factors influencing the precision of species richness estimation in japanese vascular plants

n/

Spatial conservation prioritization for the East Asian islands : A balanced representation of multitaxon biogeography in a protected area network

Aim On the basis of multitaxon biogeographical processes related to region-specific geohistory and palaeoclimate, we identified a balanced and area-effective protected area network (PAN) expansion in the East Asian islands, a global biodiversity hotspot. Location Japanese archipelago, Ryukyu archipelago and Izu-Bonin oceanic islands. Methods We modelled the distributions of 6,325 species (amphibians, birds, freshwater fish, mammals, plants and reptiles) using 4,389,489 occurrence data points. We then applied the Zonation software for spatial conservation prioritization. First, we identified environmental drivers underpinning taxon-specific biodiversity patterns. Second, we analysed each taxon individually to understand baseline priority patterns. Third, we combined all taxa into an inclusive analysis to identify the most important PAN expansions. Results Biodiversity patterns were well explained by geographical factors (climate, habitat stability, isolation and area), but their explanatory power differed between the taxa. There was remarkably little overlap between priority areas for the individual higher taxa. The inclusive prioritization analysis across all taxa identified priority regions, in particular in southern subtropical and mountainous areas. Expanding the PAN up to 17% would cover most of the ranges for rare and/or restricted-range species. On average, approximately 30% of the ranges of all species could be covered by the 17% expansion identified here. Main conclusions Our analyses identified top candidates for the expansion of Japan's protected area network. Taxon-specific prioritization was informative for understanding the conservation priority patterns of different taxa associated with unique biogeographical processes. For the basis of PAN expansion, we recommend multi-taxon prioritization as an area-efficient compromise that reflects taxon-specific priority patterns. Spatial prioritization across multiple taxa provides a promising start for the development of conservation plans with the aim of long-term persistence of biodiversity on the East Asian islands.Peer reviewe

A geometric approach to scaling individual distributions to macroecological patterns

Understanding macroecological patterns across scales is a central goal of ecology and a key need for conservation biology. Much research has focused on quantifying and understanding macroecological patterns such as the species-area relationship (SAR), the endemic-area relationship (EAR) and relative species abundance curve (RSA). Understanding how these aggregate patterns emerge from underlying spatial pattern at individual level, and how they relate to each other, has both basic and applied relevance. To address this challenge, we develop a novel spatially explicit geometric framework to understand multiple macroecological patterns, including the SAR, EAR, RSA, and their relationships. First, we provide a general theory that can be used to derive the asymptotic slopes of the SAR and EAR, and demonstrates the dependency of RSAs on the shape of the sampling region. Second, assuming specific shapes of the sampling region, species geographic ranges, and individual distribution patterns therein based on theory of stochastic point processes, we demonstrate various well-documented macroecological patterns can be recovered, including the tri-phasic SAR and various RSAs (e.g., Fisher\u27s logseries and the Poisson lognormal distribution). We also demonstrate that a single equation unifies RSAs across scales, and provide a new prediction of the EAR. Finally, to demonstrate the applicability of the proposed model to ecological questions, we provide how beta diversity changes with spatial extent and its grain over multiple scales. Emergent macroecological patterns are often attributed to ecological and evolutionary mechanisms, but our geometric approach still can recover many previously observed patterns based on simple assumptions about species geographic ranges and the spatial distribution of individuals, emphasizing the importance of geometric considerations in macroecological studies

Quantifying sample completeness and comparing diversities among assemblages.

We develop a novel class of measures to quantify sample completeness of a biological survey. The class of measures is parameterized by an order q ≥ 0 to control for sensitivity to species relative abundances. When q = 0, species abundances are disregarded and our measure reduces to the conventional measure of completeness, that is, the ratio of the observed species richness to the true richness (observed plus undetected). When q = 1, our measure reduces to the sample coverage (the proportion of the total number of individuals in the entire assemblage that belongs to detected species), a concept developed by Alan Turing in his cryptographic analysis. The sample completeness of a general order q ≥ 0 extends Turing's sample coverage and quantifies the proportion of the assemblage's individuals belonging to detected species, with each individual being proportionally weighted by the (q − 1)th power of its abundance. We propose the use of a continuous profile depicting our proposed measures with respect to q ≥ 0 to characterize the sample completeness of a survey. An analytic estimator of the diversity profile and its sampling uncertainty based on a bootstrap method are derived and tested by simulations. To compare diversity across multiple assemblages, we propose an integrated approach based on the framework of Hill numbers to assess (a) the sample completeness profile, (b) asymptotic diversity estimates to infer true diversities of entire assemblages, (c) non‐asymptotic standardization via rarefaction and extrapolation, and (d) an evenness profile. Our framework can be extended to incidence data. Empirical data sets from several research fields are used for illustration.publishedVersionPaid Open Acces

Past and future decline of tropical pelagic biodiversity

Author's accepted version (postprint).This is an Accepted Manuscript of an article published by the National Academy of Sciences in PNAS on 26/05/2020.Available online: https://www.pnas.org/content/pnas/117/23/12891.full.pdfA major research question concerning global pelagic biodiversity remains unanswered: when did the apparent tropical biodiversity depression (i.e., bimodality of latitudinal diversity gradient [LDG]) begin? The bimodal LDG may be a consequence of recent ocean warming or of deep-time evolutionary speciation and extinction processes. Using rich fossil datasets of planktonic foraminifers, we show here that a unimodal (or only weakly bimodal) diversity gradient, with a plateau in the tropics, occurred during the last ice age and has since then developed into a bimodal gradient through species distribution shifts driven by postglacial ocean warming. The bimodal LDG likely emerged before the Anthropocene and industrialization, and perhaps ∼15,000 y ago, indicating a strong environmental control of tropical diversity even before the start of anthropogenic warming. However, our model projections suggest that future anthropogenic warming further diminishes tropical pelagic diversity to a level not seen in millions of years.acceptedVersio

Plant dispersal strategies of high tropical alpine communities across the Andes

Dispersal is a key ecological process that influences plant community assembly. Therefore, understanding whether dispersal strategies are associated with climate is of utmost importance, particularly in areas greatly exposed to climate change. We examined alpine plant communities located in the mountain summits of the tropical Andes across a 4,000-km latitudinal gradient. We investigated species dispersal strategies and tested their association with climatic conditions and their evolutionary history. We used dispersal-related traits (dispersal mode and growth form) to characterize dispersal strategies for 486 species recorded on 49 mountain summits. Then we analysed the phylogenetic signal of traits and investigated the association between dispersal traits, phylogeny, climate and space using structural equation modelling and fourth-corner analysis together with RLQ ordination. A median of 36% species in the communities was anemochorous (wind-dispersed) and herbaceous. This dispersal strategy was followed by the barochory-herb combination (herbaceous with unspecialized seeds, dispersed by gravity) with a median of 26.3% species in the communities. The latter strategy was common among species with distributions restricted to alpine environments. While trait states were phylogenetically conserved, they were significantly associated with a temperature gradient. Low minimum air temperatures, found at higher latitudes/elevations, were correlated with the prevalence of barochory and the herb growth form, traits that are common among Caryophyllales, Brassicaceae and Poaceae. Milder temperatures, found at lower latitudes/elevations, were associated with endozoochorous, shrub species mostly from the Ericaceae family. Anemochorous species were found all along the temperature gradient, possibly due to the success of anemochorous Compositae species in alpine regions. We also found that trait state dominance was more associated with the climatic conditions of the summit than with community phylogenetic structure. Although the evolutionary history of the tropical Andean flora has also shaped dispersal strategies, our results suggest that the environment had a more predominant role. Synthesis. We showed that dispersal-related traits are strongly associated with a gradient of minimum air temperatures in the Andes. Global warming may weaken this key filter at tropical alpine summits, potentially altering community dispersal strategies in this region and thus, plant community structure and composition.Fil: Tovar, Carolina. Royal Botanic Gardens; Reino UnidoFil: Melcher, Inga. University of Amsterdam; Países BajosFil: Kusumoto, Buntarou. Royal Botanic Gardens; Reino Unido. University Of The Ryukyus, Okinawa; JapónFil: Cuesta, Francisco. Universidad de Las Américas.; EcuadorFil: Cleef, Antoine. University of Amsterdam; Países BajosFil: Meneses, Rosa Isela. Universidad Católica del Norte; ChileFil: Halloy, Stephan. Ministry For Primary Industries; Nueva ZelandaFil: Llambi, Luis Daniel. Universidad de Los Andes; VenezuelaFil: Beck, Stephan G.. Universidad Mayor de San Andrés; BoliviaFil: Muriel, Priscilla. Pontificia Universidad Católica del Ecuador; EcuadorFil: Jaramillo, Ricardo Luis. Pontificia Universidad Católica del Ecuador; EcuadorFil: Jacome, Jorge. Pontificia Universidad Javeriana; ColombiaFil: Carilla, Julieta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentin

Global raster dataset on historical coastline positions and shelf sea extents since the Last Glacial Maximum

Motivation: Historical changes in sea level caused shifting coastlines that affected the distribution and evolution of marine and terrestrial biota. At the onset of the Last Glacial Maximum (LGM) 26 ka, sea levels were >130 m lower than at present, resulting in seaward-shifted coastlines and shallow shelf seas, with emerging land bridges leading to the isolation of marine biota and the connection of land-bridge islands to the continents. At the end of the last ice age, sea levels started to rise at unprecedented rates, leading to coastal retreat, drowning of land bridges and contraction of island areas. Although a growing number of studies take historical coastline dynamics into consideration, they are mostly based on past global sea-level stands and present-day water depths and neglect the influence of global geophysical changes on historical coastline positions. Here, we present a novel geophysically corrected global historical coastline position raster for the period from 26 ka to the present. This coastline raster allows, for the first time, calculation of global and regional coastline retreat rates and land loss rates. Additionally, we produced, per time step, 53 shelf sea rasters to present shelf sea positions and to calculate the shelf sea expansion rates. These metrics are essential to assess the role of isolation and connectivity in shaping marine and insular biodiversity patterns and evolutionary signatures within species and species assemblages. Main types of variables contained: The coastline age raster contains cells with ages in thousands of years before present (bp), representing the time since the coastline was positioned in the raster cells, for the period between 26 ka and the present. A total of 53 shelf sea rasters (sea levels <140 m) are presented, showing the extent of land (1), shelf sea (0) and deep sea (NULL) per time step of 0.5 kyr from 26 ka to the present. Spatial location and grain: The coastline age raster and shelf sea rasters have a global representation. The spatial resolution is scaled to 120 arcsec (0.333° × 0.333°), implying cells of c. 3,704 m around the equator, 3,207 m around the tropics (±30°) and 1,853 m in the temperate zone (±60°). Time period and temporal resolution: The coastline age raster shows the age of coastline positions since the onset of the LGM 26 ka, with time steps of 0.5 kyr. The 53 shelf sea rasters show, for each time step of 0.5 kyr, the position of the shelf seas (seas shallower than 140 m) and the extent of land. Level of measurement: Both the coastline age raster and the 53 shelf sea rasters are provided as TIFF files with spatial reference system WGS84 (SRID 4326). The values of the coastline age raster per grid cell correspond to the most recent coastline position (in steps of 0.5 kyr). Values range from 0 (0 ka, i.e., present day) to 260 (26 ka) in bins of 5 (0.5 kyr). A value of “no data” is ascribed to pixels that have remained below sea level since 26 ka. Software format: All data processing was done using the R programming language

Global raster dataset on historical coastline positions and shelf sea extents since the Last Glacial Maximum

Abstract Motivation Historical changes in sea level caused shifting coastlines that affected the distribution and evolution of marine and terrestrial biota. At the onset of the Last Glacial Maximum (LGM) 26 ka, sea levels were >130?m lower than at present, resulting in seaward-shifted coastlines and shallow shelf seas, with emerging land bridges leading to the isolation of marine biota and the connection of land-bridge islands to the continents. At the end of the last ice age, sea levels started to rise at unprecedented rates, leading to coastal retreat, drowning of land bridges and contraction of island areas. Although a growing number of studies take historical coastline dynamics into consideration, they are mostly based on past global sea-level stands and present-day water depths and neglect the influence of global geophysical changes on historical coastline positions. Here, we present a novel geophysically corrected global historical coastline position raster for the period from 26 ka to the present. This coastline raster allows, for the first time, calculation of global and regional coastline retreat rates and land loss rates. Additionally, we produced, per time step, 53 shelf sea rasters to present shelf sea positions and to calculate the shelf sea expansion rates. These metrics are essential to assess the role of isolation and connectivity in shaping marine and insular biodiversity patterns and evolutionary signatures within species and species assemblages. Main types of variables contained The coastline age raster contains cells with ages in thousands of years before present (bp), representing the time since the coastline was positioned in the raster cells, for the period between 26 ka and the present. A total of 53 shelf sea rasters (sea level

A theory for ecological survey methods to map individual distributions

Spatially explicit approaches are widely recommended for ecosystem management. The quality of the data, such as presence/absence or habitat maps, affects the management actions recommended and is, therefore, key to management success. However, available data are often biased and incomplete. Previous studies have advanced ways to resolve data bias and missing data, but questions remain about how we design ecological surveys to develop a dataset through field surveys. Ecological surveys may have multiple spatial scales, including the spatial extent of the target ecosystem (observation window), the resolution for mapping individual distributions (mapping unit), and the survey area within each mapping unit (sampling unit). We developed an ecological survey method for mapping individual distributions by applying spatially explicit stochastic models. We used spatial point processes to describe individual spatial placements using either random or clustering processes. We then designed ecological surveys with different spatial scales and individual detectability. We found that the choice of mapping unit affected the presence mapped fraction, and the fraction of the total individuals covered by the presence mapped patches. Tradeoffs were found between these quantities and the map resolution, associated with equivalent asymptotic behaviors for both metrics at sufficiently small and large mapping unit scales. Our approach enabled consideration of the effect of multiple spatial scales in surveys, and estimation of the survey outcomes such as the presence mapped fraction and the number of individuals situated in the presence detected units. The developed theory may facilitate management decision-making and inform the design of monitoring and data gathering