Predictor Of Plant Species Richness Research Articles

Exotic species drive patterns of plant species diversity in 93 restored tallgrass prairies.

A primary goal of restoration ecology is to understand the factors that generate variability in species diversity and composition among restorations. Plant communities may assemble deterministically toward a common community type, or they may assemble stochastically, ending differently because of weather conditions during establishment, soil legacy effects, or exotic species propagule pressure. To test these alternative hypotheses, we sampled plant communities and soil at 93 randomly selected restored prairies distributed throughout Iowa, USA. Five remnant sites were sampled as a reference. We tested our hypotheses using multiple regressions and investigated the strength of direct and indirect effects on species diversity and richness using structural equation models. The prairie restorations were highly variable in their age, size, diversity, soil characteristics, and how they were managed post-seeding. The strongest predictor of plant species richness and diversity was the degree of invasion, as measured by the abundance of exotic species. Restorations planted with species-rich seed mixes had reduced exotic species abundance, which led indirectly to higher species richness of restorations. Sites with higher organic matter and a more linear shape had a direct positive effect on exotic abundance, which in turn decreased diversity. We found little support for deterministic assembly, and diversity did not increase with the age of planting. Our results indicate that restored prairie communities tend to assemble into states of high or low diversity, driven by invasion from exotic plant species. Management of exotic species is essential for maximizing species diversity in temperate grassland restorations.

A global test of the subsidized island biogeography hypothesis

AbstractAimThe decreasing capacity of area to predict species richness on small islands (the small‐island effect; SIE) seems to be one of the few exceptions of the species–area relationship. While most studies have focused on how to detect the SIE, the underlying ecological factors determining this pattern remain largely unexplored. Here, we evaluate one of the few mechanisms proposed to explain the SIE, the subsidized island biogeography hypothesis, which posits that marine productivity around small islands may alter their expected species richness.LocationSeven hundred and ninety islands worldwide, including 420 islands < 1 km2.Time periodPresent.Major taxa studiedAngiosperms.MethodsWe applied iterative partial regression to determine the effects of island area and marine productivity on plant species richness for islands of varying sizes. We also employed geographically weighted regression to account for non‐stationarity in the marine productivity effects. Lastly, we used estimates of ammonia emissions based on nutrient excretion by seabird colonies from a subset of 66 islands to evaluate the effects of marine resources deposition on angiosperm species richness.ResultsWe found no effect of marine productivity on insular species richness, at both regional and global scales. In all models, area emerged as the only predictor of plant species richness. A weak contribution of marine productivity was only detectable in models with a low number of islands, but this effect was independent of island size. Although nutrient deposition significantly contributes to explaining plant diversity, this effect was also independent of island size.Main conclusionsOur study demonstrates that marine productivity has no general effect on plant species richness of small islands worldwide. Although marine‐derived resources may still contribute to species richness variation, this effect does not seem to be restricted to small islands. Overall, our results do not provide support for the subsidized island biogeography hypothesis.

And the winner is …. ! A test of simple predictors of plant species richness in agricultural grasslands

Land-use intensification, nutrient enrichment and enhanced productivity levels are major drivers of the current biodiversity loss in agricultural grasslands. Although these drivers are potentially strongly causally linked, their potential to explain changes in biodiversity can enhance each other and often varies over time. Here, we explored the explanatory power of different abiotic drivers and the Ellenberg indicator value for nutrient availability to predict plant species richness using data of 150 grassland plots over seven years. The approach also allows to assess the temporal robustness of many of these drivers. Our results revealed the Ellenberg indicator value for nutrients to be the best and temporally most consistent predictor of plant species richness. Unweighted mean Ellenberg values showed an even stronger negative relationship to plant species richness than abundance weighted mean values. Direct measurements of soil and plant biomass nutrients, aboveground biomass and land-use intensity predicted plant species richness less well and showed considerable temporal variability in the respective association. In case of biomass nitrogen and phosphorus concentrations, current year weather conditions are assumed to strongly affect the strength of the relationship by shifting the phenological development considerable among sampling years. Although mainly driven by aboveground biomass, a combination of biomass nutrient concentrations with productivity, i.e. the nutrient stock in the aboveground biomass, turned out to better predict plant species richness than its single components and inter-annual variability in the relationship was markedly lower. Especially for aboveground biomass and the intensity of land-use, long-term mean values significantly improved the explanatory power compared to single year measurements. We conclude that studies explaining biodiversity changes should carefully take into account temporal variability in the drivers under study before judging the strength of a particular mechanistic relationship.

Beyond arctic and alpine: the influence of winter climate on temperate ecosystems.

Winter climate is expected to change under future climate scenarios, yet the majority of winter ecology research is focused in cold-climate ecosystems. In many temperate systems, it is unclear how winter climate relates to biotic responses during the growing season. The objective of this study was to examine how winter weather relates to plant and animal communities in a variety of terrestrial ecosystems ranging from warm deserts to alpine tundra. Specifically, we examined the association between winter weather and plant phenology, plant species richness, consumer abundance, and consumer richness in 11 terrestrial ecosystems associated with the U.S. Long-Term Ecological Research (LTER) Network. To varying degrees, winter precipitation and temperature were correlated with all biotic response variables. Bud break was tightly aligned with end of winter temperatures. For half the sites, winter weather was a better predictor of plant species richness than growing season weather. Warmer winters were correlated with lower consumer abundances in both temperate and alpine systems. Our findings suggest winter weather may have a strong influence on biotic activity during the growing season and should be considered in future studies investigating the effects of climate change on both alpine and temperate systems.

A Multi-scale Spatial Analysis of Native and Exotic Plant Species Richness Within a Mixed-Disturbance Oak Savanna Landscape

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio’s Oak Openings region. Multiple regression models explained 37–77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.

Relationship between landscape heterogeneity and plant species richness on the Mexican Pacific coast

The present study aims to use landscape heterogeneity as a predictor of plant species richness in a tropical dry landscape area in the coast of Michoacán, Mexico. To understand the relationship between species richness and landscape, a three-step approach was followed: first, landscape spatial heterogeneity was measured by classifying landscape types according to their attributes (i.e., environmental, soil and topographic variables). Second, several diversity standard indices were used to explore biological diversity and to select the best one explaining the relationship between landscape heterogeneity and plant species richness, for this study area. Third, from the obtained results it was possible to calculate biodiversity values on the basis of landscape heterogeneity. The results indicate that it is possible to predict more than 61% of species richness through an indicator of landscape heterogeneity (H′; Shannon–Weaver diversity index). This procedure may be useful in terms of land use, conservation, and management of protected areas, mainly in areas with high biodiversity but with limited biological data, since it allows to obtain an approximation of the spatial distribution of species richness, even with scarce biological information.

Comment on “Productivity Is a Poor Predictor of Plant Species Richness”

Adler et al. (Reports, 23 September 2011, p. 1750) analyzed the standardized sampling data from 48 herbaceous-dominated plant communities and concluded that "Productivity is a poor predictor of plant species richness" at fine-scale. However, their method was biased toward site-number-dominated plant communities. They also failed to provide enough data for regional analysis and detailed information for within-site analysis.

Response to Comments on “Productivity Is a Poor Predictor of Plant Species Richness”

Pan et al . claim that our results actually support a strong linear positive relationship between productivity and richness, whereas Fridley et al . contend that the data support a strong humped relationship. These responses illustrate how preoccupation with bivariate patterns distracts from a deeper understanding of the multivariate mechanisms that control these important ecosystem properties.

Comment on “Productivity Is a Poor Predictor of Plant Species Richness”

Adler et al. (Reports, 23 September 2011, p. 1750) reported "weak and variable" relationships between productivity and species richness and dispute the "humped-back" model (HBM) of plant diversity. We show that their analysis lacks sufficient high-productivity sites, ignores litter, and excludes anthropogenic sites. If corrected, the data set of Adler et al. would apparently yield strong HBM support.

Multi-scale environmental heterogeneity as a predictor of plant species richness

Ecological theory predicts a positive influence of local-, landscape-, and regional-scale spatial environmental heterogeneity on local species richness. Therefore, knowing how heterogeneity measured at a variety of scales relates to local species richness has important implications for conservation of biological diversity. We took a statistical modeling approach to determine which metrics of heterogene- ity measured at which scales were useful predictors of local species richness, and whether the heterogeneity- local richness relationship was always positive. Local plant species richness data came from 400-m 2 vegetation plots in North and South Carolina, USA. At each of four scales from within plots to across regions, we used either GIS or field data to calculate measures of heterogeneity from abiotic environmen- tal variables, vegetation productivity data, and land cover classifications. Among all predictors at all scales, we found that no measure of heterogeneity was a better predictor of local richness than mean pH within plots. However, at scales larger than within plots, measures of heterogeneity were correlated most strongly with local richness, and each of the three classes of variables we used had a distinct scale at which it performed better than the others. These results highlight the fact that ecological processes occurring across multiple scales influence local species richness differently. In addition, relationships between heterogeneity and richness were usually, though not always, positive, underscoring the impor- tance of processes that occur at a variety of scales to local biodiversity conservation and management.

The effects of adjacent land use on wetland species richness and community composition

Wetlands provide important ecosystem functions and values, such as wildlife habitat, water filtration and flood protection. Wetland plant communities play a fundamental role in maintaining these functions but are thought to be increasingly threatened by human modifications of the landscape, such as deforestation and road construction. Here, we examine the quantitative relationships between two dependent variables (plant species richness, community composition) and a set of independent variables describing land use (e.g., forest cover, road density, and building density). As independent variables, we further include wetland characteristics that may be related to landuse practices (e.g., area and nutrient status). Wetland size is the most important predictor of both total plant species richness and the species richness within most functional groups. In addition, landscape properties, such as forest cover, presence of streams and nutrient status of water and sediment are significant predictors of plant species richness. Adjacent land use 250–300 m from the wetland affects plant diversity. Differences in the land-use-diversity relationship among different plant functional groups suggest that adjacent land use affects wetland plant communities in two important ways. First, it alters the abundance and distribution of propagules in adjoining habitats. Second, it alters the number of dispersal routes. Our results suggest that current management practices are inadequate and that regulation of adjacent land use is a critical component of wetland conservation.

우리나라 無人島嶼의 地理的 還境과 植物의 分布 pattern 사이의 相關性 分析

본 연구는 환경부의 '전국 무인도서 자연환경조사 보고서(1999년∼2001년)'에서 발췌한 261개의 무인 도서를 대상으로 섬의 지리적 환경과 섬에 분포하는 관속식물의 종수 및 분포사이의 상관성을 구명하고자 수행하였다. 261개 도서의 평균 면적은 75,000㎡이며, 면적의 분포범위는 최소 1,l00㎡에서 최대 961,200㎡였다. 육지와의 최단거리 평균은 14.9km(150m∼51.4km)이었다. 261개 도서에서 관찰된 전체 종수는 30과 1,109 종으로, 각 도서당 관찰된 종수의 평균은 98.7종이었다. 자생식물은 1,003종(90.4%)이었으며, 귀화식물은 106종(9.6%)로 조사되었다. 그리고 조사된 전체 종수 중에서 국화과가 114종으로 가장 많았으며, 벼과 (90종), 콩과(54종), 장미과(53종) 순으로 나타났다. 261개 섬은 출현한 식물종의 구성에 근거하여 다차원척도분석을 실시한 결과 '남해그룹(130개 섬)'과 '서해그룹(131개 섬)'의 두 지역으로 뚜렷이 구분할 수 있었다. 서해그룹에 속하는 섬들은 남해그룹의 섬들에 비해 면적이 더 넓었으나(서해그룹 평균=93,000㎡, 남해그룹 평균=57,000㎡), 도서당 출현 종수는 적었다(서해그룹 평균=192, 남해그룹 평균=233). 또한 서해그룹보다는 남해그룹에만 한정적으로 분포하는 종들이 두 그룹을 구분하는데 더욱 큰 영향을 미치는 것으로 나타나서, 위도에 따른 식물 분포를 반영하고 있다. 출현하는 식물 종수에 가장 큰 영향을 미치는 인자는 섬의 면적이었으며, 육지와의 최단거리와 인간의 간섭 인자 순으로 나타났다. 식물종수에 미치는 환경인자들은 서해그룹과 남해그룹에서 각기 다르게 나타났으며, 남해그룹의 섬들이 서해그룹의 섬들에 비하여 육지와의 거리가 가깝고 단위면적당 출현 종수가 많았기 때문에 보다 다양한 환경인자들에 의해 민감하게 영향을 받는 것으로 생각된다. 따라서 이상의 결과들은 무인도서 생태계 보존을 위해 중요하게 활용될 것으로 기대되며, 앞으로 인간간섭과 귀화식물종이 무인도서 생태계에 미치는 영향에 대한 연구가 계속적으로 이루어질 것이다. Correlations among the island area, distance to mainland, latitude, longitude, human impacts, diversity and composition of vascular plants were investigated by analyzing data on 261 islands(10.3% of total number of islands in Korea) selected from the annual reports for 'the natural evironment survey of the uninhabited islands in Korea' published by 'Ministry of Environment' during three years from 1999. The area of surveyed 261 islands ranged 1,100 to 961,000㎡(average of 75,000㎡), and the distance to mainland ranged 0.15 to 51.5km (average of 14.9km). Total number of plant species recorded in those islands was 1,109 species throughout 30 families, and mean mumber of plant species of each island was 98.7 species. Native species were 1,003 species (90.4%), and exotic species were 106 species(9.6%). The families with the largest number of species was the Compositae with 114 species, and followed in the order of Gramineae(90), Leguminosae(54), and Rosaceae(53). The result of multi-dimensional scaling analysis based on the plant species composition showed that 261 islands were distinctly divided into two groups, western sea group(131 islands) and southern sea group(130 islands). The islands of western sea group(average area of 93,000㎡) had greatly larger area than them of southern sea group(average area of 57,000㎡), but the average number of species (average species of 192) per island were less than in southern sea group (average species of 233). And, the partitioning into two groups was responsible for the species restricted to southern than to western sea group. Therefore, this results suggest that the distribution pattern and the composition of plant species could be also affected by the latitude of the island. When the species-area model was applied to total island and plant species, these results indicate that the island area was the most significant predictor of plant species diversity, and the distance to mainland and the human impacts were also shown to be significant predictors of plant species richness. But when applied to both groups of islands by the stepwise selection method, the result showed that islands of southern sea group were greatly affected by the factors such as human impacts, distance to mainland and longitude than western sea group. For the purpose of conservation of natural ecosystem on the uninhabited islands in Korea, we will also examine how the human impacts and the invasion of exotic plant species will disturb the native species diversity.

Determinants of plant species richness on small Bahamian islands

AimI investigated the determinants of plant species richness in two archipelagos, comparing the predictive power of different explanatory variables. I evaluated both conventional variables and alternative variables not commonly used in such analyses. I also investigated the effect of island location in relation to neighbouring landmasses on plant species richness and the predictive ability of regression models.LocationArchipelagos of small islands in the central Exumas and near the north‐east coast of Andros, Bahamas.MethodsI surveyed plant species richness and obtained measures of seven predictor variables: total island area, the ratio of perimeter to total area, vegetated area, the ratio of vegetated area to total area, distance to the nearest large island, elevation and protection from surrounding islands. All seven predictor variables were evaluated as determinants of plant species richness in simple and stepwise multiple linear regressions. Analyses were conducted for each archipelago overall, and then separately for three categories of islands in the Exumas. Total area, elevation, and distance were evaluated as predictors of vegetation incidence in simple and stepwise multiple logistic regressions for both archipelagos.ResultsSome expression of insular area was always the best single predictor of plant species richness in the linear regressions. Total area was a relatively poor predictor compared with other expressions of insular area. Distance, elevation, and protection explained relatively little of the overall variation in plant species number, although all variables were selected as significant in some models. A greater amount of variation in plant species richness was explained by the linear regression models in the Exumas (69.0%) compared with Andros (60.9%). Different variables were entered into the models for the three categories of islands in the Exumas, and adjusted coefficients of multiple determination ranged from 68.9% to 85.7%. In the logistic regressions, the model including total area and distance yielded almost 90% correct classification of vegetation incidence in the Exumas; no significant variables were selected for Andros. A group of exposed, outer islands supported many fewer species than more sheltered islands, on the basis of total island area or elevation.Main conclusionsThe three variables commonly used in studies of determinants of insular species richness – total island area, distance, and elevation – were relatively poor predictors in most analyses. Alternative expressions of insular area – indicative of disturbance or shape in combination with area – were usually better predictors than total area and may more realistically reflect habitable area. Alternative predictors explained similar amounts of variation in plant species richness compared with commonly used predictors, and combinations of all variables into a single stepwise model resulted in increased predictive power. The predictive power of the models tended to be higher for groups of islands that were more sheltered by neighbouring islands. Exposed islands, although separated by relatively small distances from nearby protected islands, may be impacted by storms much more severely and possess many fewer species. The location of small islands relative to large landmasses, as well as their geological histories, should be taken into account in such analyses.

Forest plant species richness in small, fragmented mixed deciduous forest patches: the role of area, time and dispersal limitation

AimThe research aimed to investigate how plant species richness of small, fragmented forest patches changes over time. Also interactions between time and area were studied in relation to species richness. Finally, the relative importance of plant dispersal limitation on the process of species accumulation was examined by investigating how species were distributed within a regional landscape.LocationMixed deciduous forest patches in central Belgium.MethodsThe land use history of a region of 80 km2 was reconstructed using nine historical maps dating from 1775 to 1991. Within a central area of 42 km2, 241 forest patches were surveyed for presence/absence of 203 species predominantly occurring in forests. Aggregation of species within this region was estimated using a Monte Carlo simulation. Spatial and temporal patterns of species richness were investigated by both regression and analysis of variance (ANOVA).ResultsFifty‐one of 103 species showed significant spatial aggregation patterns, suggesting severe dispersal limitation. Species richness significantly increased with age. However, the effects of time on species richness could not be separated from area and area and time clearly interacted. Slopes of regression equations for species number on area and patch age were shown to be significantly interrelated.Main conclusionsArea and time cannot be treated independently as predictors of plant species richness. Dispersal proved to be important in structuring local forest plant community composition, contrary to most other studies that have investigated local forest plant community structure. The processes of forest succession and species accumulation are controlled by both local and regional processes. More studies focusing on the regional factors determining local community composition are needed in order to fully understand the process of forest plant community assembly.

Distinguishing the Effects of Area and Habitat Type on Island Plant Species Richness by Separating Floristic Elements and Substrate Types and Controlling for Island Isolation

An archipelago of sixty-one small islands on bare hypersaline mudflats in tropical Australia can be classified according to substrate composition into twenty-three shell, nineteen silt and nineteen mixed shell-silt islands. Their overall flora can be divided into three floristic elements characteristic of different source areas with different substrate types. Thirty-four of the islands are equidistant from source areas, providing a control on the effects of island isolation. The relative effects of area and habitat type on species richness were distinguished by examining species-area relations for different substrate sets and floristic elements independently as well as jointly. For this particular archipelago, island area is the primary determinant of total species richness. As expected, island isolation has negligible effect. Island elevation was found to be a better predictor of plant species richness than substrate composition, probably through its effect on the soil salinity profile. The relation of species richness to island area and elevation differs substantially between the different floristic elements. Overall, the approach appears valuable and worth further testing.