Aim
The mosaic of savannas that persists in the forest‐dominant Congo Basin is thought to be palaeoclimatic relics, but past biogeographical processes that have formed and maintained these systems ...are poorly understood. Here, we explored the post‐Pleistocene biogeography of Gabon's savannas using termites as biological indicators to understand historical and mechanistic factors influencing present‐day termite communities in the country's extant savannas.
Location
Gabon, Central Africa.
Taxon
Blattodea: Termitoidae.
Methods
Using standardised transect methods, we sampled termite communities in four disjunct modern savanna areas of Gabon: the centre (Lopé), the southeast (Batéké) and the south (Mayombe North and South). Termites at Lopé were collected in three habitats (annually burned savannas, savannas with a depressed fire regime and forest). We used DNA barcoding of the COII region to identify termite species and compared abundance, species richness and community composition across areas and habitats.
Results
Community composition differed greatly between Lopé and both Batéké and Mayombe savannas with Lopé being exceptionally depauperate and lacking characteristic savanna species. Within Lopé, termite abundance and diversity was highest in forests and lowest in annually burned savannas, with a gradual change in species composition across the forest–savanna gradient associated with fire history.
Main Conclusions
The absence of savanna typical species in Lopé savannas challenges current assumptions that these savannas were linked to the south/southeastern savannas during the Pleistocene and suggests a different evolutionary history. Lopé savannas may instead have opened as an isolated grassland and never have been contiguous with neighbouring savannas, or were isolated soon after forest expansion began and have now lost savanna‐typical species. Furthermore, the patterns of termite community composition in fire suppressed savannas support a hypothesis of rapid change driven by fire frequency where either fire suppression or infrequent burning over 23 years has meant savannas have become ecologically much more forest‐like.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Overexploitation is one of the main pressures driving wildlife closer to extinction, yet broad‐scale data to evaluate species’ declines are limited. Using African pangolins (Family: Pholidota) as a ...case study, we demonstrate that collating local‐scale data can provide crucial information on regional trends in exploitation of threatened species to inform conservation actions and policy. We estimate that 0.4‐2.7 million pangolins are hunted annually in Central African forests. The number of pangolins hunted has increased by ∼150% and the proportion of pangolins of all vertebrates hunted increased from 0.04% to 1.83% over the past four decades. However, there were no trends in pangolins observed at markets, suggesting use of alternative supply chains. The price of giant (Smutsia gigantea) and arboreal (Phataginus sp.) pangolins in urban markets has increased 5.8 and 2.3 times respectively, mirroring trends in Asian pangolins. Efforts and resources are needed to increase law enforcement and population monitoring, and investigate linkages between subsistence hunting and illegal wildlife trade.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Summary
Changes in phenology are an inevitable result of climate change, and will have wide‐reaching impacts on species, ecosystems, human society and even feedback onto climate. Accurate ...understanding of phenology is important to adapt to and mitigate such changes. However, analysis of phenology globally has been constrained by lack of data, dependence on geographically limited, non‐circular indicators and lack of power in statistical analyses.
To address these challenges, especially for the study of tropical phenology, we developed a flexible and robust analytical approach – using Fourier analysis with confidence intervals – to objectively and quantitatively describe long‐term observational phenology data even when data may be noisy. We then tested the power of this approach to detect regular cycles under different scenarios of data noise and length using both simulated and field data.
We use Fourier analysis to quantify flowering phenology from newly available data for 856 individual plants of 70 species observed monthly since 1986 at Lopé National Park, Gabon. After applying a confidence test, we find that 59% of the individuals have regular flowering cycles, and 88% species flower annually. We find time‐series length to be a significant predictor of the likelihood of confidently detecting a regular cycle from the data. Using simulated data we find that cycle regularity has a greater impact on detecting phenology than event detectability. Power analysis of the Lopé field data shows that at least 6 years of data are needed for confident detection of the least noisy species, but this varies and is often >20 years for the most noisy species.
There are now a number of large phenology datasets from the tropics, from which insights into current regional and global changes may be gained, if flexible and quantitative analytical approaches are used. However, consistent long‐term data collection is costly and requires much effort. We provide support for the importance of such research and give suggestions as to how to avoid erroneous interpretation of shorter length datasets and maximise returns from long‐term observational studies.
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Global change is expected to increase savanna woody encroachment as well as fire spreading into forest. Forest–savanna ecotones are the frontier of these processes and can thus either mitigate or ...enhance the effects of global change. However, the ecology of the forest–savanna ecotone is poorly understood. In this study, we determined whether a distinct ecotonal tree community existed between forest and savanna. We then evaluated whether the ecotonal tree community was more likely to facilitate fire spreading into the forest, woody encroachment of the savanna or the stabilisation of both forest and savanna parts of the landscape.
We sampled 28 vegetation transects across forest–savanna ecotones in a central African forest–savanna mosaic. We collected data on the size and species of all established (basal diameter >3 cm) trees in each transect. Split moving window dissimilarity analysis detected the location of borders delineating savanna, ecotone and forest tree communities. We assessed whether the ecotonal tree community was likely to facilitate fire spreading into the forest by burning experimental fires and evaluating shade and grass biomass along the transects. To decide whether the ecotone was likely to facilitate woody encroachment of the savanna, we evaluated if ecotonal tree species were forest pioneers.
A compositionally distinct and spatially extensive ecotonal tree community existed between forest and savanna. The ecotonal tree community did not promote fire spreading into forest and instead acted as a fire buffer, shading out flammable grass biomass from the understorey and protecting the forest from 95% of savanna fires. The ecotone helped stabilise the forest–savanna mosaic by allowing the fire‐dependant savanna to burn without exposing the fire‐sensitive forest to lethal temperatures.
The ecotonal tree community was comprised of many forest pioneer species that will promote woody encroachment in the savanna, especially if fire frequency is decreased.
Synthesis. A distinct fire‐buffering ecotonal tree community in this forest–savanna mosaic landscape illustrated that savanna fires are unlikely to compromise forest integrity. Conversely, suppression of fire in this landscape will likely lead to loss of savanna as the ecotone becomes the frontier of woody encroachment. Regular burning is essential for the preservation of this forest–savanna mosaic.
Abstraite
Le réchauffement climatique globale pourrait permettre l'expansion des savanes ligneuses sur les écosystèmes forestiers et ainsi augmenté les surfaces de propagation des feux à l'intérieur des forêts. Les mosaïque forêt‐savane sont caractérisées par une frontière, ou écotone, démarquant ces deux compartiments. Cet écotone particulier peut alors mitiger ou amplifier les effets de ce réchauffement planétaire. Néanmoins, l’écologie de cet écotone de transition forêt‐savane est jusqu'alors peut étudier. Dans cette étude, nous avons déterminer l'assemblage des espèces ligneuses qui forment une communauté végétale distincte, spécifique à cet écotone. Nous avons ensuite évalué et testé les propriétés de cette communauté dans le ralentissement ou la propagation des feux de savane en forêt ; son impact sur la dynamique de cette mosaïque forêt‐savane, avec soit une colonisation de la forêt vers la savane ou une stabilisation de ces deux composantes paysagères.
Nous avons échantillonné vingt‐huit transects à travers ce type d’écotones de transition dans une mosaïque forêt‐savane d'Afrique centrale. Nous avons recueilli des données sur la taille et les espèces de tous les arbres de plus de trois centimètres de diamètre recensés le long de chaque transects. Notre analyse de "Split moving window dissimilarity" le long de ces transects nous a permis de détecter les limites précises délimitant la communauté végétale de savane, celle propre à l’écotone et celle de la forêt. Pour observer si la communauté végétale spécifique à l’écotone de transition était susceptible de faciliter la propagation du feu dans la forêt, nous avons provoqué des feux expérimentaux et évalué l'ombre et la biomasse d'herbe le long des transects. Pour déterminer si l'écotone était susceptible de faciliter l'avancement de la forêt sur la savane, nous avons évalué si les espèces d'arbres formant la communauté végétale spécifique à l’écotone de transition étaient des espèces pionnières ou colonisatrice.
Notre étude met en lumière l'existence d'un assemblage d'espèces ligneuses formant une communauté spécifique à cet écotone de transition forêt‐savane. Cette communauté n'a pas favorisé la propagation du feu en forêt et a au contraire agi comme un coupe‐feu grâce à l'ombre qu'elle projette sur la biomasse d'herbe potentiellement inflammable du sous‐bois. Dans notre étude, l’écotone testé a protégé la forêt de 95% des feux de savane expérimentaux. Cet écotone permet de stabiliser la dynamique de la mosaïque forêt‐savane ; en permettant à la savane de se régénérer par brûlis et en protégeant la forêt des incendies et des températures létales pour les arbres.
La communauté d'espèces végétales de l’écotone était composée de nombreuses espèces pionnières forestières qui favorisent l'avancement de la forêt sur la savane, surtout si la fréquence des feux est diminuée.
Synthèse. Dans ce paysage de mosaïque forêt‐savane, une communauté d'espèces végétales distincte propre à l’écotone de transition existe. Cette communauté agit comme un tampon contre l'impact du feu sur la forêt. Notre étude démontre alors que les feux de savane sont peu susceptibles de compromettre l'intégrité de la forêt. Inversement, la suppression des incendies dans ce paysage entraînera alors une perte de l'écosystème de savane car l'écotone permet le recrutement d'espèces ligneuses colonisatrices, favorisant l'expansion de la forêt. Un brûlage régulier semble donc être requis pour la préservation de cette mosaïque forêt‐savane.
A distinct fire‐buffering ecotonal tree community in this forest–savanna mosaic landscape illustrated that savanna fires are unlikely to compromise forest integrity. Conversely, suppression of fire in this landscape will likely lead to loss of savanna as the ecotone becomes the frontier of woody encroachment. Regular burning is essential for the preservation of this forest–savanna mosaic.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Efforts to preserve, protect and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. ...Real‐time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real‐time analysis where there is no reliable cellular or WiFi connectivity.
We modified an off‐the‐shelf camera trap (Bushnell™) and customised existing open‐source hardware to create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end‐user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed‐canopy forest in Gabon, Central Africa. All reference materials required to build the system are provided in open‐source repositories.
Results show the system can operate for a minimum of 3 months without intervention when capturing a median of 17.23 images per day. The median time‐difference between image capture and receiving an alert was 7.35 min, though some outliers showed delays of 5‐days or more when the system was incorrectly positioned and unable to connect to the Iridium network.
We anticipate significant developments in this field and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real‐time use cases including real‐time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas.
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Phenology is a key component of ecosystem function and is increasingly included in assessments of ecological change. We consider how existing, and emerging, tropical phenology monitoring programs can ...be made most effective by investigating major sources of noise in data collection at a long-term study site. Researchers at Lopé NP, Gabon, have recorded monthly crown observations of leaf, flower and fruit phenology for 88 plant species since 1984. For a subset of these data, we first identified dominant regular phenological cycles, using Fourier analysis, and then tested the impact of observation uncertainty on cycle detectability, using expert knowledge and generalized linear mixed modeling (827 individual plants of 61 species). We show that experienced field observers can provide important information on major sources of noise in data collection and that observation length, phenophase visibility and duration are all positive predictors of cycle detectability. We find that when a phenological event lasts > 4 wk, an additional 10 yr of data increases cycle detectability by 114 percent and that cycle detectability is 92 percent higher for the most visible events compared to the least. We also find that cycle detectability is four times as high for flowers compared to ripe fruits after 10 yr. To maximize returns in the short-term, resources for long-term monitoring of phenology should be targeted toward highly visible phenophases and events that last longer than the observation interval. In addition, programs that monitor flowering phenology are likely to accurately detect regular cycles more quickly than those monitoring fruits, thus providing a baseline for future assessments of change.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NMLJ, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Ecological data are collected over vast geographic areas using digital sensors such as camera traps and bioacoustic recorders. Camera traps have become the standard method for surveying many ...terrestrial mammals and birds, but camera trap arrays often generate millions of images that are time‐consuming to label. This causes significant latency between data collection and subsequent inference, which impedes conservation at a time of ecological crisis. Machine learning algorithms have been developed to improve the speed of labelling camera trap data, but it is uncertain how the outputs of these models can be used in ecological analyses without secondary validation by a human.
Here, we present our approach to developing, testing and applying a machine learning model to camera trap data for the purpose of achieving fully automated ecological analyses. As a case‐study, we built a model to classify 26 Central African forest mammal and bird species (or groups). The model generalizes to new spatially and temporally independent data (n = 227 camera stations, n = 23,868 images), and outperforms humans in several respects (e.g. detecting ‘invisible’ animals). We demonstrate how ecologists can evaluate a machine learning model's precision and accuracy in an ecological context by comparing species richness, activity patterns (n = 4 species tested) and occupancy (n = 4 species tested) derived from machine learning labels with the same estimates derived from expert labels.
Results show that fully automated species labels can be equivalent to expert labels when calculating species richness, activity patterns (n = 4 species tested) and estimating occupancy (n = 3 of 4 species tested) in a large, completely out‐of‐sample test dataset. Simple thresholding using the Softmax values (i.e. excluding ‘uncertain’ labels) improved the model's performance when calculating activity patterns and estimating occupancy but did not improve estimates of species richness.
We conclude that, with adequate testing and evaluation in an ecological context, a machine learning model can generate labels for direct use in ecological analyses without the need for manual validation. We provide the user‐community with a multi‐platform, multi‐language graphical user interface that can be used to run our model offline.
Résumé
Des données écologiques sont collectées sur de vastes zones géographiques à l'aide de capteurs numériques tels que des caméras‐pièges et des enregistreurs bioacoustique. Les caméras‐pièges sont devenus la méthode standard pour étudier et suivre de nombreux mammifères terrestres et oiseaux, mais les réseaux de caméras‐pièges génèrent souvent des millions d'images dont l'identification prend beaucoup de temps. Cela entraîne un temps de latence important entre la collecte des données et l'inférence qui en découle, ce qui entrave la conservation en période de crise écologique. Des algorithmes d'apprentissage automatique ont été développés pour améliorer la vitesse d'identification des données des caméras‐pièges, mais il n'est pas certain que les résultats de ces modèles puissent être utilisés dans des analyses écologiques sans validation par un humain.
Ici, nous présentons notre approche pour développer, tester et appliquer un modèle d'apprentissage automatique aux données des caméras‐pièges dans le but de réaliser des analyses écologiques entièrement automatisées. Comme cas d'étude, nous avons construit un modèle permettant de classer 26 espèces (ou groupes) de mammifères et d'oiseaux des forêts d'Afrique centrale. Le modèle s'applique à de nouvelles données indépendantes dans l'espace et dans le temps (n = 227 stations de caméras‐pièges, n = 23,868 images), et surpasse les humains à plusieurs égards (par exemple, en détectant les animaux ‘invisibles’). Nous démontrons comment les écologues peuvent évaluer la précision et l'exactitude d'un modèle d'apprentissage automatique dans un contexte écologique en comparant la richesse spécifique, les modèles d'activité (n = 4 espèces testées) et d'occupation (n = 4 espèces testées) dérivés des identifications issues du modèle d'apprentissage automatique avec les mêmes estimations dérivées des identifications d'experts.
Les résultats montrent que l'identification entièrement automatisées des espèces peut être équivalentes à celle d'experts pour calculer la richesse spécifique, les modèles d'activité (n = 4 espèces testées) et estimer l'occupation (n = 3 des 4 espèces testées) dans un grand jeu de données d'essai complètement hors échantillon. Une simple valeur Softmax seuil (i.e. excluant les identifications ‘incertaines’) a amélioré la performance du modèle lors du calcul des modèles d'activité et de l'estimation de l'occupation, mais n'a pas amélioré les estimations de la richesse en espèces.
Nous concluons qu'avec des tests et des évaluations adéquats dans un contexte écologique, un modèle d'apprentissage automatique peut générer des identifications destinées à être utilisés directement dans des analyses écologiques, sans qu'il soit nécessaire de les valider manuellement. Nous fournissons à la communauté des utilisateurs une interface graphique multi‐plateforme et multilingue qui peut être utilisée pour faire fonctionner notre modèle hors ligne.
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Classic evolutionary theory suggests that sexual dimorphism evolves primarily via sexual and fecundity selection. However, theory and evidence are beginning to accumulate suggesting that resource ...competition can drive the evolution of sexual dimorphism, via ecological character displacement between sexes. A key prediction of this hypothesis is that the extent of ecological divergence between sexes will be associated with the extent of sexual dimorphism. As the stable isotope ratios of animal tissues provide a quantitative measure of various aspects of ecology, we carried out a meta‐analysis examining associations between the extent of isotopic divergence between sexes and the extent of body size dimorphism. Our models demonstrate that large amounts of between‐study variation in isotopic (ecological) divergence between sexes is nonrandom and may be associated with the traits of study subjects. We, therefore, completed meta‐regressions to examine whether the extent of isotopic divergence between sexes is associated with the extent of sexual size dimorphism. We found modest but significantly positive associations across species between size dimorphism and ecological differences between sexes, that increased in strength when the ecological opportunity for dietary divergence between sexes was greatest. Our results, therefore, provide further evidence that ecologically mediated selection, not directly related to reproduction, can contribute to the evolution of sexual dimorphism.
Theoretical and empirical work suggests that between‐sex competition for resources plays a role in the evolution of sexual dimorphism. We investigated this concept by analyzing cross‐species relationships between the extent of sexual dimorphism and published sex differences in tissue stable isotope values, which are a proxy of dietary differences. We found that sexual dimorphism is related to sex differences in trophic level, in directions and contexts consistent with those expected if resource competition is involved in the evolution of sexual dimorphism.
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The predicted relationship between home-range size and group mass in primates developed by Clutton-Brock and Harvey (1977) has proved extremely robust in describing the use of space by most primate ...species. However, mandrills (Mandrillus sphinx) are now known to have an extreme group mass in the wild, far larger than that of the species used originally to generate that relationship, and so it was unknown whether this relationship would be robust for this species. We investigated the home-range size and use of a wild horde of ca. 700 mandrills in Lopé National Park, Gabon, using radiotelemetry. The total area the horde used over a 6-yr period 100% minimum convex polygon (MCP) was 182 km², including 89 km² of suitable forest habitat. Mandrills used gallery forests and isolated forest fragments with high botanical diversity far more intensively that the continuous forest and completely avoided savanna and marsh. Peeled polygons and fixed kernel contours revealed multiple centres of use, with the horde spending more than half its time in <10% of the total documented range, typical of a frugivore using a patchy environment. Home-range size and internal structure varied considerably between years, but total home range fitted the predicted relationship between group mass and home range size, despite being an outlier to the dataset. We discuss the conservation implications of the species' space requirements, in light of current pressures on land use in their range.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, SIK, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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