Evaluating Global Biodiversity Hotspots – Very Rich and Even More Endangered

Hrdina, Aleš; Romportl, Dušan

doi:10.1515/jlecol-2017-0013

Cited by 56 publications

(43 citation statements)

References 20 publications

(20 reference statements)

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“…In Tanzania, forests (Figure 2 and Table 1) occupy an estimated 48.1 million hectares of land, equivalent to 55% of the total area (MNRT, 2015). Forests in Tanzania are rich in biodiversity and placed among the 36 global biodiversity hotspots (Hrdina & Romportl, 2017; Myers, Mittermeier, Mittermeier, Da Fonseca, & Kent, 2000). However, it is among the countries with the highest reported forest loss (Hansen et al., 2013) and high vulnerability to the effects of climate change (Montade et al., 2018; Platts, McClean, Lovett, & Marchant, 2008).…”

Section: Methodsmentioning

confidence: 99%

Modelling the impact of climate change on Tanzanian forests

John

Bunting

Hardy

et al. 2020

Diversity and Distributions

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Aim Climate change is pressing extra strain on the already degraded forest ecosystem in Tanzania. However, it is mostly unknown how climate change will affect the distribution of forests in the future. We aimed to model the impacts of climate change on natural forests to help inform national‐level conservation and mitigation strategies. Location Tanzania. Methods We conducted maximum entropy (MaxEnt) modelling to simulate forest habitat suitability using the Tanzanian national forest inventory survey (1,307 occurrences) and environmental data. Changes in forest habitats were simulated under two Representative Concentration Pathways (RCPs) emission scenarios RCP 4.5 and RCP 8.5 for 2055 and 2085. Results The results indicate that climate change will threaten forest communities, especially fragmented strips of montane forests. Even under optimistic emission scenario, the extent of montane forest is projected to almost halve by 2085, intersecting many biodiversity hotspots across the Eastern Arc Mountains. Similarly, climate change is predicted to threaten microhabitat forests (i.e. thickets), with losses exceeding 70% by 2085 (RCP8.5). Other forest habitats are predicted to decrease (lowland forest and woodland) representing essential ecological networks, whereas suitable habitats for carbon‐rich mangroves are predicted to expand by more than 40% at both scenarios. Conclusions Climate change will impact forests by accelerating habitat loss, and fragmentation and the remaining land suitable for forests will also be subject to pressures associated with rising demand for food and biofuels. These changes are likely to increase the probability of adverse impacts to the country's indigenous flora and fauna. Our findings, therefore, call for a shift in conservation efforts, focusing on (i) the enhanced management of existing protected areas that can absorb the impacts of future climate change, and (ii) expanding conservation efforts into newly suitable regions through effective land use planning and land reclamation, helping to preserve and enhance forest connectivity between fragmented patches.

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Section: Methodsmentioning

confidence: 99%

Modelling the impact of climate change on Tanzanian forests

John

Bunting

Hardy

et al. 2020

Diversity and Distributions

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“…The remarkable disparity in the distribution of terrestrial biodiversity has fascinated biologists for more than two centuries (Harrison & Noss, ; Kier et al, ; von Humboldt & Bonpland, ). Thirty‐six recognized biodiversity hotspots, which cover 2.4% of the Earth's land surface, contain an estimated 50% of all endemic plant species and 42% of all endemic terrestrial vertebrate species (Hrdina & Romportl, ; Myers, Mittermeier, Mittermeier, Fonseca, & Kent, ). Endemism lies at the core of understanding the variation of biodiversity across space, revealing how speciation, extinction, dispersal and biophysical barriers influence species distributions (Lomolino et al, ).…”

Section: Introductionmentioning

confidence: 99%

Current climate, isolation and history drive global patterns of tree phylogenetic endemism

Sandel

Weigelt

Kreft

et al. 2019

Global Ecol Biogeogr

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Aim We mapped global patterns of tree phylogenetic endemism (PE) to identify hotspots and test hypotheses about possible drivers. Specifically, we tested hypotheses related to current climate, geographical characteristics and historical conditions and assessed their relative importance in shaping PE patterns. Location Global. Time period We used the present distribution of trees, and predictors covering conditions from the mid‐Miocene to present. Major taxa studied All seed‐bearing trees. Methods We compiled distributions for 58,542 tree species across 463 regions worldwide, matched these to a recent phylogeny of seed plants and calculated PE for each region. We used a suite of predictor variables describing current climate (e.g., mean annual temperature), geographical characteristics (e.g., isolation) and historical conditions (e.g., tree cover at the Last Glacial Maximum) in a spatial regression model to explain variation in PE. Results Tree PE was highest on islands, and was higher closer to the equator. All three groups of predictor variables contributed substantially to the PE pattern. Isolation and topographic heterogeneity promoted high PE, as did high current tree cover. Among mainland regions, temperature seasonality was strongly negatively related to PE, while mean annual temperature was positively related to PE on islands. Some relationships differed among the major floristic regions. For example, tree cover at the Last Glacial Maximum was a positive predictor of PE in the Palaeotropics, while tree cover at the Miocene was a negative predictor of PE in the Neotropics. Main conclusions Globally, PE can be explained by a combination of geographical, historical and current factors. Some geographical variables appear to be key predictors of PE. However, the impact of historic and current climate variables differs considerably among the major floristic regions, reflecting their unique histories. Hence, the current distribution of trees is the result of globally relevant geographical drivers and regional climatic histories.

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“…One natural laboratory for studying plant evolution is the subnival belt of the Hengduan Mountains ( Sun et al., 2014 ). The Hengduan Mountains are located at the southeastern region of the Qinghai-Tibet Plateau; because of its high levels of endemism and species diversity, this region has been designated one of the 36 most important global biodiversity hotpots ( Myers et al., 2000 ; Hrdina and Romportl, 2017 ). The alpine subnival belt (i.e., highest vertical zone of vegetation) is characterized by extreme environments, such as low temperatures, strong wind, frequent precipitation, intense ultraviolet radiation, and low insect abundance and activity ( He et al., 2006 ; Wang, 2006 ).…”

Section: Introductionmentioning

confidence: 99%

Distribution patterns of clonal plants in the subnival belt of the Hengduan Mountains, SW China

et al. 2020

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Clonal reproduction (i.e., production of potentially independent offspring by vegetative growth) is thought to provide plants with reproductive assurance. Thus, studying the evolution of clonal reproduction in local floras is crucial for our understanding of the adaptive mechanisms plants deploy in stressful environments such as alpine regions. In this study, we characterized clonal plant species in the subnival belt of the Hengduan Mountains (a global biodiversity hotspot with extreme environmental conditions in southwest China), in order to determine the effects of sex system, growth form, and elevational distribution on clonality. We compiled clonality data of angiosperm species belonging to 41 families in the subnival belt of the Hengduan Mountains using published information. Of the 793 species recorded in the region, 47.92% (380 species) are clonal species. Both sex system and growth form had significant effects on the occurrence of clonal reproduction: unisexual species (79.79%) were more likely to be clonal than bisexual species (43.63%), and herbaceous species (51.04%) were more likely to be clonal than woody species (16.67%). Compared with non-alpine-endemic species (44.60%), alpine-endemic species (58.33%) showed a significantly higher proportion of clonal reproduction. Further logistic regression analysis showed a positive association between incidence of clonality and elevational range, indicating that species distributed at high elevations are more likely to be clonal. Furthermore, the elevational gradients in clonality were contingent on sex system or growth form. This study reveals that plants in the subnival belt of the Hengduan Mountains might optimize their probability of reproduction through clonal reproduction, a finding that adds to our growing understanding of plant's adaptations to harsh alpine environments.

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Evaluating Global Biodiversity Hotspots – Very Rich and Even More Endangered

Cited by 56 publications

References 20 publications

Modelling the impact of climate change on Tanzanian forests

Modelling the impact of climate change on Tanzanian forests

Current climate, isolation and history drive global patterns of tree phylogenetic endemism

Distribution patterns of clonal plants in the subnival belt of the Hengduan Mountains, SW China

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