Habitat fragmentation and species diversity in competitive communities

Rybicki, Joel; Abrego, Nerea; Ovaskainen, Otso

doi:10.1111/ele.13450

Cited by 101 publications

(73 citation statements)

References 52 publications

(145 reference statements)

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“…Large areas of habitat tend to support more individuals, and hence, more species (Rosenzweig 1995). Increasing fragmentation may be detrimental if little habitat is available, but intermediate degrees of fragmentation may be beneficial for competitive communities when the amount of habitat is fairly high (Rybicki, Abrego, and Ovaskainen 2020). Besides modifying the spatial pattern of the landscape, habitat size reduction and increase of isolation cause an alteration of the dispersal rate, affecting survival, and mortality of individuals (Fahrig and Merriam 1994;Hanski 1994).…”

Section: Effects Of Landscape Change On Oristic Composition and Strucmentioning

confidence: 99%

WITHDRAWN: Effects of Landscape Change on Floristic Composition and Structure in the Bale Mountains National Park, Southeastern Ethiopia

Muhammed¹,

Elias

2020

Preprint

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BackgroundBale mountains national park (BMNP) is one of the 34 International Biodiversity Hotspots that comprise a variety of life forms. However, it faces a critical challenge from subsistence farming and overgrazing. This study was made to analyze the effects of landscape change on floristic composition, diversity, and structure in BMNP. The vegetation and environmental data were collected from 96 plots that were laid along 8 line transects. Vegetation hierarchical clustering and landscape structural analysis was made using R software version 3.5.2 and FRAGSTATS version 4.2.1, respectively. ResultsA total of 205 species that belongs to 153 genera and 71 families were identified. The overall Shannon diversity and evenness index was 4.34 and 0.81, respectively. Both the species richness and Shannon diversity index were significantly higher (p < 0.05) in the edge habitat (40 ± 0.2 and 2.93 ± 0.2, respectively) than the interior (25 ± 4.5 and 2.43 ± 0.4, respectively). Conversely, the basal area was lower in the interior habitat (173.79 m2 ha-1) than the edge (64.15 m2 ha-1). Moreover, as AREA_MN and COA of patches increases, species richness, diversity, evenness, woody species density, basal area, DBH, and height also increases. Whereas, as PN, SHAPE_MN, ED, ENN_MN, and IJI of patches increases, those floristic compositions and structural variables decrease. ConclusionThis study revealed that BMNP is a biologically diverse and ecologically significant area that provides a variety of ecological and economic benefits to the surrounding communities and the country at large. However, its landscape is changing alarmingly and urgent restoration and conservation action needs to be taken to reverse this condition.

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Section: Effects Of Landscape Change On Oristic Composition and Strucmentioning

confidence: 99%

WITHDRAWN: Effects of Landscape Change on Floristic Composition and Structure in the Bale Mountains National Park, Southeastern Ethiopia

Muhammed¹,

Elias

2020

Preprint

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“…By contrast, the species-fragmented area relationship suggests that negative effects of FPS should reduce gamma-diversity compared to that predicted by the species-area relationship alone (Hanski et al, 2013). However, patch-scale studies and the modeling that describes the species-fragmented area relationship do not take into consideration mechanisms that can lead to positive effects of fragmentation, such as increased beta-diversity caused by competitive release and higher habitat diversity (Fahrig et al, 2019;Rybicki et al, 2019). These mechanisms may increase beta-diversity and thus lead to overall increases in gamma-diversity with FPS.…”

Section: Introductionmentioning

confidence: 99%

“…Theoretical modeling is a useful way to address contested issues where field data are difficult to collect and are subject to confounding variables. To this end, simulation models have been used to study FPS, which represent individual organisms moving across simulated landscapes (Gunton et al, 2017;Rybicki et al, 2019;Thompson et al, 2019). However, these studies are conducted on binary landscapes with the space between the focal-habitat patches (the habitat type of interest), the matrix, being a single, usually highly unsuitable, habitat type.…”

Section: Introductionmentioning

confidence: 99%

“…With only a single matrix habitat, one possible mechanism of FPS benefits is lost, that of increased habitat diversity. FPS can increase the diversity of other habitats adjacent to focal-habitat patches, and that in turn can increase the beta diversity of inhabitants of the focal-habitat (Fahrig et al, 2019;Rybicki et al, 2019). By having multiple matrix habitats, edge effects, which are typically considered a negative mechanism of FPS due to modification of edge due to changes in microclimate and increased predation from species outside of the habitat, can have a positive effect (Betts et al, 2019;Fahrig et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Habitat Fragmentation Increases Overall Richness, but Not of Habitat-Dependent Species

2020

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Debate rages as to whether habitat fragmentation leads to the decline of biodiversity once habitat loss is accounted for. Previous studies have defined fragmentation variously, but research needs to address “fragmentation per se,” which excludes confounding effects of habitat loss. Our study controls for habitat area and employs a mechanistic multi-species simulation to explore processes that may lead some species groups to be more or less sensitive to fragmentation per se. Our multi-land-cover, landscape-scale, individual-based model incorporates the movement of generic species, each with different land cover preferences. We investigate how fragmentation per se changes diversity patterns; within (alpha), between (beta) and across (gamma) patches of a focal-land-cover, and if this differs among species groups according to their specialism and dependency on this focal-land-cover. We defined specialism as the increased competitive ability of specialists in suitable habitat and decreased ability in less suitable land covers compared to generalist species. We found fragmentation per se caused an increase in gamma diversity in the focal-land-cover if we considered all species regardless of focal-land-cover preference. However, critically for conservation, the gamma diversity of species for whom the focal land cover is suitable habitat declined under fragmentation per se. An exception to this finding occurred when these species were specialists, who were unaffected by fragmentation per se. In general, focal-land-cover species were under pressure from the influx of other species, with fragmentation per se leading to a loss of alpha diversity not compensated for by increases in beta diversity and, therefore, gamma diversity fell. The specialist species, which were more competitive, were less affected by the influx of species and therefore alpha diversity decreased less with fragmentation per se and beta diversity compensated for this loss, meaning gamma diversity did not decrease. Our findings help to inform the fragmentation per se debate, showing that effects on biodiversity can be negative or positive, depending on species’ competitive abilities and dependency on the fragmented land cover. Such differences in the effect of fragmentation per se would have important consequences for conservation. Focusing conservation efforts on reducing or preventing fragmentation in areas with species vulnerable to fragmentation.

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“…Reactants are any agents that disappear in a reaction, products are any agents that appear in a reaction, whereas catalysts are any agents that remain unchanged but they modify a rate of a reaction. RCP models apply to a broad class of situations, such as models of population ecology [ 5 , 6 , 25 ], metapopulation ecology [ 24 , 26 ], community ecology [ 23 , 27 , 28 ], pathogenesis [ 29 ], evolutionary ecology [ 6 , 30 , 31 ] and movement ecology [ 6 , 32 ].…”

Section: The Mathematical Framework Of Reactant–catalyst–product Modementioning

confidence: 99%

A general mathematical method for predicting spatio-temporal correlations emerging from agent-based models

Ovaskainen

Somervuo

Finkelshtein

2020

J. R. Soc. Interface.

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Agent-based models are used to study complex phenomena in many fields of science. While simulating agent-based models is often straightforward, predicting their behaviour mathematically has remained a key challenge. Recently developed mathematical methods allow the prediction of the emerging spatial patterns for a general class of agent-based models, whereas the prediction of spatio-temporal pattern has been thus far achieved only for special cases. We present a general and mathematically rigorous methodology that allows deriving the spatio-temporal correlation structure for a general class of individual-based models. To do so, we define an auxiliary model, in which each agent type of the primary model expands to three types, called the original, the past and the new agents. In this way, the auxiliary model keeps track of both the initial and current state of the primary model, and hence the spatio-temporal correlations of the primary model can be derived from the spatial correlations of the auxiliary model. We illustrate the agreement between analytical predictions and agent-based simulations using two example models from theoretical ecology. In particular, we show that the methodology is able to correctly predict the dynamical behaviour of a host–parasite model that shows spatially localized oscillations.

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Habitat fragmentation and species diversity in competitive communities

Cited by 101 publications

References 52 publications

WITHDRAWN: Effects of Landscape Change on Floristic Composition and Structure in the Bale Mountains National Park, Southeastern Ethiopia

WITHDRAWN: Effects of Landscape Change on Floristic Composition and Structure in the Bale Mountains National Park, Southeastern Ethiopia

Habitat Fragmentation Increases Overall Richness, but Not of Habitat-Dependent Species

A general mathematical method for predicting spatio-temporal correlations emerging from agent-based models

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