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 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.

Teacher’s Corner: Negative Information and The Three-Parameter Logistic Model

1996 ◽  
Vol 21 (2) ◽  
pp. 179-185 ◽  
Author(s):  
Eric T. Bradlow
Keyword(s):  
Logistic Model ◽  
Sampling Methods ◽  
Latent Trait ◽  
Negative Information ◽  
Binary Response ◽  
Observed Information ◽  
Latent Ability ◽  
Item Properties ◽  
Limiting Case ◽  
The Relationship

The 3-parameter logistic model is commonly used to describe the relationship among an unobserved latent trait (ability), unobserved item properties, and an observed binary outcome. We show that for certain values of the item properties and latent ability, the observed information about ability contained in the binary response is negative. This result has implications for maximization procedures, such as Newton-Raphson; approximate sampling methods, such as the Metropolis-Hastings algorithm; and Bayesian adaptive testing. All of these typically utilize the observed information. This result is contrasted with the fact that observed negative information does not occur in the limiting case with no guessing (2-parameter logistic model). The probability of negative information is expressed by a simple formula. This research extends the work of Samejima (1973) and Yen, Burket, and Sykes (1991).

Spatial Scale and Species Diversity: Building Species–Area Curves from Species Incidence

2005 ◽  
Author(s):  
Jack J. Lennon ◽  
William Edward Kunin
Keyword(s):  
Species Diversity ◽  
Absolute Number ◽  
Simple Graph ◽  
Number Of Species ◽  
Wide Range ◽  
Species Incidence ◽  
Species Area ◽  
Species Area Relationship ◽  
The Relationship ◽  
Reductionist Approach

This chapter is largely focused on the species–area relationship (SAR), although it may not seem so for much of the time. Bear with us; we will get there in the end. Our aim is to provide insights into how the relationship works, and how it is built. This leads us to take a rather reductionist approach, and to break down the SAR into its component parts. We will spend a substantial section of this chapter examining these pieces and their properties. We will then explore the logic by which the parts are reassembled, and will explore how biological and biogeographical properties of a system may affect the SAR. Before attempting this feat, however, we should begin with a brief discussion of the SAR itself, to explain why it is worth making such a fuss over. The SAR is, after all, only a simple graph: a plot of the number of species found in a sample as a function of the area sampled. Ecologists being an argumentative lot, we cannot even all agree on what this plot should look like; Gleason (1922, see also Williams 1964) argued that the absolute number of species should be plotted as a function of the logarithm of area, whereas Arrhenius (1921, see also Preston 1960) suggested that both species and area should be plotted logarithmically. Connor and McCoy (1979) found cases that fit both models, and two others besides (log species by untransformed area, and neither variable transformed). However it’s plotted, the SAR is not even a particularly attractive or elegant graph—at its best (!) it is simply a straight diagonal line within a tight scatter of datapoints on a rectangular plot. Hardly something to set the pulse racing. Yet the SAR is exciting stuff; that simple line encapsulates a great deal of information about the diversity of biological systems across a wide range of scales.

scholarly journals Countryside Species–Area Relationship as a Valid Alternative to the Matrix‐Calibrated Species–Area Model

2014 ◽  
Vol 28 (3) ◽  
pp. 874-876 ◽  
Author(s):  
HENRIQUE MIGUEL PEREIRA ◽  
GUY ZIV ◽  
MURILO MIRANDA
Keyword(s):  
Area Model ◽  
The Matrix ◽  
Species Area ◽  
Species Area Relationship

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.

Patterns of biological diversity

2019 ◽  
pp. 11-37
Author(s):  
Gary G. Mittelbach ◽  
Brian J. McGill
Keyword(s):  
Species Richness ◽  
Species Interactions ◽  
Biological Diversity ◽  
Spatial Scales ◽  
Species Numbers ◽  
Diversity Gradient ◽  
Species Abundances ◽  
Species Area ◽  
Species Area Relationship ◽  
The Relationship

This chapter examines how biodiversity, the variety of life, is distributed across the globe and within local communities. It begins by considering some of the challenges associated with assessing biological diversity at different spatial scales. Then, three of the best-studied patterns in species richness are examined in detail—the species–area relationship, the distribution of species abundances, and the relationship between productivity and species richness. The chapter concludes with a detailed exploration of the most dramatic of Earth’s biodiversity patterns—the latitudinal diversity gradient. The above patterns constitute much of what community ecology seeks to explain about nature. Their study provides a foundation from which to explore mechanisms of species interactions, and to understand the processes that drive variation in species numbers and their distribution.

scholarly journals The strength of the biodiversity–ecosystem function relationship depends on spatial scale

2018 ◽  
Vol 285 (1880) ◽  
pp. 20180038 ◽  
Author(s):  
Patrick L. Thompson ◽  
Forest Isbell ◽  
Michel Loreau ◽  
Mary I. O'Connor ◽  
Andrew Gonzalez
Keyword(s):  
Spatial Variation ◽  
Spatial Scale ◽  
Spatial Scales ◽  
Scale Dependence ◽  
Α Diversity ◽  
Species Area ◽  
Species Area Relationship ◽  
Function Relationship ◽  
New Research ◽  
The Relationship

Our understanding of the relationship between biodiversity and ecosystem functioning (BEF) applies mainly to fine spatial scales. New research is required if we are to extend this knowledge to broader spatial scales that are relevant for conservation decisions. Here, we use simulations to examine conditions that generate scale dependence of the BEF relationship. We study scale by assessing how the BEF relationship (slope and R 2 ) changes when habitat patches are spatially aggregated. We find three ways for the BEF relationship to be scale-dependent: (i) variation among local patches in local (α) diversity, (ii) spatial variation in the local BEF relationship and (iii) incomplete compositional turnover in species composition among patches. The first two cause the slope of the BEF relationship to increase moderately with spatial scale, reflecting nonlinear averaging of spatial variation in diversity or the BEF relationship. The third mechanism results in much stronger scale dependence, with the BEF relationship increasing in the rising portion of the species area relationship, but then decreasing as it saturates. An analysis of data from the Cedar Creek grassland BEF experiment revealed a positive but saturating slope of the relationship with scale. Overall, our findings suggest that the BEF relationship is likely to be scale dependent.

scholarly journals Hubungan Tindakan Pemberantasan Sarang Nyamuk dengan Keberadaan Larva Vektor DBD di Kelurahan Lubuk Buaya

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Ayu Azlina ◽  
Adrial Adrial ◽  
Eliza Anas
Keyword(s):  
Environmental Factor ◽  
Random Sampling ◽  
Endemic Area ◽  
Sampling Methods ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Chi Square ◽  
Cross Sectional ◽  
Death Case ◽  
The Relationship

AbstrakKelurahan Lubuk Buaya merupakan daerah endemik Demam Berdarah Dengue (DBD) dengan korban meninggal terbanyak pada tahun 2012. Penyebaran DBD dipengaruhi oleh faktor lingkungan dan tindakan Pemberantasan Sarang Nyamuk (PSN). Tujuan penelitian ini adalah menentukan hubungan tindakan pemberantasan sarang nyamuk dan keberadaan larva vektor DBD di Kelurahan Lubuk Buaya Kecamatan Koto Tangah Kota Padang. Jenis penelitian adalah analitik observasional dengan rancangan cross sectional. Penelitian dilaksanakan di Kelurahan Lubuk Buaya dengan 110 sampel pada bulan Desember 2014. Sampel diambil dengan metode Multistage Random Sampling. Pengambilan data menggunakan kuesioner dan survei larva terhadap kontainer yang berada di dalam dan di luar rumah responden. Data disajikan dalam bentuk tabel ditribusi dan dianalisis statistik dengan uji chi-square. Hasil penelitian menunjukkan lebih dari separuh responden melakukan tindakan PSN yang baik. Keberadaan larva vektor DBD tergolong tinggi dengan HI 35,45%, CI 13,41%, BI 50% dan Density figure/Df= 5. Terdapat hubungan yang bermakna antara tindakan pemberantasan sarang nyamuk dengan keberadaan larva vektor DBD di kelurahan Lubuk Buaya (p=0,001). Pelaksanaan PSN di Kelurahan Lubuk Buaya secara umum belum terlaksana secara optimal.Kata kunci: PSN, larva, vektor DBD AbstractKelurahan Lubuk Buaya is a Dengue Hemorhagic Fever (DHF) endemic area with the highest death case in 2012. The spreading of DHF influenced by environmental factor and practice of mosquito breading place eradication. The objective of this study was to determine the relationship between mosquito breading place eradication practice and the presence of larvae DHF’s vector. The research was an analitic observational with cross-sectional study design. The research was held in Lubuk Buaya with 110 samples in December 2014. The samples were taken with the Multistage Random Sampling methods. Data’s were collected by using a questionnare and survey of the larvae. Data were presented in distribution table and analyzed statistically with Chi Square method. The result showed more than half of the respondents have a good mosquito breading place eradication practice and the presence of larvae DHF’s vector in lubuk buaya is high with HI 35.45%, CI 13.41%, BI 50%, and density figure 5. There is a relationship between breading place eradication practice and the presence of larvae DHF’s vector (p=0.001). The implementation of breading place eradication practice in Lubuk Buaya isn’t implemented optimally.Keywords: breading place eradication, larvae, dengue hemorhagic fever vektor

scholarly journals The Relationship between Total Income and Groundwater Utilization on Fluviomarine Landform Area in Jakarta

2017 ◽  
Vol 31 (1) ◽  
pp. 69-82
Author(s):  
Cahyadi Setiawan ◽  
S Suratman ◽  
Muh. Aris Marfai
Keyword(s):  
Sea Level ◽  
Water Demand ◽  
Random Sampling ◽  
Sampling Methods ◽  
Survey Methods ◽  
Total Income ◽  
Qualitative Approaches ◽  
Groundwater Samples ◽  
Household Water ◽  
The Relationship

Approximately 40% of Jakarta is below sea level when the tide is in, which is referred to as a fluviomarine landform. This study aims: (a) to analyse the relationship between total income and household water demand, and (b) to analyse the relationship between total income and the proportion of groundwater utilization. It uses quantitative and qualitative analysis survey methods, as well as sampling methods, to represent the population. The population of this research is comprised of households that use groundwater on land units made from two classes of landform, two classes of settlement pattern, and three classes of settlement density. To determine the 30 wells, samples with proportional random sampling of the land units formed with groundwater samples have been taken at a radius of 100m from each well sample of 110 households. Quantitative and qualitative approaches have been used to prove the research aims. The analysis of this study indicates that the total income is proportional to household water demand but that it is inversely proportional to the share of groundwater utilization. The results also show that groundwater is not the only source to fulfil household water demand, and that it is necessary to utilize other sources of water.

Persepsi Dan Partisipasi Pengunjung Terhadap Permasalahan Sampah Laut (Marine Debris) Di Pantai Temberan Kabupaten Bangka Dan Pantai Pasir Padi Pangkalpinang

2020 ◽  
Vol 3 (1) ◽  
pp. 11-20
Author(s):  
Siska Oktavia ◽  
Wahyu Adi ◽  
Aditya Pamungkas
Keyword(s):  
Data Collection ◽  
Random Sampling ◽  
Sampling Technique ◽  
Marine Debris ◽  
Reliability Test ◽  
Validity Test ◽  
Data Collection Technique ◽  
Mixed Approach ◽  
Relationship Of ◽  
The Relationship

This study aims to analyze the value of the density of marine debris, perceptions and participation in Temberan beach and Pasir Padi beach, as well as determine the relationship of perception and participation to the density of marine debris. This research is a type of research that is descriptive with a mixed approach (quantitative and qualitative). The study was conducted at Temberan beach in Bangka Regency and Pasir Pasir Beach Pangkal Pinang in October 2019. The sampling technique used was random sampling and purposive sampling. The data collection technique was carried out using observation technique namely sampling and questionnaire. The validity test uses the Pearson Product Moment formula and the reliability test uses the Cronbach’s Alpha formula. The results showed that the density of debris in the Temberan beach was more dominant at 10.92 pieces/meter2, while at Temberan beach 3 pieces/meter2. The results of perception and participation are different, with the Temberan beach occupying more complex waste problems. The relationship of perception and participation in the density of marine debris have a relationship that affects each other.

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