Janet Russell Perkins

Understanding the interactions between abiotic (environmental and anthropogenic) factors and species diversity and distribution patterns is fundamental to improving the ecological representativeness of biodiversity management tools such as protected areas (PAs). However, significant knowledge gaps remain about how species’ ecological and evolutionary opportunities are associated with abiotic factors, especially in biodiversity-rich but economically ill-equipped countries such as Kenya. Here, we explored the interactions of terrestrial mammal diversity patterns and abiotic factors across species groups and ecoregions in Kenya. We coupled data on terrestrial mammal occurrences, phylogeny, functional traits, and environmental predictors in Kenya to derive multiple diversity indices, encompassing species richness and phylogenetic and functional richness, and mean pairwise and nearest taxon distances. We explored the interactions of these indices with several abiotic factors using multivariate regression analyses while adjusting for spatial autocorrelation. The results showed weak correlations between species richness versus the phylogenetic and functional diversity indices. The best-fit models explained variable proportions of diversity indices between species groups and ecoregions and consistently retained annual temperature and precipitation averages and seasonality and human footprint as the strongest predictors. Compared to the species-poor xeric northern and eastern Kenya regions, the predictors had weak associations with diversity variances in the species-rich mesic western and central Kenya regions, similar to focal species groups compared to ordinal classifications and the combined species pool. These findings illustrate that climate and human footprint interplay determine multiple facets of terrestrial mammal diversity patterns in Kenya. Accordingly, curbing human activities degrading long-term climatic regimes is vital to ensuring the ecological integrity of terrestrial mammal communities and should be integrated into biodiversity management frameworks. For a holistic representation of critical conservation areas, biodiversity managements should also prioritize terrestrial mammal phylogenetic and functional attributes besides species richness.

While area-based approaches continue to dominate biodiversity conservation, there is growing recognition of the importance of the human dimensions of biodiversity. We applied the Important Plant Areas (IPA) approach in Colombia to identify key sites for the conservation of plant species with reported human uses. Drawing on the Checklist of Useful Plants of Colombia, we collated 1,045,889 clean occurrence records for 5400 native species from global data repositories and digitized herbaria. Through analysis based on regionalized grid cells, we identified 980 sites meeting IPA thresholds. These are primarily located in forest habitats, with only 19.8 % within existing national natural parks or internationally designated conservation areas. Grid cells were transformed to polygons based on overlapping ecosystems and administrative boundaries to form more meaningful site boundaries. A subsequent two-stage ranking procedure based on conservation value and richness found 46 sites to be of high priority, with 10 selected as top priorities for further investigation and conservation action. These 10 sites support significant populations of 33 threatened useful plant species and represent six of the 13 bioregions of Colombia in just 0.27 % of its land area. To progress from potential to confirmed IPAs, targeted fieldwork is required alongside stakeholder engagement and consultation, crucially involving local resource users. As a megadiverse country ranked second in the world for its botanical richness, effective IPA management would not only contribute to Colombian targets for sustainable development and conservation but would also support global targets to recover biodiversity for both planet and people.

Background Poa annua (annual bluegrass) is an allotetraploid turfgrass, an agronomically significant weed, and one of the most widely dispersed plant species on earth. Here, we report the chromosome-scale genome assemblies of P. annua’s diploid progenitors, P. infirma and P. supina, and use multi-omic analyses spanning all three species to better understand P. annua’s evolutionary novelty. Results We find that the diploids diverged from their common ancestor 5.5 – 6.3 million years ago and hybridized to form P. annua  ≤ 50,000 years ago. The diploid genomes are similar in chromosome structure and most notably distinguished by the divergent evolutionary histories of their transposable elements, leading to a 1.7 × difference in genome size. In allotetraploid P. annua, we find biased movement of retrotransposons from the larger (A) subgenome to the smaller (B) subgenome. We show that P. annua’s B subgenome is preferentially accumulating genes and that its genes are more highly expressed. Whole-genome resequencing of several additional P. annua accessions revealed large-scale chromosomal rearrangements characterized by extensive TE-downsizing and evidence to support the Genome Balance Hypothesis. Conclusions The divergent evolutions of the diploid progenitors played a central role in conferring onto P. annua its remarkable phenotypic plasticity. We find that plant genes (guided by selection and drift) and transposable elements (mostly guided by host immunity) each respond to polyploidy in unique ways and that P. annua uses whole-genome duplication to purge highly parasitized heterochromatic sequences. The findings and genomic resources presented here will enable the development of homoeolog-specific markers for accelerated weed science and turfgrass breeding .

Aim This study aimed to investigate the distribution patterns of plant diversity in Kenya, how climatic fluctuations and orogeny shaped them, and the formation of its β-diversity. Location Kenya, East Africa. Taxon Angiosperms. Methods We quantified patterns of turnover and nestedness components of phylogenetic β-diversity for angiosperm species among neighbouring sites using a well-resolved phylogenetic tree and extensive distribution records from public databases and other published sources. We applied clustering methods to delineate biota based on pairwise similarities among multiple sites and used a random assembly null model to assess the effects of species abundance distribution on phylogenetic β-diversity. Results The phylogenetic turnover of the Kenyan flora, intersecting with the biodiversity hotspots Eastern Afromontane, Coastal Forests of Eastern Africa, and Horn of Africa, shows a non-monotonic pattern along a latitudinal gradient that is strongly structured into volcanic and coastal areas. The other areas are mainly dominated by phylogenetic nestedness, even in the eastern part of the equatorial region parallel to the volcanic area. Phylogenetic diversity and phylogenetic structure analyses explain the mechanism of the observed phylogenetic turnover and nestedness patterns. We identified five phytogeographical regions in Kenya: the Mandera, Turkana, Volcanic, Pan Coastal and West Highland Regions. Conclusions Variations in turnover gradient and coexistence are highly dependent on the regional biogeographical history resulting from climatic fluctuations and long-lasting orogeny, which jointly shaped the biodiversity patterns of the Kenyan flora. The nestedness component dominated climatically unstable regions and is presumed to have been caused by heavy local species extinction and recolonization from the Volcanic Region. The high turnover component in climatically stable regions may have preserved old lineages and the prevalence of endemic species within narrow ranges.

Conservation efforts in global biodiversity hotspots often face a common predicament: an urgent need for conservation action hampered by a significant lack of knowledge about that biodiversity. In recent decades, the computerisation of primary biodiversity data worldwide has provided the scientific community with raw material to increase our understanding of the shared natural heritage. These datasets, however, suffer from a lot of geographical and taxonomic inaccuracies. Automated tools developed to enhance their reliability have shown that detailed expert examination remains the best way to achieve robust and exhaustive datasets. In New Caledonia, one of the most important biodiversity hotspots worldwide, the plant diversity inventory is still underway, and most taxa awaiting formal description are narrow endemics, hence by definition hard to discern in the datasets. In the meantime, anthropogenic pressures, such as nickel-ore mining, are threatening the unique ultramafic ecosystems at an increasing rate. The conservation challenge is therefore a race against time, as the rarest species must be identified and protected before they vanish. In this study, based on all available datasets and resources, we applied a workflow capable of highlighting the lesser known taxa. The main challenges addressed were to aggregate all data available worldwide, and tackle the geographical and taxonomic biases, avoiding the data loss resulting from automated filtering. Every doubtful specimen went through a careful taxonomic analysis by a local and international taxonomist panel. Geolocation of the whole dataset was achieved through dataset cross-checking, local botanists’ field knowledge, and historical material examination. Field studies were also conducted to clarify the most unresolved taxa. With the help of this method and by analysing over 85,000 data, we were able to double the number of known narrow endemic taxa, elucidate 68 putative new species, and update our knowledge of the rarest species’ distributions so as to promote conservation measures.

Western Ecuador harbours high plant diversity and endemism. The region of Manabí has known intense deforestation over the last decades, but lowland rain forests persist in a network of small forest fragment patches. Here, we describe two new magnoliid tree species from a small privately owned forest fragment known as La Esperanza reserve, in the El Carmen canton (Manabí): Aniba ecuadorica (Lauraceae) and Guatteria esperanzae (Annonaceae). For both species a detailed morphological description, a preliminary conservation status following IUCN criteria, distribution maps and high quality photographs are provided. This represents the second species of Aniba known to occur in western Ecuador, while there are 14 species of Guatteria documented for Ecuador west of the Andes. Aniba ecuadorica is only known from two localities and has a preliminary IUCN conservation status of Critically Endangered, while Guatteria esperanzae is known from six localities and is suggested to be Endangered. Finally, we provide a quick overview of Guatteria species in western Ecuador with a key to the species in the region. The description of these two new tree species underlines the important need of prospection and conservation of the remnant forests in the Manabí region of western Ecuador. We also stress the importance of privately owned forest fragments for biodiversity conservation.

Aims Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before (past bias) or after (recent bias) ARCs—underpins these data misrepresentations. Occurrence–habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location Virtual Southeast Asia. Methods Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past and recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results Greater ARC resulted in greater occurrence–habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence–habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without. Main conclusions We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of ARCs, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximize the temporal range of anthropogenic predictors, exclude mismatched occurrences and test for residual data misrepresentations.

Insect phenological lability is key for determining which species will adapt under environmental change. However, little is known about when adult insect activity terminates and overall activity duration. We used community‐science and museum specimen data to investigate the effects of climate and urbanisation on timing of adult insect activity for 101 species varying in life history traits. We found detritivores and species with aquatic larval stages extend activity periods most rapidly in response to increasing regional temperature. Conversely, species with subterranean larval stages have relatively constant durations regardless of regional temperature. Species extended their period of adult activity similarly in warmer conditions regardless of voltinism classification. Longer adult durations may represent a general response to warming, but voltinism data in subtropical environments are likely underreported. This effort provides a framework to address the drivers of adult insect phenology at continental scales and a basis for predicting species response to environmental change.

Biodiversity databases are increasingly available and have fostered accelerated advances in many disciplines within ecology and evolution. However, the quality of the evidence generated depends critically on the quality of the input data, and species misidentifications are present in virtually any o…

The Qinghai-Tibetan Plateau (QTP) harbors abundant and diverse plant life owing to its high habitat heterogeneity. However, the distribution pattern of biodiversity hotspots and their conservation status remain unclear. Based on 148,283 high-resolution occurrence coordinates of 13,450 seed plants, w…