scholarly journals A framework for disentangling ecological mechanisms underlying the island species-area relationship

2018 ◽  
Author(s):  
Jonathan M. Chase ◽  
Leana Gooriah ◽  
Felix May ◽  
Wade A. Ryberg ◽  
Matthew S. Schuler ◽  
...  
Keyword(s):  
Random Sampling ◽  
Spatial Scales ◽  
Biodiversity Loss ◽  
Oceanic Islands ◽  
Island Area ◽  
Rarefaction Curves ◽  
Island Species ◽  
Species Area ◽  
Ecological Mechanisms ◽  
Species Area Relationship

AbstractThe relationship between an island’s size and the number of species on that island—the island species-area relationship (ISAR)—is one of the most well-known patterns in biogeography, and forms the basis for understanding biodiversity loss in response to habitat loss and fragmentation. Nevertheless, there is contention about exactly how to estimate the ISAR, and the influence of the three primary ecological mechanisms—random sampling, disproportionate effects, and heterogeneity— that drive it. Key to this contention is that estimates of the ISAR are often confounded by sampling and estimates of measures (i.e., island-level species richness) that are not diagnostic of potential mechanisms. Here, we advocate a sampling-explicit approach for disentangling the possible ecological mechanisms underlying the ISAR using parameters derived from individual-based rarefaction curves estimated across spatial scales. If the parameters derived from rarefaction curves at each spatial scale show no relationship with island area, we cannot reject the hypothesis that ISARs result only from random sampling. However, if the derived metrics change with island area, we can reject random sampling as the only operating mechanism, and infer that effects beyond sampling (i.e., disproportionate effects and/or heterogeneity) are also operating. Finally, if parameters indicative of within-island spatial variation in species composition (i.e., β-diversity) increase with island area, we can conclude that intra-island compositional heterogeneity plays a role in driving the ISAR. We illustrate this approach using representative case studies, including oceanic islands, natural island-like patches, and habitat fragments from formerly continuous habitat, illustrating several combinations of underlying mechanisms. This approach will offer insight into the role of sampling and other processes that underpin the ISAR, providing a more complete understanding of how, and some indication of why, patterns of biodiversity respond to gradients in island area.

scholarly journals A framework for disentangling ecological mechanisms underlying the island species–area relationship

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Jonathan M. Chase ◽  
Leana Gooriah ◽  
Felix May ◽  
Wade A. Ryberg ◽  
Matthew S. Schuler ◽  
...  
Keyword(s):  
Island Species ◽  
Species Area ◽  
Ecological Mechanisms ◽  
Species Area Relationship

scholarly journals Maintenance of biodiversity on islands

2016 ◽  
Vol 283 (1829) ◽  
pp. 20160102 ◽  
Author(s):  
Ryan A. Chisholm ◽  
Tak Fung ◽  
Deepthi Chimalakonda ◽  
James P. O'Dwyer
Keyword(s):  
Species Richness ◽  
Island Biogeography ◽  
Mechanistic Model ◽  
Neutral Theory ◽  
Small Island ◽  
Small Islands ◽  
Island Area ◽  
Island Species ◽  
Theory Of Island Biogeography ◽  
Species Area

MacArthur and Wilson's theory of island biogeography predicts that island species richness should increase with island area. This prediction generally holds among large islands, but among small islands species richness often varies independently of island area, producing the so-called ‘small-island effect’ and an overall biphasic species–area relationship (SAR). Here, we develop a unified theory that explains the biphasic island SAR. Our theory's key postulate is that as island area increases, the total number of immigrants increases faster than niche diversity. A parsimonious mechanistic model approximating these processes reproduces a biphasic SAR and provides excellent fits to 100 archipelago datasets. In the light of our theory, the biphasic island SAR can be interpreted as arising from a transition from a niche-structured regime on small islands to a colonization–extinction balance regime on large islands. The first regime is characteristic of classic deterministic niche theories; the second regime is characteristic of stochastic theories including the theory of island biogeography and neutral theory. The data furthermore confirm our theory's key prediction that the transition between the two SAR regimes should occur at smaller areas, where immigration is stronger (i.e. for taxa that are better dispersers and for archipelagos that are less isolated).

scholarly journals The species-area relationship: new challenges for an old pattern

2001 ◽  
Vol 25 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Mark V. Lomolino
Keyword(s):  
Secondary Phase ◽  
Species Number ◽  
General Tendency ◽  
Small Islands ◽  
Stochastic Variation ◽  
Causal Explanations ◽  
Island Area ◽  
Species Area ◽  
Species Area Relationship ◽  
The Relationship

The species-area relationship (i.e., the relationship between area and the number of species found in that area) is one of longest and most frequently studied patterns in nature. Yet there remain some important and interesting questions on the nature of this relationship, its causality, quantification and application for both ecologists and conservation biologists. Traditionally, the species-area relationship describes the very general tendency for species number to increase with island area; a relationship whose slope declines (but remains positive) as area increases. The true relationship, however, may be much more complicated than this, and may in many cases approximate a sigmoidal relationship. On small islands, species number may vary independently of island area. Species richness then increases as we consider larger islands, but the curve eventually slows and asymptotes or levels off when richness equals that of the the source or mainland pool. The relationship may also include a secondary phase of increase in richness if island area becomes large enough to allow in situ speciation. Causal explanations for this relationship may, therefore, need to be multifactorial and include a range of processes from disturbance and stochastic variation in habitat quality on the very small islands, to ecological interactions, immigration, extinction and, finally, evolution on the larger islands.

scholarly journals Habitat fragmentation, biodiversity loss and the risk of novel infectious disease emergence

2018 ◽  
Vol 15 (149) ◽  
pp. 20180403 ◽  
Author(s):  
David A. Wilkinson ◽  
Jonathan C. Marshall ◽  
Nigel P. French ◽  
David T. S. Hayman
Keyword(s):  
Habitat Fragmentation ◽  
Tropical Forests ◽  
Biodiversity Loss ◽  
Mitigation Measures ◽  
Infectious Agents ◽  
Disease Emergence ◽  
Zoonotic Infections ◽  
Species Area ◽  
Risk Areas ◽  
Species Area Relationship

The number of microbes on Earth may be 10 30 , exceeding all other diversity. A small number of these can infect people and cause disease. The diversity of parasitic organisms likely correlates with the hosts they live in and the number mammal hosts for zoonotic infections increases with species richness among mammalian orders. Thus, while habitat loss and fragmentation may reduce species diversity, the habitat encroachment by people into species-rich areas may increase the exposure of people to novel infectious agents from wildlife. Here, we present a theoretical framework that exploits the species–area relationship to link the exposure of people to novel infections with habitat biodiversity. We model changes in human exposure to microbes through defined classes of habitat fragmentation and predict that increased habitat division intrinsically increases the hazard from microbes for all modelled biological systems. We apply our model to African tropical forests as an example. Our results suggest that it is possible to identify high-risk areas for the mitigation and surveillance of novel disease emergence and that mitigation measures may reduce this risk while conserving biodiversity.

scholarly journals Species-Area Relationship and Its Scale-Dependent Effects in Natural Forests of North Eastern China

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 422
Author(s):  
Beibei Chen ◽  
Jun Jiang ◽  
Xiuhai Zhao
Keyword(s):  
Random Sampling ◽  
Logistic Model ◽  
Sampling Methods ◽  
Scale Transformation ◽  
Nested Sampling ◽  
Area Model ◽  
Species Area ◽  
Species Area Relationship ◽  
The Relationship ◽  
Sampling Plot

The Species-area relationship is one of the core issues in community ecology and an important basis for scale transformation of biodiversity. However, the effect of scale on this relationship, together with the selection of an optimal species-area model for different sampling methods, is still controversial. This study is based on the data from two sampling areas of 40 km2 in size, one in a Korean pine (Pinus koraiensis Sieb. et Zucc) broad-leaved mixed forest in Mt. Changbai and the other in Jiaohe, Jilin Province. The logarithmic, power, and logistic model were established on a scale of 10 km2, 20 km2, and 30 km2, respectively, using a nested sampling plot and random sampling plot. The goodness of the species-area model was tested by the Akaike information criterion (AIC). The results show that the sampling method affected the relationship between species and area, and the data were fitted better under random sampling compared with nested sampling. The construction of the relationship between species and area was closely related to the upper limit of the sampling area size. On a small scale (10 km2), the data were fitted best with the logarithmic and logistic model, whereas the logistic model was the best fit on a medium (20 km2) and large scale (30 km2). We evaluated the scale dependence of species-area relationship in two forests with nested and random sampling methods. We further showed that the logistic model based on the random sampling plot can explain most soundly the species-area relationship in Jiaohe and Mt. Changbai. More studies are needed in other regions to develop models to optimize sampling designs for different forest types under different density constraints at different spatial scales, and for a more accurate estimation of forest dynamics under long-term observations.

scholarly journals The map of biodiversity: From local to global scales

2018 ◽  
Author(s):  
Maria Anton Pardo
Keyword(s):  
Environmental Variables ◽  
Environmental Heterogeneity ◽  
Spatial Scales ◽  
Global Scale ◽  
Local Scale ◽  
Habitat Size ◽  
Diversity Patterns ◽  
Regional Species Pool ◽  
Species Area ◽  
Species Area Relationship

Species richness is not homogeneous in space and it normally presents differences when comparing among different sites. These differences often respond to gradients in one or several factors which create biodiversity patterns in space and are scale-dependent. At a local scale, diversity patterns depend on the habitat size (species-area relationship), the productivity, the environmental harshness, the frequency and intensity of disturbance, or the regional species pool. Regional diversity may be influenced by environmental heterogeneity (increasing dissimilarity), although it could act also at smaller or larger spatial scales, and the connectivity among habitats. Finally, at a global scale, diversity patterns are found with the latitude, the altitude or the depth, although these factors are surrogates or one or several environmental variables (productivity, area, isolation, or harshness).

scholarly journals Environmental filtering underpins the island species—area relationship in a subtropical anthropogenic archipelago

2019 ◽  
Vol 108 (2) ◽  
pp. 424-432 ◽  
Author(s):  
Jinliang Liu ◽  
Thomas J. Matthews ◽  
Lei Zhong ◽  
Jiajia Liu ◽  
Donghao Wu ◽  
...  
Keyword(s):  
Environmental Filtering ◽  
Island Species ◽  
Species Area ◽  
Species Area Relationship
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