Diversity and Distributions
1366-9516
1472-4642
Anh Quốc
Cơ quản chủ quản: Wiley-Blackwell Publishing Ltd , WILEY
Lĩnh vực:
Ecology, Evolution, Behavior and Systematics
Phân tích ảnh hưởng
Thông tin về tạp chí
Diversity and Distributions is a journal of conservation biogeography. We publish papers that deal with the application of biogeographical principles, theories, and analyses to problems concerning the conservation of biodiversity. Appropriate topics include innovative applications or methods of species distribution modelling; the application of island biogeographic principles to conservation; developing paradigms, models and frameworks for conservation planning and risk assessment; or identifying the agents of global change, including how climate change, land use change and invasive species affect the abundance, distribution, and range boundaries of native species. Papers must meet four criteria to be considered for publication: (1) They must have a strong biogeographic focus with clear conservation implications, or a strong conservation focus on biogeographic patterns or principles, (2) submissions must test clear hypotheses or predictions arising from theory, or derive novel insights from biogeographic patterns and biodiversity trends, (3) they must be presented clearly and concisely, and (4) their results must have clear and important implications for our understanding of biogeography and must be of potential broad interest of the readership.
Các bài báo tiêu biểu
A parametric diversity measure combining the relative abundances and taxonomic distinctiveness of species ABSTRACT Most ecological diversity indices summarize the information about the relative abundances of species without reflecting taxonomic differences between species. Nevertheless, in environmental conservation practice, data on species abundances are mostly irrelevant and generally unknown. In such cases, to summarize the conservation value of a given site, so‐called ‘taxonomic diversity’ measures can be used. Such measures are based on taxonomic relations among species and ignore species relative abundances. In this paper, bridging the gap between traditional biodiversity measures and taxonomic diversity measures, I introduce a parametric diversity index that combines species relative abundances with their taxonomic distinctiveness. Due to the parametric nature of the proposed index, the contribution of rare and abundant species to each diversity measure is explicit.
Tập 10 Số 2 - Trang 143-146 - 2004
BiolFlor — a new plant‐trait database as a tool for plant invasion ecology
Tập 10 Số 5-6 - Trang 363-365 - 2004
Invasive plants and their ecological strategies: prediction and explanation of woody plant invasion in New England Abstract Effective management of introduced species requires the early identification of species that pose a significant threat of becoming invasive. To better understand the invasive ecology of species in New England, USA, we compiled a character data set with which to compare non‐native species that are known invaders to non‐native species that are not currently known to be invasive. In contrast to previous biological trait‐based models, we employed a Bayesian hierarchical analysis to identify sets of plant traits associated with invasiveness for each of three growth forms (vines, shrubs, and trees). The resulting models identify a suite of ‘invasive traits’ highlighting the ecology associated with invasiveness for each of three growth forms. The most effective predictors of invasiveness that emerged from our model were ‘invasive elsewhere’, ‘fast growth rate’, ‘native latitudinal range’, and ‘growth form’. The contrast among growth forms was pronounced. For example, ‘wind dispersal’ was positively correlated with invasiveness in trees, but negatively correlated in shrubs and vines. The predictive model was able to correctly classify invasive plants 67% of the time (22/33), and non‐invasive plants 95% of the time (204/215). A number of potential future invasive species in New England that deserve management consideration were identified.
Tập 13 Số 5 - Trang 633-644 - 2007
Interactions between global and local stressors of ecosystems determine management effectiveness in cumulative impact mapping Abstract Aim Cumulative impact maps are used to identify the spatial distribution of multiple human impacts to species and ecosystems. Impacts can be caused by local stressors which can be managed, such as eutrophication, and by global stressors that cannot be managed, such as climate change. Cumulative impact maps typically assume that there are no interactive effects between stressors on biodiversity. However, the benefits of managing the ecosystem are affected by interactions between stressors. Our aim was to determine whether the assumption of no interactions in impact maps leads to incorrect identification of sites for management. Location General, Australasia. Methods We used the additive effects model to incorporate the effects of interactions into an interactive impact map. Seagrass meadows in A ustralasia threatened by a local stressor, nutrient inputs, and a global stressor, warming, were used as a case study. The reduction in the impact index was quantified for reductions in the nutrient stressor. We examined the outcomes for three scenarios: no interactions, antagonistic interactions or synergistic interactions. Results Cumulative impact maps imply that reducing a local stressor will give equivalent reductions in the impact index everywhere, regardless of spatial variability in a global stressor. We show that reductions in the impact index were greatest in refuges from warming if there was an antagonistic interaction between stressors, and greatest in areas of high warming stress if there was a synergistic interaction. Reducing the nutrient stressor in refuges from warming always reduced the impact index, regardless of the interaction. Main conclusions Interactions between local and global stressors should be considered when using cumulative impact maps to identify sites where management of a local stressor will provide the greatest impact reduction. If the interaction type is unknown, impact maps can be used to identify refuges from global stressors, as sites for management.
Tập 20 Số 5 - Trang 538-546 - 2014
Recreational boating: a large unregulated vector transporting marine invasive species
Tập 17 Số 6 - Trang 1161-1172 - 2011
The diversity and distribution of lianas in the Afromontane rain forests of Ethiopia ABSTRACT The diversity and distribution of lianas were studied in five Afromontane rain forests of Ethiopia. Quadrats of 20 × 20 m were laid down along transects in the Bonga, Berhane‐Kontir, Harenna, Yayu and Maji forests. In all forests, 30,917 liana individuals belonging to 123 species in 87 genera and 40 plant families were recorded. The most species‐rich families were Asclepiadaceae (14), Fabaceae (9), Annonaceae (7) and Cucurbitaceae (7). The top 10 dominant families represented 56% of the total number of species. Over 400 other plant species representing different life forms were recorded growing together with lianas. The lianas accounted for over 30% of the total woody plant diversity and over 20% of the total floral diversity in the study areas. The analysis of floristic composition of the forests indicates that the Berhane‐Kontir Forest had the highest Fisher's diversity index α, and Yayu the lowest. Generally, there were low similarities between the forests in terms of species composition. Although lianas were abundant in almost all forests, there was a considerable variation among the forests in terms of density and spatial distribution. The major dispersal modes of lianas were anemochory (30%), mammaliochory (30%), ornithochory and autochory, and the four mechanisms of climbing of lianas were twining (54%), hooking (24%), rooting and use of tendrils. Altitude and human disturbance were found to be important factors affecting liana distribution. The need for sustainable management and use of lianas in the Afromontane rain forests is emphasized.
Tập 11 Số 5 - Trang 443-452 - 2005
Alpha diversity of lianas in a tropical evergreen forest in the Anamalais, Western Ghats, India Abstract. Species richness, abundance, size‐class distribution, climbing mode and spatial patterns of lianas were investigated in a 30‐ha permanent plot of tropical evergreen forest at Varagalaiar in the Anamalais, Western Ghats, India. Each hectare was subdivided into 10 m × 10 m quadrats, in which all lianas ≥ 1 cm d.b.h. were measured, tagged and identified. The total liana density was 11, 200 individuals (373 ha–1) and species richness was 75 species, representing 66 genera and 37 families. The richness estimators employed for species and family accumulation curves after 100 times randomization of sample order, have stabilized the curves at 16th and 15th hectares, respectively. A greater proportion of lianas was twiners (55% of species and 44.4% of density) and root climbers (5% of species and 14% of density), and a few were tendril climbers, reflecting the late successional stage of the forest. In the size‐class distribution, 82% of abundance and 97% of species richness fell within 1–3 cm diameter threshold. The dominance of succulent diaspore type signifies the faunal dependence of lianas on vertebrate frugivores for dispersal. The diversity, population density and family composition of lianas of our site is compared with those of other tropical forests. The need for biomonitoring of this synusia in the permanent plot for forest functioning is emphasized.
Tập 6 Số 1 - Trang 1-14 - 2000
The importance of correcting for sampling bias in MaxEnt species distribution models Abstract Aim Advancement in ecological methods predicting species distributions is a crucial precondition for deriving sound management actions. Maximum entropy (MaxEnt) models are a popular tool to predict species distributions, as they are considered able to cope well with sparse, irregularly sampled data and minor location errors. Although a fundamental assumption of MaxEnt is that the entire area of interest has been systematically sampled, in practice, MaxEnt models are usually built from occurrence records that are spatially biased towards better‐surveyed areas. Two common, yet not compared, strategies to cope with uneven sampling effort are spatial filtering of occurrence data and background manipulation using environmental data with the same spatial bias as occurrence data. We tested these strategies using simulated data and a recently collated dataset on Malay civet V iverra tangalunga Location Borneo, Southeast Asia. Methods We collated 504 occurrence records of Malay civets from Borneo of which 291 records were from 2001 to 2011 and used them in the MaxEnt analysis (baseline scenario) together with 25 environmental input variables. We simulated datasets for two virtual species (similar to a range‐restricted highland and a lowland species) using the same number of records for model building. As occurrence records were biased towards north‐eastern Borneo, we investigated the efficacy of spatial filtering versus background manipulation to reduce overprediction or underprediction in specific areas. Results Spatial filtering minimized omission errors (false negatives) and commission errors (false positives). We recommend that when sample size is insufficient to allow spatial filtering, manipulation of the background dataset is preferable to not correcting for sampling bias, although predictions were comparatively weak and commission errors increased. Main Conclusions We conclude that a substantial improvement in the quality of model predictions can be achieved if uneven sampling effort is taken into account, thereby improving the efficacy of species conservation planning.
Tập 19 Số 11 - Trang 1366-1379 - 2013
Unstructured citizen science data fail to detect long‐term population declines of common birds in Denmark Abstract Aim Long‐term monitoring of biodiversity is necessary to identify population declines and to develop conservation management. Because long‐term monitoring is labour‐intensive, resources to implement robust monitoring programmes are lacking in many countries. The increasing availability of citizen science data in online public databases can potentially fill gaps in structured monitoring programmes, but only if trends estimated from unstructured citizen science data match those estimated from structured monitoring programmes. We therefore aimed to assess the correlation between trends estimated from structured and unstructured data. Location Denmark. Methods We compared population trends for 103 bird species estimated over 28 years from a structured monitoring programme and from unstructured citizen science data to assess whether trends estimated from the two data sources were correlated. Results Trends estimated from the two data sources were generally positively correlated, but less than half the population declines identified from the structured monitoring data were recovered from the unstructured citizen science data. The mismatch persisted when we reduced the structured monitoring data from count data to occurrence data to mimic the information content of unstructured citizen science data and when we filtered the unstructured data to reduce the number of incomplete lists reported. Mismatching trends were especially prevalent for the most common species. Worryingly, more than half the species showing significant declines in the structured monitoring showed significant positive trends in the citizen science data. Main conclusions We caution that unstructured citizen science databases cannot replace structured monitoring data because the former are less sensitive to population changes. Thus, unstructured data may not fulfil one of the most critical functions of structured monitoring programmes, namely to act as an early warning system that detects population declines.
Tập 22 Số 10 - Trang 1024-1035 - 2016
Correcting for bias in distribution modelling for rare species using citizen science data Abstract Aim To improve the accuracy of inferences on habitat associations and distribution patterns of rare species by combining machine‐learning, spatial filtering and resampling to address class imbalance and spatial bias of large volumes of citizen science data. Innovation Modelling rare species’ distributions is a pressing challenge for conservation and applied research. Often, a large number of surveys are required before enough detections occur to model distributions of rare species accurately, resulting in a data set with a high proportion of non‐detections (i.e. class imbalance). Citizen science data can provide a cost‐effective source of surveys but likely suffer from class imbalance. Citizen science data also suffer from spatial bias, likely from preferential sampling. To correct for class imbalance and spatial bias, we used spatial filtering to under‐sample the majority class (non‐detection) while maintaining all of the limited information from the minority class (detection). We investigated the use of spatial under‐sampling with randomForest models and compared it to common approaches used for imbalanced data, the synthetic minority oversampling technique (SMOTE ), weighted random forest and balanced random forest models. Model accuracy was assessed using kappa, Brier score and AUC . We demonstrate the method by evaluating habitat associations and seasonal distribution patterns using citizen science data for a rare species, the tricoloured blackbird (Agelaius tricolor ). Main Conclusions Spatial under‐sampling increased the accuracy of each model and outperformed the approach typically used to direct under‐sampling in the SMOTE algorithm. Our approach is the first to characterize winter distribution and movement of tricoloured blackbirds. Our results show that tricoloured blackbirds are positively associated with grassland, pasture and wetland habitats, and negatively associated with high elevations or evergreen forests during both winter and breeding seasons. The seasonal differences in distribution indicate that individuals move to the coast during the winter, as suggested by historical accounts.
Tập 24 Số 4 - Trang 460-472 - 2018