A research framework for projecting ecosystem change in highly diverse tropical mountain ecosystems

Simulation of latent heat flux over a high altitude pasture in the tropical Andes with a coupled land surface framework

Latent heat flux is a central element of land-atmosphere interactions under climate change. Knowledge is particularly poor in the biodiversity hotspot of the Andes, where heat flux measurements using eddy covariance stations are scarce and land surface models (LSMs) often oversimplify the complexity of the ecosystems. The main objective of this study is to perform latent heat flux simulations for the tropical South Eastern (SE) Ecuadorian Andes using a coupled LSM framework, and to test the performance with heat flux and soil moisture data collected from a tropical high-altitude pasture. Prior to testing, we applied multi-criteria model calibration of sensitive model parameters, focusing on improving simulated soil water conditions and radiation fluxes as a prerequisite for proper heat flux simulations. The most sensitive parameters to improve soil moisture and radiation flux simulations were soil porosity, saturated hydraulic conductivity, leaf area index, soil colour and NIR (Near Infrared) leaf optical properties. The best calibrated model run showed a very good performance for half-hourly latent heat flux simulations with an R2 of 0.8 and an RMSE of 34.0 W m-2, outperforming simulations with uncalibrated and uncoupled LSM simulations in comparable areas. The slight overall overestimation in the simulated latent heat flux can be related to (i) simulation uncertainties in the canopy heat budget, (ii) an imbalance in the observed flux data and (iii) slight overestimations in the simulated soil moisture. Although our study focuses on latent heat fluxes and their relation to simulated radiation fluxes and soil moisture, model outputs of sensible heat fluxes were also discussed. The systematic overestimation of sensible heat flux in the model seems to be mainly a result of overestimated canopy temperatures. The improved simulation for latent heat flux has a high translational potential to support land use strategies in the tropical Andes under climate change.

The diversity pattern of soil bacteria in the rhizosphere of different plants in mountain ecosystems

Research on the composition and diversity of rhizosphere microbial communities of different plant species can help to identify important microbial functional groups or functional potentials, which is of great significance for vegetation restoration and ecological reconstruction. To provide scientific basis for the management of mountain ecosystem, the diversity pattern of rhizosphere bacterial community was investigated using 16 S rRNA high-throughput sequencing method among different host plants (Cirsium japonicum, Artemisia annua, Descurainia sophia, Lepidium apetalum, Phlomis umbrosa, and Carum carvi) in Tomur Peak National Nature Reserve, China. The results showed that the richness and diversity of rhizosphere bacteria were highest in Descurainia sophia, and lowest in Lepidium apetalum. Pseudomonadota, Acidobacteriota, and Actinomycetota were the common dominant phyla, and Sphingomonas was the predominant genus. Furthermore, there were some specific genera in different plants. The relative abundance of non-dominant genera varied among the plant species. Canonical correspondence analysis indicated that available potassium (AK), total phosphorus (TP), total potassium (TK), and soil organic matter (SOM) were the main drivers of bacterial community structure. Based on PICRUSt functional prediction, the bacterial communities in all samples encompass six primary metabolic pathways and 47 secondary metabolic pathways. The major secondary metabolic pathways (with a relative abundance of functional gene sequences > 3%) include 15 categories. Co-occurrence network analysis revealed differences in bacterial composition and interactions among different modules, with rhizosphere microorganisms of different plants exhibiting distinct functional advantages. This study elucidates the distribution patterns of rhizosphere microbial community diversity in mountain ecosystems, which provides theoretical guidance for the ecological protection of mountain soil based on the microbiome.

A Data Storage, Analysis, and Project Administration Engine (TMFdw) for Small- to Medium-Size Interdisciplinary Ecological Research Programs with Full Raster Data Capabilities

Over almost 20 years, a data storage, analysis, and project administration engine (TMFdw) has been continuously developed in a series of several consecutive interdisciplinary research projects on functional biodiversity of the southern Andes of Ecuador. Starting as a “working database”, the system now includes program management modules and literature databases, which are all accessible via a web interface. Originally designed to manage data in the ecological Research Unit 816 (SE Ecuador), the open software is now being used in several other environmental research programs, demonstrating its broad applicability. While the system was mainly developed for abiotic and biotic tabular data in the beginning, the new research program demands full capabilities to work with area-wide and high-resolution big models and remote sensing raster data. Thus, a raster engine was recently implemented based on the Geo Engine technology. The great variety of pre-implemented desktop GIS-like analysis options for raster point and vector data is an important incentive for researchers to use the system. A second incentive is to implement use cases prioritized by the researchers. As an example, we present machine learning models to generate high-resolution (30 m) microclimate raster layers for the study area in different temporal aggregation levels for the most important variables of air temperature, humidity, precipitation, and solar radiation. The models implemented as use cases outperform similar models developed in other research programs.

Effects of leaf traits of tropical trees on the abundance and body mass of herbivorous arthropod communities

In tropical forests, herbivorous arthropods remove between 7% up to 48% of leaf area, which has forced plants to evolve defense strategies. These strategies influence the palatability of leaves. Palatability, which reflects a syndrome of leaf traits, in turn influences both the abundance and the mean body mass not only of particular arthropod taxa but also of the total communities. In this study, we tested two hypotheses: (H1) The abundance of two important chewer guilds ('leaf chewers' and 'rostrum chewers'), dominant components of arthropod communities, is positively related to the palatability of host trees. (H2) Lower palatability leads to an increased mean body mass of chewers (Jarman-Bell principle). Arthropods were collected by fogging the canopies of 90 tropical trees representing 31 species in three plots at 1000 m and three at 2000 m a.s.l. Palatability was assessed by measuring several 'leaf traits' of each host tree and by conducting a feeding trial with the generalist herbivore Gryllus assimilis (Orthoptera, Gryllidae). Leaf traits provided partial support for H1, as abundance of leaf chewers but not of rostrum chewers was positively affected by the experimentally estimated palatability. There was no support for H2 as neither leaf traits nor experimentally estimated palatability affected the mean body mass of leaf chewers. The mean body mass of rostrum chewers was positively related to palatability. Thus, leaf traits and experimentally estimated palatability influenced the abundance and mean body mass of chewing arthropods on the community level. However, the data were not consistent with the Jarman-Bell principle. Overall, our results suggest that the palatability of leaves is not among the dominant factors influencing abundance and mean body mass of the community of chewing arthropod herbivores. If other factors, such as the microclimate, predation or further (a-)biotic interactions are more important has to be analyzed in refined studies.

Impacts of anthropogenic climate change on tropical montane forests: an appraisal of the evidence

In spite of their small global area and restricted distributions, tropical montane forests (TMFs) are biodiversity hotspots and important ecosystem services providers, but are also highly vulnerable to climate change. To protect and preserve these ecosystems better, it is crucial to inform the design and implementation of conservation policies with the best available scientific evidence, and to identify knowledge gaps and future research needs. We conducted a systematic review and an appraisal of evidence quality to assess the impacts of climate change on TMFs. We identified several skews and shortcomings. Experimental study designs with controls and long-term (≥10 years) data sets provide the most reliable evidence, but were rare and gave an incomplete understanding of climate change impacts on TMFs. Most studies were based on predictive modelling approaches, short-term (<10 years) and cross-sectional study designs. Although these methods provide moderate to circumstantial evidence, they can advance our understanding on climate change effects. Current evidence suggests that increasing temperatures and rising cloud levels have caused distributional shifts (mainly upslope) of montane biota, leading to alterations in biodiversity and ecological functions. Neotropical TMFs were the best studied, thus the knowledge derived there can serve as a proxy for climate change responses in under-studied regions elsewhere. Most studies focused on vascular plants, birds, amphibians and insects, with other taxonomic groups poorly represented. Most ecological studies were conducted at species or community levels, with a marked paucity of genetic studies, limiting understanding of the adaptive capacity of TMF biota. We thus highlight the long-term need to widen the methodological, thematic and geographical scope of studies on TMFs under climate change to address these uncertainties. In the short term, however, in-depth research in well-studied regions and advances in computer modelling approaches offer the most reliable sources of information for expeditious conservation action for these threatened forests.

Biodiversity and ecosystem functions depend on environmental conditions and resources rather than the geodiversity of a tropical biodiversity hotspot

Biodiversity and ecosystem functions are highly threatened by global change. It has been proposed that geodiversity can be used as an easy-to-measure surrogate of biodiversity to guide conservation management. However, so far, there is mixed evidence to what extent geodiversity can predict biodiversity and ecosystem functions at the regional scale relevant for conservation planning. Here, we analyse how geodiversity computed as a compound index is suited to predict the diversity of four taxa and associated ecosystem functions in a tropical mountain hotspot of biodiversity and compare the results with the predictive power of environmental conditions and resources (climate, habitat, soil). We show that combinations of these environmental variables better explain species diversity and ecosystem functions than a geodiversity index and identified climate variables as more important predictors than habitat and soil variables, although the best predictors differ between taxa and functions. We conclude that a compound geodiversity index cannot be used as a single surrogate predictor for species diversity and ecosystem functions in tropical mountain rain forest ecosystems and is thus little suited to facilitate conservation management at the regional scale. Instead, both the selection and the combination of environmental variables are essential to guide conservation efforts to safeguard biodiversity and ecosystem functions.

Nutrient cycling drives plant community trait assembly and ecosystem functioning in a tropical mountain biodiversity hotspot

Community trait assembly in highly diverse tropical rainforests is still poorly understood. Based on more than a decade of field measurements in a biodiversity hotspot of southern Ecuador, we implemented plant trait variation and improved soil organic matter dynamics in a widely used dynamic vegetation model (the Lund-Potsdam-Jena General Ecosystem Simulator, LPJ-GUESS) to explore the main drivers of community assembly along an elevational gradient. In the model used here (LPJ-GUESS-NTD, where NTD stands for nutrient-trait dynamics), each plant individual can possess different trait combinations, and the community trait composition emerges via ecological sorting. Further model developments include plant growth limitation by phosphorous (P) and mycorrhizal nutrient uptake. The new model version reproduced the main observed community trait shift and related vegetation processes along the elevational gradient, but only if nutrient limitations to plant growth were activated. In turn, when traits were fixed, low productivity communities emerged due to reduced nutrient-use efficiency. Mycorrhizal nutrient uptake, when deactivated, reduced net primary production (NPP) by 61-72% along the gradient. Our results strongly suggest that the elevational temperature gradient drives community assembly and ecosystem functioning indirectly through its effect on soil nutrient dynamics and vegetation traits. This illustrates the importance of considering these processes to yield realistic model predictions.

Leaf trait variation in species-rich tropical Andean forests

Screening species-rich communities for the variation in functional traits along environmental gradients may help understanding the abiotic drivers of plant performance in a mechanistic way. We investigated tree leaf trait variation along an elevation gradient (1000-3000 m) in highly diverse neotropical montane forests to test the hypothesis that elevational trait change reflects a trend toward more conservative resource use strategies at higher elevations, with interspecific trait variation decreasing and trait integration increasing due to environmental filtering. Analysis of trait variance partitioning across the 52 tree species revealed for most traits a dominant influence of phylogeny, except for SLA, leaf thickness and foliar Ca, where elevation was most influential. The community-level means of SLA, foliar N and Ca, and foliar N/P ratio decreased with elevation, while leaf thickness and toughness increased. The contribution of intraspecific variation was substantial at the community level in most traits, yet smaller than the interspecific component. Both within-species and between-species trait variation did not change systematically with elevation. High phylogenetic diversity, together with small-scale edaphic heterogeneity, cause large interspecific leaf trait variation in these hyper-diverse Andean forests. Trait network analysis revealed increasing leaf trait integration with elevation, suggesting stronger environmental filtering at colder and nutrient-poorer sites.