Fundamental equations for species-area theory

Pan, Xubin

doi:10.1038/srep01334

Cited by 16 publications

(14 citation statements)

References 6 publications

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“…Species–area relationships constitute one of the most general and well‐studied ecological patterns in the terrestrial realm (Arrhenius, ; Gleason, ; Williams, ; Preston, , ; MacArthur & Wilson, , ; Connor & McCoy, ; Allen & White, ; Scheiner, , ; Turner & Tjørve, ; Tjørve & Tjørve, ; Tjørve et al ., ; Triantis et al ., , ; Santos et al ., ; Whittaker & Triantis, ; Pan, ; Whittaker & Matthews, ; Matthews et al ., , ). However, this ‘protean pattern’ (see Lomolino, ) of a positive relationship between species richness and area has not been properly addressed for the marine realm.…”

Section: Introductionmentioning

confidence: 99%

Towards a ‘Sea‐Level Sensitive’ dynamic model: impact of island ontogeny and glacio‐eustasy on global patterns of marine island biogeography

et al. 2019

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A synthetic model is presented to enlarge the evolutionary framework of the General Dynamic Model (GDM) and the Glacial Sensitive Model (GSM) of oceanic island biogeography from the terrestrial to the marine realm. The proposed 'Sea-Level Sensitive' dynamic model (SLS) of marine island biogeography integrates historical and ecological biogeography with patterns of glacio-eustasy, merging concepts from areas as diverse as taxonomy, biogeography, marine biology, volcanology, sedimentology, stratigraphy, palaeontology, geochronology and geomorphology. Fundamental to the SLS model is the dynamic variation of the littoral area of volcanic oceanic islands (defined as the area between the intertidal and the 50-m isobath) in response to sea-level oscillations driven by glacial-interglacial cycles. The following questions are considered by means of this revision: (i) what was the impact of (global) glacio-eustatic sea-level oscillations, particularly those of the Pleistocene glacial-interglacial episodes, on the littoral marine fauna and flora of volcanic oceanic islands? (ii) What are the main factors that explain the present littoral marine biodiversity on volcanic oceanic islands? (iii) How can differences in historical and ecological biogeography be reconciled, from a marine point of view? These questions are addressed by compiling the bathymetry of 11 Atlantic archipelagos/islands to obtain quantitative data regarding changes in the littoral area based on Pleistocene sea-level oscillations, from 150 thousand 1117 years ago (ka) to the present. Within the framework of a model sensitive to changing sea levels, we discuss the principal factors affecting the geographical range of marine species; the relationships between modes of larval development, dispersal strategies and geographical range; the relationships between times of speciation, modes of larval development, ecological zonation and geographical range; the influence of sea-surface temperatures and latitude on littoral marine species diversity; the effect of eustatic sea-level changes and their impact on the littoral marine biota; island marine species-area relationships; and finally, the physical effects of island ontogeny and its associated submarine topography and marine substrate on littoral biota. Based on the SLS dynamic model, we offer a number of predictions for tropical, subtropical and temperate volcanic oceanic islands on how rates of immigration, colonization, in-situ speciation, local disappearance, and extinction interact and affect the marine biodiversity around islands during glacials and interglacials, thus allowing future testing of the theory.

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Section: Introductionmentioning

confidence: 99%

Towards a ‘Sea‐Level Sensitive’ dynamic model: impact of island ontogeny and glacio‐eustasy on global patterns of marine island biogeography

et al. 2019

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“…Habitat management for biodiversity conservation relies on two main principles, the species-area relationship (SAR) and the intermediate disturbance hypothesis (IDH, Connell 1978). According to the SAR, the number of species generally increases with area (Connor and McCoy 2001;Pan 2013), thus, management of larger habitat patches should conserve more species. However, the relationship between the area and number of species is not linear; initially the increment of the species is fast, but becomes slower as area increases (Báldi and Kisbenedek 2000;Celada and Bogliani 1993;Paracuellos and Tellería 2004).…”

Section: Introductionmentioning

confidence: 99%

Habitat management varying in space and time: the effects of grazing and fire management on marshland birds

Mérő¹,

Lontay

Lengyel

2015

J Ornithol

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(for four years) and late-summer burning (one or three years before the study) on both songbirds 29 and non-passerines in a previously homogeneous reedbed. We surveyed birds by a combination 30 of line transects and point counts in a quasi-experimental design consisting of six treatment 31 levels. Management led to a higher diversity of marsh habitats and increased bird diversity. The 32 species richness and abundance of non-passerines (ducks and geese, wading birds, gulls and 33 terns, rails, coots and grebes) was higher in recently burned than in unburned or old-burned 34 patches. The species richness of farmland songbirds was higher in grazed patches than in non-35 grazed patches, and reed songbirds had higher richness and abundance in unburned, old-burned 36 or grazed patches than in recently burned patches. Total Shannon diversity and evenness of birds

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“…Direct estimates of biodiversity loss are challenging because of highly incomplete global species' distribution knowledge 4 and the difficulties of ascertaining actual extinctions 5 6 7 . Instead, estimates of diversity loss have relied on indirect methods, such as the relationship between area and the number of species in that area, the species–area relationship (SAR) 8 9 10 11 , or the relationship between an area that is lost and the number of species confined to it, the endemics–area relationship (EAR) 12 13 .…”

mentioning

confidence: 99%

“…Recently, He and Hubbell 12 initiated discussion over the reliability of the indirect methods, claiming that the SAR-based method (also known as backward estimation) overestimates extinctions when compared with the EAR-based method (forward estimation). This debate has generated several valuable insights, such as recognition that EAR and SAR are linked by the complementarity of area that is lost and the area that remains 14 , recognition of point reflection symmetry of the two curves 13 , or identification of critical role of aggregation of individuals 15 and ecological context 16 17 at small-scale plots. However, this debate has not yet been settled, and there are still critical unresolved issues, as well as opportunities for synthesis.…”

mentioning

confidence: 99%

On the decline of biodiversity due to area loss

2015

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Predictions of how different facets of biodiversity decline with habitat loss are broadly needed, yet challenging. Here we provide theory and a global empirical evaluation to address this challenge. We show that extinction estimates based on endemics–area and backward species–area relationships are complementary, and the crucial difference comprises the geometry of area loss. Across three taxa on four continents, the relative loss of species, and of phylogenetic and functional diversity, is highest when habitable area disappears inward from the edge of a region, lower when it disappears from the centre outwards, and lowest when area is lost at random. In inward destruction, species loss is almost proportional to area loss, although the decline in phylogenetic and functional diversity is less severe. These trends are explained by the geometry of species ranges and the shape of phylogenetic and functional trees, which may allow baseline predictions of biodiversity decline for underexplored taxa.

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Fundamental equations for species-area theory

Cited by 16 publications

References 6 publications

Towards a ‘Sea‐Level Sensitive’ dynamic model: impact of island ontogeny and glacio‐eustasy on global patterns of marine island biogeography

Towards a ‘Sea‐Level Sensitive’ dynamic model: impact of island ontogeny and glacio‐eustasy on global patterns of marine island biogeography

Habitat management varying in space and time: the effects of grazing and fire management on marshland birds

On the decline of biodiversity due to area loss

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