Cecilia A. L. Dahlsjo

Seasonal and spatial variations in Leaf Area Index (LAI, or plant area index, PAI) are challenging to delineate in tropical forests because the changes are often too subtle to be reliably detected. Many existing DHP software tools offer one‐click processing of all images using auto‐threshold segmentation (e.g. HemispheR, HemiPy and Hemisfer), but they produce results with large discrepancies. Some software (e.g. CAN‐EYE) requires manual tuning of each image, making large‐scale analysis impractical. We analysed 19,044 images from four tropical forest subtypes and found that using coding‐free AI software to process hemispherical images can significantly improve the consistency of canopy‐sky segmentation, thereby improving the detection of temporal and spatial variation of PAI. The results show that replacing the auto‐threshold segmentation with AI substantially reduced inter‐software disagreement, with the mean inter‐software range for PAI decreasing from 4.31 to 1.19, and delineating correct seasonal and spatial patterns. CAN‐EYE could identify the correct seasonal patterns but produced less accurate results than the CAN‐EYE‐AI integrated approach due to subjective bias. The high consistency achieved after AI integration enables reliable cross‐site and temporal comparisons. As users can combine the AI segmentation with other DHP software, our integrated, affordable and coding‐free method offers wide applicability and high consistency of PAI measurements, facilitating the advancement of tropical forest monitoring and research.

Effective environmental policies for the tropics depend on accurate, representative scientific data. However, there is strong evidence from particular disciplines and regions that existing research is patchily distributed. Here, we show that poor representation of sampling and citation in some biomes and across key environmental gradients from all disciplines for the entire tropics may lead to flawed scientific paradigms and inappropriate policy prescriptions. We map sampling locations and citations from 2 738 published studies in natural terrestrial tropical environments across all disciplines to identify gaps in field sampling effort and research attention. Five ecoregions – all in moist broadleaf forests – generate 22% of the total citations but cover only 3% of the tropical land area. By contrast, drier biomes with low tree cover account collectively for 57% of the tropical area but generate only 20% of total citations. Locations that are drier, colder, with greater plant species richness, lower tree cover and facing greater climate change extremes are under-sampled and under-cited. Our results will help to correct these imbalances to improve the scientific basis for environmental policies across the tropics.

Tropical forests cover large areas of equatorial Africa and play a substantial role in the global carbon cycle. However, there has been a lack of biometric measurements to understand the forests’ gross and net primary productivity (GPP, NPP) and their allocation. Here we present a detailed field assessment of the carbon budget of multiple forest sites in Africa, by monitoring 14 one-hectare plots along an aridity gradient in Ghana, West Africa. When compared with an equivalent aridity gradient in Amazonia, the studied West African forests generally had higher productivity and lower carbon use efficiency (CUE). The West African aridity gradient consistently shows the highest NPP, CUE, GPP, and autotrophic respiration at a medium-aridity site, Bobiri. Notably, NPP and GPP of the site are the highest yet reported anywhere for intact forests. Widely used data products substantially underestimate productivity when compared to biometric measurements in Amazonia and Africa. Our analysis suggests that the high productivity of the African forests is linked to their large GPP allocation to canopy and semi-deciduous characteristics.

Tree diseases are one of the major threats to forests worldwide. As the frequency and severity of disease outbreaks increase, effective prevention and mitigation strategies are urgently needed. Emerging methods are available to tackle this issue, however, trade-offs and potential ecological consequences should be considered for successful forest preservation.

2 Tropical forests cover large areas of equatorial Africa and play a significant role in the global carbon cycle. However, there has been a lack of in-situ measurements to understand the forests’ gross and net primary productivity (GPP and NPP) and their allocation. Here we present the first detailed field assessment of the carbon budget of multiple forest sites in Africa, by monitoring 14 one-hectare plots along an aridity gradient in Ghana. When compared with an equivalent aridity gradient in Amazonia using the same measurement protocol, the studied West African forests generally had higher GPP and NPP and lower carbon use efficiency (CUE). The West African aridity gradient consistently shows the highest NPP, CUE, GPP, and autotrophic respiration at a medium-aridity site, Bobiri. Notably, NPP and GPP of the site are the highest yet reported anywhere in the tropics using similar methods. Widely used data products (MODIS and FLUXCOM) substantially underestimate productivity when compared to in situ measurements, in Amazonia and especially in Africa. Our analysis suggests that the high productivity of the African forests is linked to their large GPP allocation to canopy and semi-deciduous characteristics, which may be a result of a seasonal climate coupled with high soil fertility.

Light in nature is complex and dynamic, and varies along spectrum, space, direction, and time. While both spectrally resolved measurements and spatially resolved measurements are widely available, spectrally and spatially resolved measurements are technologically more challenging. Here, we present a portable imaging system using off-the-shelf components to capture the full spherical light environment in a spectrally and spatially resolved fashion. The method relies on imaging the 4π-steradian light field reflected from a mirrored chrome sphere using a commercial hyperspectral camera (400-1000 nm) from multiple directions and an image-processing pipeline for extraction of the mirror sphere, removal of saturated pixels, correction of specular reflectance of the sphere, promotion to a high dynamic range, correction of misalignment of images, correction of intensity compression, erasure of the imaging system, unwrapping of the spherical images, filling-in blank regions, and stitching images collected from different angles. We applied our method to Wytham Woods, an ancient semi-natural woodland near Oxford, UK. We acquired a total of 168 images in two sites with low and high abundance of ash, leading to differences in canopy, leading to a total 14 hyperspectral light probes. Our image-processing pipeline corrected small (<3°) field-based misalignment adequately. Our novel hyperspectral imaging method is adapted for field conditions and opens up novel opportunities for capturing the complex and dynamic nature of the light environment.

Light in nature is complex and dynamic, and varies along spectrum, space, direction, and time. While both spectrally resolved measurements and spatially resolved measurements are widely available, spectrally and spatially resolved measurements are technologically more challenging. Here, we present a portable imaging system using off-the-shelf components to capture the full spherical light environment in a spectrally and spatially resolved fashion. The method relies on imaging the 4 π -steradian light field reflected from a mirrored chrome sphere using a commercial hyperspectral camera (400-1000 nm) from multiple directions and an image-processing pipeline for extraction of the mirror sphere, removal of saturated pixels, correction of specular reflectance of the sphere, promotion to a high dynamic range, correction of misalignment of images, correction of intensity compression, erasure of the imaging system, unwrapping of the spherical images, filling-in blank regions, and stitching images collected from different angles. We applied our method to Wytham Woods, an ancient semi-natural woodland near Oxford, UK. We acquired a total of 168 images in two sites with low and high abundance of ash, leading to differences in canopy, leading to a total 14 hyperspectral light probes. Our image-processing pipeline corrected small ( < 3 ^° ) field-based misalignment adequately. Our novel hyperspectral imaging method is adapted for field conditions and opens up novel opportunities for capturing the complex and dynamic nature of the light environment.

There are over one million described invertebrate species on Earth, the majority of which are likely to inhabit the highly biodiverse rain forests around the equator. These are some of the most vulnerable ecosystems on Earth due to the pressures of deforestation and climate change with many of their inhabitants at risk of extinction. Invertebrates play a major role in ecosystem functioning from decomposition and nutrient cycling to herbivory and pollination; however, while our understanding of these roles is improving, we are far from being able to predict the consequences of further deforestation, climate change, and biodiversity loss due to the lack of comparative data and the high proportion of species which remain to be discovered. As we move into an era of increased pressure on old‐growth habitats and biodiversity, it is imperative that we understand how changes to invertebrate communities, and the extinction of species, affect ecosystems. Innovative and comprehensive methods that approach these issues are needed. Here, we highlight priorities for future tropical terrestrial invertebrate research such as the efficiency of sustainable land management, exploration of innovative methods for better understanding of invertebrate ecology and behavior, and quantifying the role of invertebrates in ecosystem functioning.

It has been estimated that there are seven million terrestrial arthropod species on Earth consisting of 6.1 million species of insects, 1.5 million of which are beetles. Tropical forests hold a majority of these species, yet few such places have been adequately sampled for alpha diversity, and there remains even more uncertainty about beta diversity. From an ecological point of view, it is the functional role of organisms within ecosystems that is the particular focus. It has been customary to classify invertebrates within ecosystems in terms of their trophic roles, but it is also useful to consider their roles in networks. In broad terms, we can classify these networks on the grounds of their basal resources. Those based directly on the photosynthetic products of plants are so‐called “green” food webs, and those based on dead and dying plant material are “brown” food webs. Here, we principally discuss the diversity and functional roles of the invertebrates in tropical terrestrial ecosystems. New sampling and analytical techniques, an expanded set of focal taxa, and an enhanced concern with interactions and processes hold the promise of a productive future for invertebrate studies in the tropics. These will not only add to general understanding of the dynamics of tropical ecosystems but will also provide powerful tools for monitoring and responding to environmental change.