based on a dataset from 2004 to 2015. We highlight the impact of salinity alteration on the change in aboveground biomass of this endangered species that, due to different salinity profile in the western and central sectors of the lower Gangetic plain, shows an increase only in the former sector, where the salinity is dropping and low growth in the latter, where the salinity is increasing.

Evolution is a cooperative process: the biodiversity-related niches differentiation theory (BNDT) can explain why.

A. McFayden and G.E. Hutchinson defined a niche as a multidimensional space or hypervolume within the environment that allows an individual or a species to survive, we consider niches as a fundamental ecological variable that regulate species' composition and relation in ecosystems. Successively the niche concept has been associated to the genetic term "phenotype" by MacArthurstressing the importance on what a species or a genome can show outside, either in the environmental functions or in body characteristics. Several indexes have been developed to evaluate the grade of overlapping and similarities of species' niches, even utilizing the theory of information. However, which are the factors that determine the number of species that can coexist in a determinate environment and why a generalist species do not compete until the exclusion of the remaining species to maximize its fitness, is still quite unknown. Moreover, there are few studies and theories that clearly explain why the number of niches is so variable through ecosystems and how can several species live in the same basal niche, intended in a comprehensive sense as the range of basic conditions (temperature, humidity, food-guild, etc.). Here I show that the number of niches in an ecosystem depends on the number of species present in a particular moment and that the species themselves allow the enhancement of niches in terms of space and number. I found that using a three-dimensional model as hypervolume and testing the theory on a Mediterranean, temperate and tropical forest ecosystem it is possible to demonstrate that each species plays a fundamental role in facilitating the colonization by other species by simply modifying the environment and exponentially increasing the available niches' space and number. I resumed these hypothesis, after some preliminary empiric tests, in the Biodiversity-related Niches Differentiation Theory (BNDT), stressing with these definition that the process of niches differentiation is strictly addressed by species. This approach has various consequences, first in consideration of relations among species and second in terms of a better understanding of cooperation/competition dynamics.