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Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants.
Forest species are affected by macroclimate, however, the microclimatic variability can be more extreme and change through climate change. Fungal fruiting community composition was affected by microclimatic differences. Here we ask whether differences in the fruiting community can be explained by morphological traits of the fruit body, which may help endure harsh conditions. We used a dead wood experiment and macrofungal fruit body size, color, and toughness. We exposed logs of two host tree species under closed and experimentally opened forest canopies in a random-block design for four years and identified all visible fruit bodies of two fungal lineages (Basidio- and Ascomycota). We found a consistently higher proportion of tough-fleshed species in harsher microclimates under open canopies. Although significant, responses of community fruit body size and color lightness were inconsistent across lineages. We suggest the toughness-protection hypothesis, stating that tough-fleshed fruit bodies protect from microclimatic extremes by reducing dehydration. Our study suggests that the predicted increase of microclimatic harshness with climate change will likely decrease the presence of soft-fleshed fruit bodies. Whether harsh microclimates also affect the mycelium of macrofungi with different fruit body morphology would complement our findings and increase predictability under climate change.
The degradation of natural forests to modified forests threatens subtropical and tropical biodiversity worldwide. Yet, species responses to forest modification vary considerably. Furthermore, effects of forest modification can differ, whether with respect to diversity components (taxonomic or phylogenetic) or to local (α-diversity) and regional (β-diversity) spatial scales. This real-world complexity has so far hampered our understanding of subtropical and tropical biodiversity patterns in human-modified forest landscapes. In a subtropical South African forest landscape, we studied the responses of three successive plant life stages (adult trees, saplings, seedlings) and of birds to five different types of forest modification distinguished by the degree of within-forest disturbance and forest loss. Responses of the two taxa differed markedly. Thus, the taxonomic α-diversity of birds was negatively correlated with the diversity of all plant life stages and, contrary to plant diversity, increased with forest disturbance. Conversely, forest disturbance reduced the phylogenetic α-diversity of all plant life stages but not that of birds. Forest loss neither affected taxonomic nor phylogenetic diversity of any taxon. On the regional scale, taxonomic but not phylogenetic β-diversity of both taxa was well predicted by variation in forest disturbance and forest loss. In contrast to adult trees, the phylogenetic diversity of saplings and seedlings showed signs of contemporary environmental filtering. In conclusion, forest modification in this subtropical landscape strongly shaped both local and regional biodiversity but with contrasting outcomes. Phylogenetic diversity of plants may be more threatened than that of mobile species such as birds. The reduced phylogenetic diversity of saplings and seedlings suggests losses in biodiversity that are not visible in adult trees, potentially indicating time-lags and contemporary shifts in forest regeneration. The different responses of taxonomic and phylogenetic diversity to forest modifications imply that biodiversity conservation in this subtropical landscape requires the preservation of natural and modified forests.
The most basic behavioural states of animals can be described as active or passive. However, while high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which the automated VHF radio-tracking of small vertebrates fitted with lightweight transmitters (< 0.2 g) is used to distinguish between active and passive behavioural states.
A dataset containing > 3 million VHF signals was used to train and test a random forest model in the assignment of either active or passive behaviour to individuals from two forest-dwelling bat species (Myotis bechsteinii (n = 50) and Nyctalus leisleri (n = 20)). The applicability of the model to other taxonomic groups was demonstrated by recording and classifying the behaviour of a tagged bird and by simulating the effect of different types of vertebrate activity with the help of humans carrying transmitters. The random forest model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F-score 0.96–0.98).
The utility of the model in tackling ecologically relevant questions was demonstrated in a study of the differences in the daily activity patterns of the two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that significant differences in the timing of species activity according to ecological preferences or seasonality can be distinguished using our method.
Our approach enables the assignment of VHF signal patterns to fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radio-tracking method, we provide the trained random forest models together with an R-package that includes all necessary data-processing functionalities. In combination with state-of-the-art open-source automated radio-tracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
he most basic behavioural states of animals can be described as active or passive. While high-resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g).
We used a dataset containing >3 million signals from very-high-frequency (VHF) telemetry from two forest-dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF-tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98).
We provide an ecological case-study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night-time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method.
Our approach can classify VHF-signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state-of-the-art open-source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.
Although macroecology is a well-established field, much remains to be learned about the large-scale variation of fungal traits. We conducted a global analysis of mean fruit body size of 59 geographical regions worldwide, comprising 5340 fungal species exploring the response of fruit body size to latitude, resource availability and temperature. The results showed a hump-shaped relationship between mean fruit body size and distance to the equator. Areas with large fruit bodies were characterised by a high seasonality and an intermediate mean temperature. The responses of mutualistic species and saprotrophs were similar. These findings support the resource availability hypothesis, predicting large fruit bodies due to a seasonal resource surplus, and the thermoregulation hypothesis, according to which small fruit bodies offer a strategy to avoid heat and cold stress and therefore occur at temperature extremes. Fruit body size may thus be an adaptive trait driving the large-scale distribution of fungal species.
We recently described a positive feedback loop connecting c-MYC, NAMPT, DBC1 and SIRT1 that contributes to unrestricted cancer cell proliferation. Here we determine the relevance of the loop for serrated route intestinal tumorigenesis using genetically well-defined BrafV600E and K-rasG12D mouse models. In both models we show that c-MYC and SIRT1 protein expression increased through progression from hyperplasia to invasive carcinomas and metastases. It correlated with high NAMPT expression and was directly associated to activation of the oncogenic drivers. Assessing functional and molecular consequences of pharmacological interference with factors of the loop, we found that inhibition of NAMPT resulted in apoptosis and reduced clonogenic growth in human BRAF-mutant colorectal cancer cell lines and patient-derived tumoroids. Blocking SIRT1 activity was only effective when combined with a PI3K inhibitor, whereas the latter antagonized the effects of NAMPT inhibition. Interfering with the positive feedback loop was associated with down-regulation of c-MYC and temporary de-repression of TP53, explaining the anti-proliferative and pro-apoptotic effects. In conclusion we show that the c-MYC-NAMPT-DBC1-SIRT1 positive feedback loop contributes to murine serrated tumor progression. Targeting the feedback loop exerted a unique, dual therapeutic effect of oncoprotein inhibition and tumor suppressor activation. It may therefore represent a promissing target for serrated colorectal cancer, and presumably for other cancer types with deregulated c-MYC.