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Species richness scaling relationships require log-transformation of area.
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3 sources for · 5 against

The evidence shows that species-area relationships are expressed through multiple mathematical forms, including both power laws and logarithmic relationships, reflecting an ongoing debate where different frameworks are actively applied.

Evidence for · 3
2024 · cited by 6
Species–area relationships (SAR) are widely utilized for estimating the species richness and its spatial turnover across various scales. Despite the prevalent characterization of SAR using the power law in many microbial community studies, its efficacy remains unvalidated. This study aims to characterize the microbial SAR and its mechanisms in alpine grassland soils on the Qinghai‐Tibet Plateau (QTP).Qinghai‐Tibet Plateau, China.August 2014.Soil bacteria.Soil samples were collected from five alpine grassland sites on the QTP. Employing a nested sampling strategy at each site, soil samples were collected in plot sizes ranging from 0.5 × 0.5 m2 to 2048 × 2048 m2. Soil bacterial communities were analysed by sequencing 16S ribosomal RNA gene amplicons using an Illumina MiSeq.The bacterial SAR exhibited a logarithmic power law (R2: 0.952–0.999), outperforming the power law (R2: 0.701–0.852). Consequently, the most widely adopted power law led to an overestimation of species richness by up to 15.07% in areas >256 × 256 m2, and the regional maximum theoretical richness based on Chao1 by up to 9.88%. Mechanistically, the passive sampling hypothesis was refuted through the rarefied species richness analysis, and the disproportionate effect hypothesis was rejected based on analyses of the effective numbers of species number conversions for the probability of interspecific encounters (SPIE). Notably, Pearson and multiple linear regression analyses indicated that the spatial turnover of bacterial richness was determined by the environmental heterogeneity (R2: 0.855–0.999), rather or better than environmental variables themselves, supporting the ‘environment heterogeneity hypothesis’.Soil bacterial SAR in alpine grasslands exhibited a logarithmic power relationship. Spatial turnover was primarily governed by the environmental heterogeneity. In contrast, the traditional power law leads to an overestimation of soil bacterial diversity at the regional scale.
Evidence against · 5
2006 · cited by 690
Habitat loss has pervasive and disruptive impacts on biodiversity in habitat remnants. The magnitude of the ecological impacts of habitat loss can be exacerbated by the spatial arrangement -- or fragmentation -- of remaining habitat. Fragmentation per se is a landscape-level phenomenon in which species that survive in habitat remnants are confronted with a modified environment of reduced area, increased isolation and novel ecological boundaries. The implications of this for individual organisms are many and varied, because species with differing life history strategies are differentially affected by habitat fragmentation. Here, we review the extensive literature on species responses to habitat fragmentation, and detail the numerous ways in which confounding factors have either masked the detection, or prevented the manifestation, of predicted fragmentation effects. Large numbers of empirical studies continue to document changes in species richness with decreasing habitat area, with positive, negative and no relationships regularly reported. The debate surrounding such widely contrasting results is beginning to be resolved by findings that the expected positive species-area relationship can be masked by matrix-derived spatial subsidies of resources to fragment-dwelling species and by the invasion of matrix-dwelling species into habitat edges. Significant advances have been made recently in our understanding of how species interactions are altered at habitat edges as a result of these changes. Interestingly, changes in biotic and abiotic parameters at edges also make ecological processes more variable than in habitat interiors. Individuals are more likely to encounter habitat edges in fragments with convoluted shapes, leading to increased turnover and variability in population size than in fragments that are compact in shape. Habitat isolation in both space and time disrupts species distribution patterns, with consequent effects on metapopulation dynamics and the genetic structure of fragment-dwelling populations. Again, the matrix habitat is a strong determinant of fragmentation effects within remnants because of its role in regulating dispersal and dispersal-related mortality, the provision of spatial subsidies and the potential mediation of edge-related microclimatic gradients. We show that confounding factors can mask many fragmentation effects. For instance, there are multiple ways in which species traits like trophic level, dispersal ability and degree of habitat specialisation influence species-level responses. The temporal scale of investigation may have a strong influence on the results of a study, with short-term crowding effects eventually giving way to long-term extinction debts. Moreover, many fragmentation effects like changes in genetic, morphological or behavioural traits of species require time to appear. By contrast, synergistic interactions of fragmentation with climate change, human-altered disturbance regimes, species interactions and other drivers of population decline may magnify the impacts of fragmentation. To conclude, we emphasise that anthropogenic fragmentation is a recent phenomenon in evolutionary time and suggest that the final, long-term impacts of habitat fragmentation may not yet have shown themselves.
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rails:sufficiency:refuted:for=0+3p:against=2+3p:partial_opposition=3 | v55:sufficiency | v55:coherence_repaired:what=both

More for · 2
2019 · cited by 0
Summary Global biodiversity is declining at rates faster than at any other point in human history. Experimental manipulations of biodiversity at small spatial scales have demonstrated that communities with fewer species consistently produce less biomass than higher diversity communities. However, understanding how the global extinction crisis is likely to impact global ecosystem functioning will require applying these local and largely experimental findings to natural systems at substantially larger spatial and temporal scales. Here we propose that we can use two simple macroecological patterns – the species area curve and the biomass-area curve – to upscale the species richness-biomass relationship. We demonstrate that at local spatial scales, each additional species will contribute more to biomass production with increasing area sampled because the species-area curve saturates and the biomass-area curve increases monotonically. We use species-area and biomass-area curves from a Minnesota grassland and a Panamanian tropical dry forest to examine the species richness – biomass relationship at three and ten sampling extents, respectively. In both datasets, the observed relationship between biodiversity and biomass production at every sampling extent was predicted from simple species-area and biomass-area relationships. These findings suggest that macroecological patterns like the species-area curve underpin the scaling of biodiversity-ecosystem functioning research and can be
cited by 0
# Species richness corrected for area -- should area be log-transformed? Tags: ecology, community-ecology - Score: 9 - Views: 533 - Answers: 1 - Answered: yes - Asked by: Kayleigh Nielson (91 rep) - Asked: 2017-09-10 - Site: biology ## Question I am doing a study to compare plant species richness (total number of species per site) to a bunch of environmental factors of sites at which these plants were surveyed. Because these sites are different in size, I have converted species richness to a species density measurement by dividing by the log of site area (species density = species richness/log[area]). I log-transformed area, because the relationship between species richness and area at my sites is linear on a semi-log scale. Now that I have calculated species density in this way, I am having a hard time convincing myself that calculating density with log(area) was the correct approach. Does anyone have some insight on this? My community ecology background is not strong and I am getting bogged down in the literature. Thanks! ## Answers ### Answer by vkehayas (score: 2) Let me offer my answer even though I have not worked in ecology. You are asking two questions if I under
More against · 4
2023 · cited by 7
The species-area relationship (SAR) is widely applied in ecology. Mathematically, it is usually expressed as either a semi-log or power-law relationship, with the former being introduced by Gleason and the latter by Arrhenius. We here resolve the dispute about which form of the SAR to prefer by introducing a novel model that smoothly transforms between the Gleason semi-log (GSL) and Arrhenius power law (APL) forms. The model introduced has the form of lnq (S) = a + z ln A, with lnq being a generalized logarithmic function, which is a linear map (y = x) for q = 0 and a logarithmic map (y = ln x) for q = 1 and q can take any intermediate value between 0 and 1. We applied this model to 100 datasets (mostly islands), linking species richness to island area. The APL was the preferred model in 68% of head-to-head comparisons with the GSL. Both models were supported in 40% of cases. In just under half (44%) of the cases, an intermediate model best explained the data. The results demonstrate the utility of a simple intermediate SAR model. Visualizing the profile of the range of model fits for all q ∈ [0, 1] (a q chart) allows us to gain extra insight into SARs not yielded by head-to-head comparisons of GSL and APL. The mathematics related to the generalized logarithmic function introduced here should have applications to other areas of ecological modelling.
2012 · cited by 6
We studied the mathematical relations between species abundance distributions (SADs) and species-area relationships (SARs) and found that a power-law SAR can be generally derived from a power-law SAD without a special assumption such as the "canonical hypothesis". In the present analysis, an SAR-exponent is obtained as a function of an SAD-exponent for a finite number of species. We also studied the inverse problem, from SARs to SADs, and found that a power-SAD can be derived from a power-SAR under the condition that the functional form of the corresponding SAD is invariant for changes in the number of species. We also discuss general relationships among lognormal SADs, the broken-stick model (exponential SADs), linear SARs and logarithmic SARs. These results suggest the existence of a common mechanism for SADs and SARs, which could prove a useful tool for theoretical and experimental studies on biodiversity and species coexistence.
cited by 0
Generalized Logarithmic Species-Area Relationship Resolves the Arrhenius-Gleason Debate | Environmental Modeling & Assessment | Springer Nature Link # Generalized Logarithmic Species-Area Relationship Resolves the Arrhenius-Gleason Debate - Open access - Published: 22 February 2023 - Volume 28, pages 491–499 (2023) - Cite this article You have full access to this open access article Environmental Modeling & Assessment ## Abstract The species-area relationship (SAR) is widely applied in ecology. Mathematically, it is usually expressed as either a semi-log or power-law relationship, with the former being introduced by Gleason and the latter by Arrhenius. We here resolve the dispute about which form of the SAR to prefer by introducing a novel model that smoothly transforms between the Gleason semi-log (GSL) and Arrhenius power law (APL) forms. The model introduced has the form of lnq (S) = a + z ln A, with lnq being a generalized logarithmic function, which is a linear map (y = x) for q = 0 and a logarithmic map (y = ln x) for q = 1 and q can take any intermediate value between 0 and 1. We applied this model to 100 datasets (mostly islands), linking species richness to island a
cited by 0
Which Models Are Appropriate for Six Subtropical Forests: Species-Area and Species-Abundance Models | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here. ## Figures ## Abstract The species-area relationship is one of the most important topic in the study of species diversity, conservation biology and landscape ecology. The species-area relationship curves describe the increase of species number with increasing area, and have been modeled by various equations. In this paper, we used detailed data from six 1-ha subtropical forest communities to fit three species-area relationship models. The coefficient of determination and F ratio of ANOVA showed all the three models fitted well to the species-area relationship data in the subtropical communities, with the logarithm model performing better than the other two models. We also used the three species-abundance distributions, namely the lognormal, logcauchy and logseries model, to fit them to the species-abundance data of six communities. In this case, the logcauchy model had the better fit based on the coefficient of determinati
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