Climate change effects on multi-taxa pollinator diversity and distribution along the elevation gradient of Mount Olympus, Greece
TL;DR: The authors investigated climate change effects on pollinator distribution and diversity along the altitudinal gradient of Mt. Olympus, a biodiversity hotspot, and concluded that the predicted climate change impact stresses for the need of urgent conservation measures, including the expansion of the protection status over the whole mountain.
About: This article is published in Ecological Indicators.The article was published on 2021-12-01 and is currently open access. It has received 5 citations till now. The article focuses on the topics: Species richness & Climate change.
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TL;DR: Wang et al. as mentioned in this paper investigated the distribution of suitable habitats for the red imported fire ant (Solenopsis invicta Buren) under current and future climate scenarios in mainland China.
6 citations
TL;DR: In this paper , the authors conducted an extensive climate change impact assessment of bee pollinators in the Aegean Islands, Greece, a regional bee hotspot in the Mediterranean, and identified areas in urgent need for conservation prioritization, by undertaking an overlap analysis with the established protected areas network in Greece.
Abstract: Simple Summary In this study, we conducted, for the first time, an extensive climate change impact assessment of bee pollinators in the Aegean Islands, Greece, a regional bee hotspot in the Mediterranean. We located the current biodiversity and future extinction hotspots in the region and identified areas in urgent need for conservation prioritization, by undertaking an overlap analysis with the established protected areas network in Greece. Most bee species occurring in the archipelago are expected to face severe range contractions and there is evidence of an underlying extinction debt in the study area. Our work could serve as the baseline for the integration of a rather neglected, yet extremely economically and ecologically important taxonomic group, the bees, in the systematic conservation planning in the archipelago. Abstract Pollinators’ climate change impact assessments focus mainly on mainland regions. Thus, we are unaware how island species might fare in a rapidly changing world. This is even more pressing in the Mediterranean Basin, a global biodiversity hotspot. In Greece, a regional pollinator hotspot, climate change research is in its infancy and the insect Wallacean shortfall still remains unaddressed. In a species distribution modelling framework, we used the most comprehensive occurrence database for bees in Greece to locate the bee species richness hotspots in the Aegean, and investigated whether these might shift in the future due to climate change and assessed the Natura 2000 protected areas network effectiveness. Range contractions are anticipated for most taxa, becoming more prominent over time. Species richness hotspots are currently located in the NE Aegean and in highly disturbed sites. They will shift both altitudinally and latitudinally in the future. A small proportion of these hotspots are currently included in the Natura 2000 protected areas network and this proportion is projected to decrease in the coming decades. There is likely an extinction debt present in the Aegean bee communities that could result to pollination network collapse. There is a substantial conservation gap in Greece regarding bees and a critical re-assessment of the established Greek protected areas network is needed, focusing on areas identified as bee diversity hotspots over time.
3 citations
TL;DR: In this paper , the authors investigate how climate and land-cover change may alter the distribution of four single mountain endemics and three very rare Peloponnesian endemic taxa of the National Park via a species distribution modelling approach, and estimate the current and future extinction risk of the aforementioned taxa based on the IUCN Criteria A and B, in order to investigate the need for designing an effective plant micro-reserve network and to support decision making on spatial planning efforts and conservation research for a sustainable, integrated management.
Abstract: Chelmos-Vouraikos National Park is a floristic diversity and endemism hotspot in Greece and one of the main areas where Greek endemic taxa, preliminary assessed as critically endangered and threatened under the IUCN Criteria A and B, are mainly concentrated. The climate and land-cover change impacts on rare and endemic species distributions is more prominent in regional biodiversity hotspots. The main aims of the current study were: (a) to investigate how climate and land-cover change may alter the distribution of four single mountain endemics and three very rare Peloponnesian endemic taxa of the National Park via a species distribution modelling approach, and (b) to estimate the current and future extinction risk of the aforementioned taxa based on the IUCN Criteria A and B, in order to investigate the need for designing an effective plant micro-reserve network and to support decision making on spatial planning efforts and conservation research for a sustainable, integrated management. Most of the taxa analyzed are expected to continue to be considered as critically endangered based on both Criteria A and B under all land-cover/land-use scenarios, GCM/RCP and time-period combinations, while two, namely Alchemilla aroanica and Silene conglomeratica, are projected to become extinct in most future climate change scenarios. When land-cover/land-use data were included in the analyses, these negative effects were less pronounced. However, Silene conglomeratica, the rarest mountain endemic found in the study area, is still expected to face substantial range decline. Our results highlight the urgent need for the establishment of micro-reserves for these taxa.
TL;DR: In this paper , the authors studied α- and β-diversity of pollinators, flowering plants, and plant-pollinator interactions along the altitudinal gradient of Mt. Olympus, a legendary mountain and biodiversity hotspot in Central Greece.
Abstract: We studied α- and β-diversity of pollinators, flowering plants, and plant-pollinator interactions along the altitudinal gradient of Mt. Olympus, a legendary mountain and biodiversity hotspot in Central Greece. We explored ten study sites located on the north-eastern slope of the mountain, from 327 to 2,596 m a.s.l. Insect surveys were conducted once a month using hand netting (years 2013, 2014, and 2016), and they were combined with recordings of flowering plant diversity (species richness and flower cover). We then calculated α- and β-diversity of pollinators, plants in flower, and plant-pollinator interactions, and explored their demographic response along the altitudinal gradient. Alpha-diversity of pollinators, plants, and plant-pollinator interactions were altitude-dependent; α-diversity of all pollinators, bees, non-bumblebee bees, bee flies, and butterflies showed linear declines with altitude, whereas those of hoverflies and bumblebees showed unimodal patterns. Beta-diversity and its turnover component of all pollinators, hoverflies, bees, bumblebees, non-bumblebee bees, butterflies, and plants showed linear increases, whereas those of bee flies and of plant-pollinator interactions varied independently from the pairwise altitudinal difference. The high dissimilarity and uniqueness of pollination networks, which is probably a result of the high biodiversity and endemism of Mt. Olympus, is driven by species turnover and the formation of new interactions between new species. Contrasting to the monotonic decline of the remaining groups, the unimodal patterns of hoverfly and bumblebee α-diversity are probably the effect of a higher tolerance of these groups to high-altitude environmental conditions. Our findings highlight that the high turnover of species and of pollination interactions along the altitudinal gradient are the mainstay of hyperdiverse mountains, a fact that conveys important historical, ecological, and conservational implications.
TL;DR: In this paper , a phylogenetic analysis of 89 European and Mediterranean Silene species was conducted to investigate the influence of climate on plant morphology and pollinator communities on the evolution of plant traits.
Abstract: Pollinator selection on floral traits is a well-studied phenomenon, but less is known about the influence of climate on this species interaction. Floral trait evolution could be a result of both adaptation to climate and pollinator-mediated selection. In addition, climate may also determine pollinator communities, leading to an indirect influence of climate on floral traits. In this study, we present evidence of both direct and indirect effects of climate on plant morphology through a phylogenetic comparative analysis of the relationships between climate, pollinators, and morphology in 89 European and Mediterranean Silene species. Climate directly influences vegetative morphology, where both leaf size and internode length were found to be smaller in habitats that are warmer in the driest quarter of the year and that have more precipitation in the coldest quarter of the year. Similarly, flower size was directly influenced by climate, where smaller calyxes were also associated with habitats that are warmer in the driest quarter of the year. These results suggest that reduced leaf and flower size promote water conservation in species that occupy arid climates. Floral traits also evolved in response to pollinators, with elongated calyxes associated with nocturnal pollination, though we also found evidence that climate influences pollinator distribution. Nocturnal pollinators of Silene are found in habitats that have more temperature evenness across seasons than diurnal pollinators. Correspondingly, nocturnally-pollinated Silene are more likely to occur in habitats that have lower daily temperature fluctuation and more temperature evenness across seasons. Altogether these results show that climate can directly influence vegetative and floral morphology, but it can also affect pollinator distribution, which in turn drives floral adaptation. Our study therefore suggests that climate mediates the influence of species interactions on trait evolution by imposing direct selective demands on floral phenotypes and by determining the pollinator community that imposes its own selective demands on flowers.
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University of Leeds1, University of Cambridge2, Royal Society for the Protection of Birds3, Macquarie University4, Durham University5, University of the Witwatersrand6, Conservation International7, Stellenbosch University8, World Conservation Monitoring Centre9, National Autonomous University of Mexico10, University of Kansas11, James Cook University12
TL;DR: Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
Abstract: Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
7,089 citations
TL;DR: It was found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection and the value of GLM in combination with penalised methods and thresholds when omitted variables are considered in the final interpretation.
Abstract: Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the ‘folk lore’-thresholds of correlation coefficients between predictor variables of |r| >0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.
6,199 citations
TL;DR: Thirteen recommendations are made to enable the objective selection of an error assessment technique for ecological presence/absence models and a new approach to estimating prediction error, which is based on the spatial characteristics of the errors, is proposed.
Abstract: Predicting the distribution of endangered species from habitat data is frequently perceived to be a useful technique. Models that predict the presence or absence of a species are normally judged by the number of prediction errors. These may be of two types: false positives and false negatives. Many of the prediction errors can be traced to ecological processes such as unsaturated habitat and species interactions. Consequently, if prediction errors are not placed in an ecological context the results of the model may be misleading. The simplest, and most widely used, measure of prediction accuracy is the number of correctly classified cases. There are other measures of prediction success that may be more appropriate. Strategies for assessing the causes and costs of these errors are discussed. A range of techniques for measuring error in presence/absence models, including some that are seldom used by ecologists (e.g. ROC plots and cost matrices), are described. A new approach to estimating prediction error, which is based on the spatial characteristics of the errors, is proposed. Thirteen recommendations are made to enable the objective selection of an error assessment technique for ecological presence/absence models.
6,044 citations
TL;DR: The nature and extent of reported declines, and the potential drivers of pollinator loss are described, including habitat loss and fragmentation, agrochemicals, pathogens, alien species, climate change and the interactions between them are reviewed.
Abstract: Pollinators are a key component of global biodiversity, providing vital ecosystem services to crops and wild plants. There is clear evidence of recent declines in both wild and domesticated pollinators, and parallel declines in the plants that rely upon them. Here we describe the nature and extent of reported declines, and review the potential drivers of pollinator loss, including habitat loss and fragmentation, agrochemicals, pathogens, alien species, climate change and the interactions between them. Pollinator declines can result in loss of pollination services which have important negative ecological and economic impacts that could significantly affect the maintenance of wild plant diversity, wider ecosystem stability, crop production, food security and human welfare.
4,608 citations
TL;DR: In this article, the authors provide a theoretical explanation for the observed dependence of kappa on prevalence, and introduce an alternative measure of accuracy, the true skill statistic (TSS), which corrects for this dependence while still keeping all the advantages of Kappa.
Abstract: Summary
1In recent years the use of species distribution models by ecologists and conservation managers has increased considerably, along with an awareness of the need to provide accuracy assessment for predictions of such models. The kappa statistic is the most widely used measure for the performance of models generating presence–absence predictions, but several studies have criticized it for being inherently dependent on prevalence, and argued that this dependency introduces statistical artefacts to estimates of predictive accuracy. This criticism has been supported recently by computer simulations showing that kappa responds to the prevalence of the modelled species in a unimodal fashion.
2In this paper we provide a theoretical explanation for the observed dependence of kappa on prevalence, and introduce into ecology an alternative measure of accuracy, the true skill statistic (TSS), which corrects for this dependence while still keeping all the advantages of kappa. We also compare the responses of kappa and TSS to prevalence using empirical data, by modelling distribution patterns of 128 species of woody plant in Israel.
3The theoretical analysis shows that kappa responds in a unimodal fashion to variation in prevalence and that the level of prevalence that maximizes kappa depends on the ratio between sensitivity (the proportion of correctly predicted presences) and specificity (the proportion of correctly predicted absences). In contrast, TSS is independent of prevalence.
4When the two measures of accuracy were compared using empirical data, kappa showed a unimodal response to prevalence, in agreement with the theoretical analysis. TSS showed a decreasing linear response to prevalence, a result we interpret as reflecting true ecological phenomena rather than a statistical artefact. This interpretation is supported by the fact that a similar pattern was found for the area under the ROC curve, a measure known to be independent of prevalence.
5Synthesis and applications. Our results provide theoretical and empirical evidence that kappa, one of the most widely used measures of model performance in ecology, has serious limitations that make it unsuitable for such applications. The alternative we suggest, TSS, compensates for the shortcomings of kappa while keeping all of its advantages. We therefore recommend the TSS as a simple and intuitive measure for the performance of species distribution models when predictions are expressed as presence–absence maps.
3,518 citations