Salomon Müller

Past climate change is one of the important factors influencing primate speciation. Populations of various species could have risen or declined in response to these climatic fluctuations. Northeast India harbors a rich diversity of primates, where such fluctuations can be implicated. Recent advances in climate modeling as well as genomic data analysis has paved the way for understanding how species accumulate at a particular geographic region. We utilized these methods to explore the primate diversity in this unique region in relation to past climate change. To ascertain the population level changes, we inferred the demographic history of nine species of primates found in Northeast India and compared it with species distribution models of Pliocene and Pleistocene period. Through this study, we are able to provide a detailed picture of how past climatic changes have resulted in the present species diversity and this mixture of species have either originated in the region or have dispersed from mainland Southeast Asia. We observe that effective population size has decreased for all the species, but distributions are different for all the four genera: Macaca, Trachypithecus, Hoolock and Nycticebus. It also gives an idea about how each species is affected differently by climate change, and why it should be given emphasis in framing species‐wise conservation models for future climate change.

The storks (Ciconiiformes: Ciconiidae) are a fascinating group of birds known for their tall, wading stance, long legs, extended necks, and strong bills. The South and Southeast Asian region boasts the most diverse population of storks, necessitating immediate conservation efforts to protect their habitats and save them from the escalating threats of climate change. Within the genus Leptoptilos , three distinct species exist, two of which—the Greater Adjutant ( Leptoptilos dubius ) and the Lesser Adjutant ( Leptoptilos javanicus )—have garnered attention as ‘Near-Threatened’ according to the IUCN Red List. However, the assessment overlooks the crucial aspects like ramifications of climatic shifts and anthropogenic-induced habitat fragmentation. Hence, this study endeavors to assess climatic impacts via an ensemble approach to species distribution modeling. The findings unveil alarming trends for both adjutants across South and Southeast Asia. The L. dubius is projected to undergo a severe decline of over 95% across all future scenarios (SSP245 and SSP585 in both time periods) from its current suitable extent of 38,686 km 2 , which represents only 5.91% of its total extent. On the contrary, the L. javanicus experiences a spatial relocation towards Southeast Asia under the SSP245 and SSP585 scenarios, resulting in a decline of over 20% from its present suitable range of 239,490 km 2 , which accounts 22.59% of its IUCN range. Furthermore, the resulting habitat fragmentation, propelled by climatic alterations, is severe, with the L. dubius losing numerous viable patches entirely and the L. javanicus experiencing discontinuity in its habitat. Furthermore, given the overlapping ranges of both adjutant species, the current scenario yields a niche overlap value of 0.370. Therefore, the present study advocates for the reassessment of both L. dubius and L. dubius , urging their IUCN assessment under threatened category. Furthermore, strategic conservation measures are proposed in this study, involving local communities, non-governmental organizations, and governmental entities, to safeguard these remarkable avian species.

The Arecaceae family (palms) holds global significance for its economic and ecological roles. Borneo is known as a center of endemic plant species but faces threats from human activities, including those affecting palms. This study aims to update the distribution and conservation status of endemic Bornean palms, identify potential conservation priority areas, and conduct a gap analysis to inform conservation strategies. The methodology involved comprehensive data collection, along with spatial and statistical analysis for conservation assessment and prioritization. Despite challenges like limited data on palm distribution in Indonesia, the study provides critical insights for developing targeted conservation strategies, particularly for conservation priority areas outside protected areas. The study identified 210 endemic Bornean palms, including 16 genera and 111 local endemics, with Malaysia exhibiting the highest species richness. Preliminary global assessment categorized 147 species as threatened palms, with 51 Critically Endangered (CR), 65 Endangered (EN), and 31 Vulnerable (VU). Meanwhile, 63 species were recognized as Least Concern (LC) and Near Threatened (NT). Furthermore, we conducted a hotspot analysis to identify key areas for conservation efforts. This analysis identified 32 grids (covering 12,378.93 km2), representing 10 % of the total identified Conservation Priority Areas (CPA), and 45 grids (covering 104,257.3 km2), representing 20 %. The larger area encompassed by the 20 % CPA highlights broader landscape-level priorities, emphasizing the importance of scaling conservation efforts to address habitat connectivity and ecological resilience. These areas spanned all regions, but a higher percentage was found in Malaysia at 10 % and 20 % sensitivity levels. These findings provide important guidance for targeted conservation actions and support further discussions on the future conservation of endemic Bornean palms.

ABSTRACTAimUndersampling and other sources of sampling bias pose significant issues in marine macroecology, particularly when shaping conservation and management decisions. Yet, determining the extent to which such biases impact our understanding of marine diversity remains elusive. Here, utilising empirical data on sampling efforts, we sampled from virtually established species distributions to evaluate how deep is the influence of sampling bias on estimations of the latitudinal gradient in marine diversity.LocationAtlantic Ocean.Time PeriodPresent.Taxa StudiedOphiuroidea.MethodsWe developed a computer simulation that implements two null models of species distribution (the geometric constraints and the area model) in a two‐dimensional domain, replicates the latitudinal distribution of historical sampling efforts and then quantifies diversity metrics (observed and estimated species richness) and sample completeness for each grid cell and latitudinal band.ResultsWe found consistent patterns of observed species richness across models, noting peaks at midlatitudes regardless of whether the true richness was unimodal or flat. Dips in equatorial diversity persisted even after using different methods of species richness estimation. Additional simulations showed that estimators' accuracy improved with increased sampling efforts, but only when samples were randomly distributed. Spatially aggregated samples inflate completeness without necessarily enhancing estimators' accuracy.Main ConclusionsThis finding emphasises the imperative of bolstering sampling efforts at tropical latitudes and deploying robust statistical techniques to mitigate undersampling effects. Meanwhile, we suggest considering sampling bias as an alternative null hypothesis for recorded marine diversity patterns.

Proboscis monkeys, Nasalis larvatus (Wurmb, 1787), are indigenous to the island of Borneo and are considered one of its most emblematic species. Today the conservation status of this primate is classified as Endangered on the the IUCN Red List and listed under Appendix I of CITES, prohibiting all international commercial trade. In the Malaysian state of Sabah, the species is listed as totally protected and cannot be hunted. Continuing studies suggest that the number of proboscis monkeys has been decreasing in recent years. These studies have identified various factors contributing to this decline and its potential consequences. In order to carry out a thorough assessment of the conservation status of the species it is essential to have a good understanding of the animal`s ecology and habitat requirements and to use research-based approaches. One of such are species distribution models (SDMs) which in recent decades have become widely used tools in ecology by relating species occurrences to environmental data so as to gain ecological insights. In this work we specifically evaluated the effect of environmental parameters such as cloud cover to predict the potential distribution of the proboscis monkey in Sabah. Cloud cover, a seemingly simple atmospheric phenomenon, exerts a profound influence on a wide range of ecological biological processes, yet the assessment of its importance has remained remarkably limited. For modeling purposes the ‘flexsdm’ R (v. 3.3.3) modeling package was employed for testing out the Maximum Entropy (Maxent) algorithm, one of the most widely used SDM modeling methods. Model evaluation gave satisfactory results and the resulting model found a high level of suitability for proboscis monkeys in nearshore areas. A concerning discovery is that perhaps less than 13% of Sabah's area is suitable for proboscis monkey habitats, raising questions about their long-term viability. Cloud cover, particularly average annual cloudiness, is a key environmental factor influencing the distribution of proboscis monkeys in Sabah. The conversion of Borneo's forests to oil palm plantations can negatively impact cloud properties, potentially threatening the monkeys' habitat.

The decreasing freshwater biodiversity trend can be attributed to anthropogenic impacts in terms of climate and land cover change. For targeted conservation efforts, mapping and understanding the distribution of freshwater organisms consists of an important knowledge gap. Spatial modelling approaches offer valuable insights into present-day biodiversity patterns and potential future trajectories, however methodological constraints still hamper the applicability of addressing future climate and land cover change concurrently in one modelling workflow. Compared to climate-only projections, spatially explicit and high-resolution land cover projections have seen less attention, and the lack of such data challenges modelling efforts to predict the possible future effects of land cover change especially on freshwater organisms. Here we demonstrate a workflow where we downscale future land cover projection data from the Shared Socioeconomic Pathway (SSP) scenarios for South America at 1 km2 spatial resolution, to then predict the future habitat suitability patterns of the Colombian fish fauna. Specifically, we show how the land cover data can be converted from plain numbers into a spatially explicit representation for multiple SSP scenarios and at high spatial resolution, employing freshwater-specific downscaling aspects when spatially allocating the land cover category grid cells, and how it can be fitted into an ensemble species distribution modelling approach of 1209 fish species. Our toolbox consists of a suite of open-source tools, including Dinamica EGO, R, GRASS GIS and GDAL, and we provide the code and necessary steps to reproduce the workflow for other study areas. We highlight the feasibility of the downscaling, but also underline the potential challenges regarding the spatial scale and the size of the spatial units of analysis.

Extant neosuchian crocodiles are represented by only 24 taxa that are confined to the tropics and subtropics. However, at other intervals during their 200 Myr evolutionary history the clade reached considerably higher levels of species-richness, matched by more widespread distributions. Neosuchians have occupied numerous habitats and niches, ranging from dwarf riverine forms to large marine predators. Despite numerous previous studies, several unsolved questions remain with respect to their biogeographic history, including the geographical origins of major groups, e.g. Eusuchia and Neosuchia itself. We carried out the most comprehensive biogeographic analysis of Neosuchia to date, based on a multivariate K-means clustering approach followed by the application of two ancestral area estimation methods (BioGeoBEARS and Bayesian ancestral location estimation) applied to two recently published phylogenies. Our results place the origin of Neosuchia in northwestern Pangaea, with subsequent radiations into Gondwana. Eusuchia probably emerged in the European archipelago during the Late Jurassic/Early Cretaceous, followed by dispersals to the North American and Asian landmasses. We show that putative transoceanic dispersal events are statistically significantly less likely to happen in alligatoroids. This finding is consistent with the saltwater intolerant physiology of extant alligatoroids, bolstering inferences of such intolerance in their ancestral lineages.

Past responses to environmental change provide vital baseline data for estimating the potential resilience of extant taxa to future change. Here, we investigate the latitudinal range contraction that terrestrial and freshwater turtles (Testudinata) experienced from the Late Cretaceous to the Paleogene (100.5–23.03 mya) in response to major climatic changes. We apply ecological niche modeling (ENM) to reconstruct turtle niches, using ancient and modern distribution data, paleogeographic reconstructions, and the HadCM3L climate model to quantify their range shifts in the Cretaceous and late Eocene. We then use the insights provided by these models to infer their probable ecological responses to future climate scenarios at different representative concentration pathways (RCPs 4.5 and 8.5 for 2100), which project globally increased temperatures and spreading arid biomes at lower to mid-latitudes. We show that turtle ranges are predicted to expand poleward in the Northern Hemisphere, with decreased habitat suitability at lower latitudes, inverting a trend of latitudinal range contraction that has been prevalent since the Eocene. Trionychids and freshwater turtles can more easily track their niches than Testudinidae and other terrestrial groups. However, habitat destruction and fragmentation at higher latitudes will probably reduce the capability of turtles and tortoises to cope with future climate changes.

Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.

Tropical Rainforest Heritage sites of Sumatra are some of the most irreplaceable landscapes in the world for biodiversity conservation. These landscapes harbor many endangered Asiatic mammals all suffering multifaceted threats due to anthropogenic activities. Three charismatic mammals in Sumatra: Elephas maximus sumatranus, Pongo abelii, and Panthera tigris sumatrae are protected and listed as Critically Endangered (CR) within the IUCN Red List. Nevertheless, their current geographic distribution remains unclear, and the impact of environmental factors on these species are mostly unknown. This study predicts the potential range of those species on the island of Sumatra using anthropogenic, biophysical, topographic, and climatic parameters based on the ensemble machine learning algorithms. We also investigated the effects of habitat loss from current land use, ecosystem availability, and importance of Indonesian protected areas. Our predictive model had relatively excellent performance (Sørensen: 0.81–0.94) and can enhance knowledge on the current species distributions. The most critical environmental predictors for the distribution of the three species are conservation status and temperature seasonality. This study revealed that more than half of the species distributions occurred in non-protected areas, with proportional coverage being 83%, 72%, and 54% for E.m. sumatranus, P. abelii, and P.t. sumatrae, respectively. Our study further provides reliable information on places where conservation efforts must be prioritized, both inside and outside of the protected area networks, to safeguard the ongoing survival of these Indonesian large charismatic mammals.