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Forest Hotspots in the Biodiversity Hotspot of New Caledonia
<h1>Description</h1> <p>This dataset explores threats to New Caledonia's forests, focusing on the probability of deforestation within hotspots of tree community diversity.</p> <ul> <li>The probability of deforestation was derived from the "<em>Spatial scenario of tropical deforestation and carbon emissions for the 21st century</em>" (<a title="Spatial scenario of tropical deforestation and carbon emissions for the 21st century" href="https://doi.org/10.1101/2022.03.22.485306" target="_blank" rel="noopener">Vielledent et al., 2023</a>), available as <a title="Forest at Risk in New Caledonia" href="https://forestatrisk.cirad.fr/newcal/" target="_blank" rel="noopener">downloadable GeoTIFFs</a> for New Caledonia for the years 2050 and 2100</li> <li>Hotspots of tree community diversity were identified using the '<strong>Core Forest</strong>' class extracted from the dataset '<em>Classification of New Caledonia Forests According to Edge and Elevation Effects</em>'. Core forest are defined as forest areas located more than 300 meters from the forest edge, characterized by potentially richer tree communities.</li> </ul> <p>To assess habitat quality, each core forest fragment was surrounded by a 500-meter buffer zone. We evaluated forest habitat metrics including forest cover, forest type distribution, and fragmentation index within these buffer zones. Additionally, we analyzed the areas of forest threatened by deforestation in 2050 and 2100. The resulting maps provide decision-making support for stakeholders involved in conserving New Caledonia's forests. The fragmentation index used is the effective mesh size (meff), originally proposed by <a title="Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation" href="https://doi.org/10.1023/A:1008129329289" target="_blank" rel="noopener">Jaeger (2000)</a> and updated by <a title="Modification of the effective mesh size for measuring landscape fragmentation to solve the boundary problem" href="https://doi.org/10.1007/s10980-006-9023-0" target="_blank" rel="noopener">Moser and al. (2007)</a> to address boundary effects. A higher index value indicates less fragmented forest.</p> <h1>Content</h1> <p>This dataset was generated, analyzed, and validated using a suite of open-source software tools, including QGIS, PostgreSQL, PostGIS, Python, and the GDAL library, operating on a Linux platform. The compressed file includes six essential files formatted for an ESRI GIS system, utilizing the WGS84 international coordinate system. It is compatible for upload into spatial databases such as PostgreSQL/PostGIS.</p> <p>Each entry in the attribute table represents a buffer area containing one or several core forests, with the following fields (restricted to 10 characters):</p> <table> <tbody> <tr> <td><strong>Field</strong></td> <td><strong>Type</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td><strong>id_buffer</strong></td> <td>INTEGER</td> <td>Unique identifier for the buffer</td> </tr> <tr> <td><strong>area_ha<br></strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Area of the buffer in hectares</td> </tr> <tr> <td><strong>frag_index</strong></td> <td>NUMERIC</td> <td>Forest fragmentation meff index within the buffer</td> </tr> <tr> <td><strong>forest_cov</strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Proportion of forest within the buffer area (%)</td> </tr> <tr> <td><strong>edge_r</strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Proportion of forest area classified as edge forest (%) </td> </tr> <tr> <td><strong>mature_r</strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Proportion of forest area classified as mature forest (%) </td> </tr> <tr> <td><strong>core_r</strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Proportion of forest area classified as core forest (%) </td> </tr> <tr> <td><strong>defor_2050</strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Proportion of forest threatened by deforestation in 2050 (%)</td> </tr> <tr> <td><strong>defor_2100</strong></td> <td>NUMERIC (2 DECIMALS)</td> <td>Proportion of forest threatened by deforestation in 2100 (%)</td> </tr> <tr> <td><strong>pn</strong></td> <td>BOOLEAN</td> <td>True or False, indicating if the polygon overlaps with the Northern province</td> </tr> <tr> <td><strong>ps</strong></td> <td>BOOLEAN</td> <td>True or False, indicating if the polygon overlaps with the Southern province</td> </tr> </tbody> </table> <p> </p> <h1>Limitations</h1> <p>This analysis of forest conservation issues aims to foster dialogue between forest ecologists and forest management strategies in New Caledonia. It should not be applied blindly based solely on the few quantitative variables proposed.</p> <p>Various scenarios can utilize these metrics, and we urge managers to initially define conservation objectives (such as maximizing biodiversity, reducing fragmentation, restoring disturbed environments, etc.) and consider constraints (such as accessibility, budget, feasibility, etc.) before utilizing this dataset.</p> <p>While threats was projected for future scenarios, conservation efforts should also prioritize preserving forests in their current state, including addressing increasing fragmentation and biodiversity loss. We encourage users to explore these metrics and their correlation with other quantitative or qualitative variables to gain a deeper understanding of conservation challenges in New Caledonia's forests.</p>
Biodiversity Hotspots Map (no text)
<p>This map displays the global <a href="https://zenodo.org/record/3261807#.X8_HgNhKg2x">Biodiversity Hotspots 2016.1 dataset</a>. The colors assigned to the hotspots are only used to distinguish adjacent hotspots and have no other meaning. The biodiversity hotspots represent terrestrial biodiversity only. The offshore lines are a cartographic device to group and highlight islands that are part of the same hotspots (e.g. Polynesia-Micronesia, Indo-Burma). The background image is from Natural Earth. This version is without labels; a version with the hotspots labelled in English is available: 10.5281/zenodo.4311850</p> <p>There are currently <a href="https://www.cepf.net/node/1996">36 recognized biodiversity hotspots</a>. These are Earth’s most biologically rich—yet threatened—terrestrial regions.</p> <p>To qualify as a biodiversity hotspot, an area must meet two strict criteria:</p> <ul> <li>Contain at least 1,500 species of vascular plants found nowhere else on Earth (known as "endemic" species).</li> <li>Have lost at least 70 percent of its primary native vegetation.</li> </ul> <p>Many of the biodiversity hotspots exceed the two criteria. For example, both the Sundaland Hotspot in Southeast Asia and the Tropical Andes Hotspot in South America have about <strong>15,000</strong> endemic plant species. The loss of vegetation in some hotspots has reached a startling <strong>95</strong> percent.</p>
Biodiversity Hotspots (version 2016.1)
<p>There are currently <a href="https://www.cepf.net/node/1996">36 recognized biodiversity hotspots</a>. These are Earth’s most biologically rich—yet threatened—terrestrial regions.</p> <p>To qualify as a biodiversity hotspot, an area must meet two strict criteria:</p> <ul> <li>Contain at least 1,500 species of vascular plants found nowhere else on Earth (known as "endemic" species).</li> <li>Have lost at least 70 percent of its primary native vegetation.</li> </ul> <p>Many of the biodiversity hotspots exceed the two criteria. For example, both the Sundaland Hotspot in Southeast Asia and the Tropical Andes Hotspot in South America have about <strong>15,000</strong> endemic plant species. The loss of vegetation in some hotspots has reached a startling <strong>95</strong> percent.</p>
Data and R-scripts for "Land-use trajectories for sustainable land system transformations: identifying leverage points in a global biodiversity hotspot" (V2)
<p>Sustainable land system transformations are necessary to avert biodiversity and climate collapse. However, it remains unclear where entry points for transformations exist in complex land systems. Here, we conceptualize land systems along land-use trajectories, which allows us to identify and evaluate leverage points; i.e., entry points on the trajectory where targeted interventions have particular leverage to influence land-use decisions. We apply this framework in the biodiversity hotspot Madagascar. In the Northeast, smallholder agriculture results in a land-use trajectory originating in old-growth forests, spanning forest fragments, and reaching shifting hill rice cultivation and vanilla agroforests. Integrating interdisciplinary empirical data on seven taxa, five ecosystem services, and three measures of agricultural productivity, we assess trade-offs and co-benefits of land-use decisions at three leverage points along the trajectory. These trade-offs and co-benefits differ between leverage points: two leverage points are situated at the conversion of old-growth forests and forest fragments to shifting cultivation and agroforestry, resulting in considerable trade-offs, especially between endemic biodiversity and agricultural productivity. Here, interventions enabling smallholders to conserve forests are necessary. This is urgent since ongoing forest loss threatens to eliminate these leverage points due to path-dependency. The third leverage point allows for the restoration of land under shifting cultivation through vanilla agroforests and offers co-benefits between restoration goals and agricultural productivity. The co-occurring leverage points highlight that conservation and restoration are simultaneously necessary. Methodologically, the framework shows how leverage points can be identified, evaluated, and harnessed for land system transformations under the consideration of path-dependency along trajectories.</p>
Impact of Phytophthora cinnamomi on the taxonomic and functional diversity of forest plants in a mediterranean-type biodiversity hotspot
<p class="MsoNormal"><strong>Aim</strong></p> <p class="MsoNormal">Diversity-rich mediterranean-type sclerophyllous forests are home to 20% of described species on Earth. In the <em>Eucalyptus marginata</em> (jarrah) forest of southwest of Western Australia diversity is being reduced by extensive human use and the introduction of the plant pathogen <em>Phytophthora cinnamomi</em>. This study investigated the influence of <em>P. cinnamomi </em>infestation on the structure, taxonomic and functional diversity, and species composition of the forest.</p> <p class="MsoNormal"><strong>Location</strong>: Jarrah forest of southwestern Australia</p> <p class="MsoNormal"><strong>Methods</strong></p> <p class="MsoNormal">Species<strong> </strong>abundance, understorey cover and canopy cover were assessed along 22, 30-m long transects which crossed infested and non-infested zones in five reserves in the jarrah forest. A trait database was assembled for 137 plants using 13 traits related to nutrient- and carbon acquisition, disturbance tolerance and reproduction. The responses of canopy cover, understorey cover, species richness, Shannon diversity, evenness, abundance, and functional diversity for trait groups, and all groups combined were modelled against reserve and zone as fixed effects and transect and transect section as random effects. To assess the species composition, NMDS ordination based on Bray Curtis resemblance and indicator species analyses were used.</p> <p class="MsoNormal"><strong>Results</strong></p> <p class="MsoNormal">Significantly higher understorey cover, species richness, Shannon diversity and evenness were recorded in non-infested compared to infested zones, but there were no changes in the canopy cover and overall abundance. In non-infested zones, the functional diversity of nutrient acquisition and reproductive traits was higher, but the functional diversity of carbon acquisition traits was lower. No difference in functional diversity was recorded in disturbance tolerance and overall traits between the two zones. NMDS ordination and ANOSIM revealed a significant difference in the species composition between the two zones, and 11 indicator species significantly associated with infested and non-infested zones were identified.<strong> </strong></p> <p class="MsoNormal"><strong>Conclusion</strong></p> <p class="MsoNormal"><em>Phytophthora cinnamomi</em> has significantly affected the forest structure, taxonomic and functional diversity, and species composition. Contrasting responses of functional trait groups obscured overall trait responses to <em>P. cinnamomi.</em></p>
A Gridded Microclimate Dataset from a Sub-Arctic Biodiversity Hotspot in Finland
<p><strong>The dataset comprises 63 spatially continuous microclimate surfaces for the Kilpisjärvi region in northwestern Finland. The study region is a biodiversity hotspot for arctic-alpine flora and fauna and one of the most extensively investigated regions in Northern Europe. The data were gathered through a collaborative network of microclimate loggers, encompassing 430 measurement locations that comprehensively cover the 300 km2 landscape under study. We employed predominantly well-performing Random Forest models to project microclimate variables across the study area at a 3-metre spatial resolution.</strong></p>
FIG. 5 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
FIG. 5. — Plot between the two first axes of the CVA performed upon four external body measurements (head and body, tail, hindfoot, and tail lengths) for 252 shrew specimens from Mount Nimba, Ziama and surrounding areas. Each species is represented by a color dot. Yellow dots indicate class barycenter and ellipses at 0.05% confidence; b, C. buettikoferi Jentink, 1888; d, C. douceti Heim de Balsac, 1958; e, C. eburnea Heim de Balsac, 1958; g, C. grandiceps Hutterer, 1983; j, C. jouvenetae Heim de Balsac, 1958; C. muricauda (Miller, 1900); mu, S. megalura (Jentink, 1888); n, C. nimbae Heim de Balsac, 1956; o, C. obscurior Heim de Balsac, 1958; ol, C. olivieri (Lesson, 1827); sy, C. nimbasilvanus Hutterer, 2003; t, C. theresae Heim de Balsac, 1968.
FIG. 1 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
FIG. 1. — Detail of the trapping localities at Mount Nimba with respect to elevation. Sampling sites are shown in black circles. Light and dark grey shading refer to areas above 600 m and 1000 m, respectively. Names of localities used in this work as follows: G, Guinea; L, Liberia, Gbié: G1-A, B; Gouan: G2-A, B; Seringbara:G3; Gblayougouma G4; Ziéla: G5; East Nimba Nature Reserve L1-A, B, C; Bentor: L2; Bonlah: L3; Yekepa: L4; Tailings: L5; Camp4: L6; Liabala: L7; Gbapa: L8; Zolowee: L9; Grassfield: L10; Border (Yekepa): L11.
APPENDIX 8 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
APPENDIX 8. — Nimba shrews skins with field numbers: A, MNHN-ZM-2014-900 (LB07) C. buettikoferi Jentink, 1888 Camp 4; B, MNHN-ZM-2012-1079 (NIM217) C. grandiceps Hutterer, 1983 Gouan; C, MNHN-ZM-2012-1158 (NIM201) C. olivieri (Lesson, 1827) Gbié; D, MNHN-ZM-2012-1111 (NIM232) C. muricauda (Miller, 1900) Gouan; E, MNHN-ZM-2012-1180 (NIM 301) C. theresae Heim de Balsac, 1968 Gouan; F, MNHN-ZM-MO-1981-492 C. nimbae Heim de Balsac, 1956 Holotype Zouguepo; G, MNHN-ZM-MO-1981-483 C. eburnea Heim de Balsac, 1958 Mt Tonkui; H, MNHN-ZM-2012-1123 (NIM 219) C. obscurior Heim de Balsac, 1958 Gouan.
FIG. 4 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
FIG. 4. — Standard karyotypes from Mount Nimba shrews: A, male C. buettikoferi Jentink, 1888 MNHN-ZM-2012-1071, 2n = 52, NFa = 66; B, male C. grandiceps Hutterer, 1983 MNHN-ZM-2012-1077, 2n = 46, NFa = 64; C, male C. jouvenetae Heim de Balsac, 1958 MNHN-ZM-2012-1091, 2n = 44, NFa = 68; D, male C. olivieri (Lesson, 1827) MNHN-ZM-2012-1164, 2n = 50, NFa = 60; E, female C. theresae Heim de Balsac, 1968 MNHN-ZM-2012-1171, 2n = 50, NFa = 70.
FIG. 7 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
FIG. 7. — Comparison of the relative abundance (% on y axis) of shrew species between four different surveys. Nimba this work (N = 226), Taï: Churchfield et al. (2004) (N = 553), Ziama: Nicolas et al. (2009) (N = 2571), Dodo-Haut Cavally: Decher et al. (2005) (N = 15). For authorships of the species, see Table 5.
FIG. 3 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
FIG. 3. — Craniodental measurements used for morphometric analyses adapted from Dippenaar (1977) and Hutterer & Kock (2002): a, condyle-incisive length; b, nasal width; c, interorbital width; d, occipital greatest width; e, greatest maxillary width; f, upper tooth row length; g, height of the skull at M2 level; h, greatest braincase height; i, mandibular length; j, lower tooth row length; k, greatest length between extremities of the coronoid and angular processes.
FIG. 2 in Shrews (Mammalia, Eulipotyphla) from a biodiversity hotspot, Mount Nimba (West Africa), with a field identification key to species
FIG. 2. — Examples of habitats where pitfall traps were placed on the Guinean and Liberian Nimba: A, gallery forest and swamp, camp 4 (Liberia); B, pitfall, altitude savannah with Loudetia kagerensis, Mare d'hivernage site (1642 m) (Guinea); C, pitfall, Selingbala (Guinea): mesophyllous secondary forest; D, pitfall, Gbie (Guinea): gallery forest with Parinari excelsa Sabine,1824, Carapa procera DC., 1824 and Pseudospondias microcarpa (A. Rich.) Engl., 1883, Maranthochloa purpurea (Ridl.) Milne-Redh.
Fig. 1 in On The Biodiversity Hotspot Of Large Branchiopods (Crustacea, Branchiopoda) In The Central Paroo In Semiarid Australia
Fig. 1. Map of Bloodwood, Tregeda, and Muella Stations, central Paroo, northwestern NSW. Code to symbols: SL — Salt Lake; L — Freshwater Lake; C — Claypan; G — Grassy swamp; S — Samphire swamp; X — Poplar Box flat; short line, creek pool; dot — Black Box swamp.
Fig. 3. Four representative branchiopods from the central Paroo. A in On The Biodiversity Hotspot Of Large Branchiopods (Crustacea, Branchiopoda) In The Central Paroo In Semiarid Australia
Fig. 3. Four representative branchiopods from the central Paroo. A — Anostracan Branchinella australiensis; B — Notostracan Triops sp.; C — Spinicaudatan Limnadopsis tatei; D — Spinicaudatan Ozestheria lutraria.
Fig. 2 in On The Biodiversity Hotspot Of Large Branchiopods (Crustacea, Branchiopoda) In The Central Paroo In Semiarid Australia
Fig. 2. Images of seven types of wetlands in the central Paroo., northwestern New South Wales: A — Gidgee Salt Lake; B — Ski Freshwater Lake; C — Melaleuca claypan; D — Beverley's grassy pool (dry); E — Reedy Black Box swamp; F — Utah Poplar Box flat; G — Lower Crescent creek pool. Not to scale.
Biodiversity cradles and museums segregating within hotspots of endemism
<p>The immense concentrations of vertebrate species in tropical mountains remain a prominent but unexplained pattern in biogeography. A long-standing hypothesis suggests that montane biodiversity hotspots result from endemic species aggregating within ecologically stable localities. Here, the persistence of ancient lineages coincides with frequent speciation events, making such areas both 'cradles' (where new species arise) and 'museums' (where old species survive). Although this hypothesis refers to processes operating at the scale of valleys, it remains supported primarily by patterns generated from coarse-scale distribution data. Using high-resolution occurrence and phylogenetic data on Andean hummingbirds, we find that old and young endemic species are not spatially aggregated. The young endemic species tend to have non-overlapping distributions scattered along the Andean treeline, a long and narrow habitat where populations easily become fragmented. By contrast, the old endemic species have more aggregated distributions, but mainly within pockets of cloud forests at lower elevations than the young endemic species. These findings contradict the premise that biogeographical cradles and museums should overlap in valley systems where pockets of stable climate persist through periods of climate change. Instead, Andean biodiversity hotspots may derive from large-scale fluctuating climate complexity in conjunction with local-scale variability in available area and habitat connectivity.</p>
A practice-led assessment of landscape restoration potential in a biodiversity hotspot
<p>Effective restoration planning tools are needed to mitigate global carbon and biodiversity crises. Published spatial assessments of restoration potential are often at large scales or coarse resolutions inappropriate for local action. Using a Tanzanian case study, we introduce a systematic approach to inform landscape restoration planning, estimating spatial variation in cost-effectiveness, based on restoration method, logistics, biomass modelling and uncertainty mapping. We found potential for biomass recovery across 77.7% of a 53,000 km<sup>2</sup> region, but with some natural spatial discontinuity in moist forest biomass, that was previously assigned to human causes. Most areas with biomass deficit (80.5%) were restorable through passive or assisted natural regeneration. However, cumulative biomass gains from planting outweighed initially high implementation costs meaning that, where applicable, this method yielded greater long-term returns on investment. Accounting for ecological, funding and other uncertainty, the top 25% consistently cost-effective sites were within protected areas and/or moderately degraded moist forest and savanna. Agro-ecological mosaics had high biomass deficit but little cost-effective restoration potential. Socio-economic research will be needed to inform action towards environmental and human development goals in these areas. Our results highlight value in long-term landscape restoration investments and separate treatment of savannas and forests. Furthermore, they contradict previously asserted low restoration potential in East Africa, emphasising the importance of our regional approach for identifying restoration opportunities across the tropics.</p>
Data used in the paper: Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot
<p>This repository contains phylogenetic and functional trait data, raster files, and tables with sampling information and references used in the article "Historical and current environmental selection on functional traits of trees in the Atlantic Forest biodiversity hotspot" by Silva, J.L.A., Souza, A., and Vitória, A.P. Journal of Vegetation Science, <a href="https://doi.org/10.1111/jvs.13049">https://doi.org/10.1111/jvs.13049</a> .</p> <p>Description of files:</p> <p>(1) "Species-level_Trait_Data_Silva_et_al._2021.csv": This file contains species-specific mean trait values and the plant growth form of the 2,122 studied species, whenever available. Trait values were compiled from public sources such as original papers, master and doctoral dissertations, and global trait databases.</p> <p>(2) "Phylogenetic_Tree_Silva_et_al._2021.txt": This file contains the phylogenetic tree of the 2,122 studied species.</p> <p>(3) "CWM_Trait_Maps.zip": This file contains seven rasters of spatially contiguous surfaces produced by Ordinary Kriging Interpolation using Community-Weighted Means (CWM) of each functional trait.</p> <p>(4) "References-abundance-data.csv": This file contains sampling details and the references used to compile species abundance data for each studied site.</p> <p>(5) "References-trait-data.csv": This file contains sampling details and the references used to compile functional trait data.</p> <p> </p>
Fig. 14 in Amphibian diversity of a West African biodiversity hotspot: an assessment and commented checklist of the batrachofauna of the Ivorian part of the Nimba Mountains
Fig. 14. Ptychadenid, ranid, and rhacophorid frogs from Mount Nimba Integrated Nature Reserve: Ptychadena retropunctata (A); P. stenocephala female (B); P. submascareniensis female (C); P. submascareniensis male (D); P. tournieri female (E); Amnirana sp. 'albolabris west' female (F); Amnirana sp. 'albolabris west' male (G); Chiromantis rufescens male (H).
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