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Acoustic monitoring captures the sound of nature, revealing biodiversity patterns and underlying drivers. Acoustic indices are increasingly used to analyse obtained recordings, but studies show inconsistent performance of acoustic indices as biodiversity indicators. Here, we develop a conceptual framework on what acoustic indices reflect, including sound sources as well as their direct and indirect drivers. We evaluate our framework using recordings from six land–use types and old–growth forest sites in north-eastern Madagascar. We found the highest correlation (adj. R2 > 0.51) of Acoustic Diversity Index and Acoustic Entropy with endemic multi-taxa species richness, canopy closure, and vegetation density. The results suggest that including multiple taxa strengthens the association between the indices and species richness, potentially accounting for unobserved vocalising taxa, and that acoustic indices indicate habitat quality, reflecting underlying indirect and direct drivers affecting biodiversity. Yet, some acoustic indices are limited by saturation and their sensitivity is too low to detect small changes in biodiversity (e.g., loss of few species).

Transformation of forests into agricultural lands threatens biodiversity and ecosystem functions globally. In the biodiversity hotspot Madagascar, key ecosystem functions along with highly endemic flora and fauna are under threat. Comprehensive studies identifying determinants of biodiversity and ecosystem function losses are lacking, with no studies accounting for endemic species richness across multiple taxa. We assess how plot-scale stand structural attributes (basal area, leaf area index, diameter diversity, and tree species richness) and landscape-scale forest cover influence biodiversity (species richness of butterflies, ants, birds, reptiles, amphibians, herbaceous plants, and multidiversity) and ecosystem functions (soil organic carbon, predation rate, acoustic diversity, and multifunctionality) in the tropical mosaic landscape of northeastern Madagascar. Complexly structured stands with a larger basal area and/or a higher tree species richness promoted greater endemic multidiversity (R² = 0.70), soil organic carbon, and acoustic diversity. However, our models did not indicate significant explanatory variables for multidiversity (R² = 0.25) and multifunctionality (R² = 0.43). Landscape-scale forest cover significantly favored endemic bird species richness. Our findings highlight that a simplified stand structure, resulting from land-use change, substantially reduces endemic biodiversity and ecosystem functions in this historically forested region. Conservation actions should aim at maintaining complex stand structure in forests and agroforests, while restoration interventions should focus on re-building such structures.

Vegetation structural complexity is an important component of forest ecosystems, influencing biodiversity and functioning. Due to the heterogeneous distribution of vegetation elements, structural complexity underpins ecological dynamics, species composition, microclimate, and habitat diversity. Field measurements and Light Detection and Ranging (LiDAR) data, such as airborne (ALS) and terrestrial (TLS), can assess structural characteristics of forest and agroforestry systems at various spatial scales. This assessment is urgently needed for monitoring ecosystem restoration in degraded lands (e.g., in oil palm landscapes), where it is not well-known how structural measures derived from these different approaches relate to each other. Here, we compared the degree of correlation between individual and multivariate datasets of vegetation structural complexity metrics derived from ALS, TLS, and ground-based inventory approaches. The study was conducted in a 140 ha oil palm monoculture, enriched with 52 plots in the form of tree islands representing agroforestry systems of varying sizes and planted diversity levels in Sumatra, Indonesia. Our datasets comprised 25 ALS, five TLS, and nine ground-based inventory metrics. We studied correlations among metrics related to traditional stand summary, heterogeneity, and vertical and horizontal stand structure. We used principal component analysis for data dimensionality reduction, correlation analysis to quantify the strength of relationships between metrics, and Procrustes analysis to investigate the agreement between datasets. Significant correlations were found between ALS and TLS metrics for canopy density (r = 0.79) and maximum tree height (r = 0.58) and between ALS and ground-based inventory measures of stand heterogeneity and height diversity (r between 0.60 and −0.63). Further, we observed significant agreements between the ordinations of multivariate datasets (r = 0.56 for ALS − TLS; and r = 0.46 for ALS – ground-based inventory). Our findings underline the ability of ALS to capture structural complexity patterns, especially for canopy gap dynamics and vegetation height metrics, as captured by TLS, and for measures of heterogeneity and vertical structure as captured by ground-based inventories. Our study highlights the strength of each approach and underscores the potential of integrating ALS and TLS with ground-based inventories for a comprehensive characterization of vegetation structure in complex agroforestry systems, which can provide guidance for their management and support ecosystem restoration monitoring efforts.

Microclimate and Land Surface Temperature (LST) are important analytical variables used to understand complex oil palm agroforestry systems and their effects on biodiversity and ecosystem functions. In order to examine experimental effects of tree species richness (0, 1, 2, 3 or 6), plot size (25 m2, 100 m2, 400 m2, 1600 m2) and stand structural complexity on microclimate and Land Surface Temperature, related data were collected following a strict design. The experiment was carried out in the Jambi province, in Sumatra (Indonesia), as part of the collaborative project EFForTS [Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems]. Microclimate data collected using miniaturized data loggers combined with drone-based thermal data were considered within an oil palm plantation enriched with six target tree species. The timeframe considered for data analysis was 20th September 2017 to 26th September 2017. The experiment data can be used for comparison with data from conventional oil palm agroforestry systems in the tropics. They can more specifically be used as reference to assess microclimate and Land Surface Temperature patterns within similar agroforestry systems.

Despite islands contributing only 6.7% of land surface area, they harbor ~20% of the Earth’s biodiversity, but unfortunately also ~50% of the threatened species and 75% of the known extinctions since the European expansion around the globe. Due to their geological and geographic history and characteristics, islands act simultaneously as cradles of evolutionary diversity and museums of formerly widespread lineages—elements that permit islands to achieve an outstanding endemicity. Nevertheless, the majority of these endemic species are inherently vulnerable due to genetic and demographic factors linked with the way islands are colonized. Here, we stress the great variation of islands in their physical geography (area, isolation, altitude, latitude) and history (age, human colonization, human density). We provide examples of some of the most species rich and iconic insular radiations. Next, we analyze the natural vulnerability of the insular biota, linked to genetic and demographic factors as a result of founder events as well as the typically small population sizes of many island species. We note that, whereas evolution toward island syndromes (including size shifts, derived insular woodiness, altered dispersal ability, loss of defense traits, reduction in clutch size) might have improved the ability of species to thrive under natural conditions on islands, it has simultaneously made island biota disproportionately vulnerable to anthropogenic pressures such as habitat loss, overexploitation, invasive species, and climate change. This has led to the documented extinction of at least 800 insular species in the past 500 years, in addition to the many that had already gone extinct following the arrival of first human colonists on islands in prehistoric times. Finally, we summarize current scientific knowledge on the ongoing biodiversity loss on islands worldwide and express our serious concern that the current trajectory will continue to decimate the unique and irreplaceable natural heritage of the world’s islands. We conclude that drastic actions are urgently needed to bend the curve of the alarming rates of island biodiversity loss.

In tropical landscapes dominated by oil palm monocultures, scattered trees can contribute to biodiversity, regulate diverse ecosystem functions and deliver goods and services. However, basic quantitative information about such trees is often lacking. The objectives of our study were to identify the landscape-wide density and distribution patterns of scattered trees in an oil-palm-dominated area of Sumatra (Indonesia), and to estimate their size. The study area with the total of 1120 ha was situated in Jambi province in the lowlands of Sumatra. In 2016, the year of our assessment, 83% of the area was covered by oil palm monocultures including industrial and smallholder plantations; other land-use types included rubber plantations and secondary forests. An earlier land-use classification suggests that oil palm cultivation began before 1990 on 41% of the area. The study area was mapped in 2016 using a fixed-wing drone equipped with red-green-blue and near-infrared cameras. We counted all visible trees in the aerial image. In the entire study region, we detected 10.1 scattered trees/ha. In areas where oil palm plantations were established before 1990, the tree density was 67% lower than in the area where oil palm was introduced later. The median tree crown diameter was 4.5 m, which corresponds to an estimated diameter at breast height of 12 cm; thus, most trees were small-statured. The trees were spatially clustered and often aligned along roads and rivers. In conclusion, we found a considerable number of scattered, mostly small-statured trees. This suggests that most trees were young and disappeared before reaching larger dimensions. To ensure the survival of trees and further provision of related ecosystem services, scattered trees in the oil palm landscape need to be conserved and/or restored.

New technologies like ecoacoustic surveys promise time and cost efficiency for biodiversity assessments, serve as a basis for effective conservation policies, and are particularly appealing for remote and highly diverse tropical areas. Acoustic indices facilitate the analysis of large acoustic datasets but no consensus on their performance has been reached yet. We evaluated the efficacy of four acoustic indices (Acoustic Complexity Index, Acoustic Diversity Index, Acoustic Evenness Index, Acoustic Entropy) for sound data analysis and biodiversity assessments inside a national park and the agricultural mosaic landscape of north-eastern Madagascar, a global biodiversity hotspot. We used self-built sound recorders to continuously record soundscapes on 80 plots across seven land-use types (old-growth forest, forest fragment, forest–derived and fallow-derived vanilla agroforest, herbaceous and woody fallow, rice paddy) and compared index values between land–use types, assessed the correlation with bird species richness as measured by point counts, and related the acoustic indices to plot- and landscape-scale parameters. The Acoustic Diversity Index, Acoustic Evenness Index (inverse) and Acoustic Entropy were highest in old-growth forest and lowest for rice paddies and fallow land. Index values for structurally similar land-use types did not differ significantly from each other. The correlation of the three acoustic indices with bird species richness was strongest during daytime (R2≥0.30). Differences in the index values were best explained by land-use type and vegetation density. Our results showed that all investigated indices except the Acoustic Complexity Index were suitable biodiversity indicators for a tropical, agricultural landscape. Soundscape diversity was positively affected by plot-scale vegetation structure, emphasizing the importance of forests and particularly old-growth forest for conservation. We demonstrated that acoustic indices and sound recordings are a useful tool for assessing biodiversity in tropical agricultural mosaic landscapes. To realize the full potential of ecoacoustics in conservation, sampling guidelines and user-friendly analysis packages will be key to facilitate a wider implementation.