Climate and host plant availability impact the future distribution of the bean leaf beetle (Cerotoma trifurcata)

The bean leaf beetle, Cerotoma trifurcata, has become a major pest of soybean throughout its North American range. With a changing climate, there is the potential for this pest to further expand its distribution and become an increasingly severe pest in certain regions. To examine this possibility, we developed bioclimatic envelope models for both the bean leaf beetle, and its most important agronomic host plant, soybean (Glycine max). These two models were combined to examine the potential future pest status of the beetle using climate change projections from multiple general circulation models (GCMs) and climate change scenarios. Despite the broad tolerances of soybean, incorporation of host plant availability substantially decreased the suitable and favourable areas for the bean leaf beetle as compared to an evaluation based solely on the climate envelope of the beetle, demonstrating the importance of incorporating biotic interactions in these predictions. The use of multiple GCM–scenario combinations also revealed differences in predictions depending on the choice of GCM, with scenario choice having less of an impact. While the Norwegian model predicted little northward expansion of the beetle from its current northern range limit of southern Ontario and overall decreases in suitable and favourable areas over time, the Canadian and Russian models predict that much of Ontario and Quebec will become suitable for the beetle in the future, as well as Manitoba under the Russian model. The Russian model also predicts expansion of the suitable and favourable areas for the beetle over time. Two predictions that do not depend on our choice of GCM include a decrease in suitability of the Mississippi Delta region and continued favourability of the southeastern United States.     

Projected shifts in fish species dominance in Wisconsin lakes under climate change

Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake‐specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake‐specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid‐century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.     

Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling

Modeling the distributions of species, especially of invasive species in non‐native ranges, involves multiple challenges. Here, we developed some novel approaches to species distribution modeling aimed at reducing the influences of such challenges and improving the realism of projections. We estimated species–environment relationships for Parthenium hysterophorus L. (Asteraceae) with four modeling methods run with multiple scenarios of (i) sources of occurrences and geographically isolated background ranges for absences, (ii) approaches to drawing background (absence) points, and (iii) alternate sets of predictor variables. We further tested various quantitative metrics of model evaluation against biological insight. Model projections were very sensitive to the choice of training dataset. Model accuracy was much improved using a global dataset for model training, rather than restricting data input to the species’ native range. AUC score was a poor metric for model evaluation and, if used alone, was not a useful criterion for assessing model performance. Projections away from the sampled space (i.e., into areas of potential future invasion) were very different depending on the modeling methods used, raising questions about the reliability of ensemble projections. Generalized linear models gave very unrealistic projections far away from the training region. Models that efficiently fit the dominant pattern, but exclude highly local patterns in the dataset and capture interactions as they appear in data (e.g., boosted regression trees), improved generalization of the models. Biological knowledge of the species and its distribution was important in refining choices about the best set of projections. A post hoc test conducted on a new Parthenium dataset from Nepal validated excellent predictive performance of our ‘best’ model. We showed that vast stretches of currently uninvaded geographic areas on multiple continents harbor highly suitable habitats for parthenium. However, discrepancies between model predictions and parthenium invasion in Australia indicate successful management for this globally significant weed.     

Estimating seed dispersal distance: A comparison of methods using animal movement and plant genetic data on two primate‐dispersed Neotropical plant species

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Modeling the distribution of a wide‐ranging invasive species using the sampling efforts of expert and citizen scientists

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基于MaxEnt模拟人类活动与环境因子对青藏高原特有植物祁连獐牙菜潜在分布的影响

以青藏高原特有植物祁连獐牙菜(Swertia przewalskii Pissjauk.)为材料,基于该物种18个种群分布点及8个生物气候变量、海拔变量以及人类活动强度变量,运用最大熵模型(Max Ent)和ArcGIS技术分别构建当前气候情景下及人类活动影响下祁连獐牙菜的适宜生境预测模型,研究人类活动及自然环境变量对祁连獐牙菜空间分布的影响。结果显示,人类活动影响下的训练集和测试集的AUC值均小于无人类活动干扰的AUC值,人类活动与祁连獐牙菜分布呈负相关。限制祁连獐牙菜分布的主要变量为海拔、等温性、人类活动足迹指数及平均温度日较差。当前气候情景下祁连獐牙菜的最适宜生境占祁连山国家公园青海片区总面积的36.6%,有利于该物种的保护和恢复,而位于门源县和祁连县保护区内一般控制区的潜在生境受到人为干扰的可能性较大,应加强关注和保护。     

Integrating mechanistic and empirical model projections to assess climate impacts on tree species distributions in northwestern North America

Empirical and mechanistic models have both been used to assess the potential impacts of climate change on species distributions, and each modeling approach has its strengths and weaknesses. Here, we demonstrate an approach to projecting climate‐driven changes in species distributions that draws on both empirical and mechanistic models. We combined projections from a dynamic global vegetation model (DGVM) that simulates the distributions of biomes based on basic plant functional types with projections from empirical climatic niche models for six tree species in northwestern North America. These integrated model outputs incorporate important biological processes, such as competition, physiological responses of plants to changes in atmospheric CO₂ concentrations, and fire, as well as what are likely to be species‐specific climatic constraints. We compared the integrated projections to projections from the empirical climatic niche models alone. Overall, our integrated model outputs projected a greater climate‐driven loss of potentially suitable environmental space than did the empirical climatic niche model outputs alone for the majority of modeled species. Our results also show that refining species distributions with DGVM outputs had large effects on the geographic locations of suitable habitat. We demonstrate one approach to integrating the outputs of mechanistic and empirical niche models to produce bioclimatic projections. But perhaps more importantly, our study reveals the potential for empirical climatic niche models to over‐predict suitable environmental space under future climatic conditions.     

The influence of pre‐settlement and early post‐settlement processes on the adult distribution and relative dominance of two invasive mussel species

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Material affects attack rates on dummy caterpillars in tropical forest where arthropod predators dominate: an experiment using clay and dough dummies with green colourants on various plant species

Predation can be one of the key factors that determine abundance in insect herbivore communities, and drive evolution of body size, and anti‐predator traits, including crypsis. Population dynamics and selection pressures will depend on the identity of dominant predators in the system, and these may vary substantially among habitats. Arthropods emerge as chief predators on caterpillars in the understorey of non‐montane tropical forest, whereas birds dominate elsewhere. In a tropical forest in Uganda, Africa, we evaluated marks on dummy caterpillars that differed in size, material (clay vs. dough), colourant, and plant species on which dummy caterpillars were exposed. We included live caterpillars to estimate the extent to which studies using artificial caterpillars reflect actual levels of predation. Ants and wasps were the most important damagers of dummy caterpillars, whereas bug and beetle damage was very rare, and no bird or small mammal damage was observed. Daily attack rates did not differ significantly from apparent mortality of live caterpillars (daily mortality = 12.1%), but dummy caterpillars made from dough were attacked more frequently (daily attack rate = 18.4%) than those from clay (daily attack rate = 6.9%). Caterpillars of different colour and size, and caterpillars exposed on different plant species had the same chances to be predated. This is in contrast to results from temperate area studies where birds dominate and are not affected by dummy caterpillar material, but prefer larger caterpillars. Our results are consistent with dominant predators on tropical forest caterpillars being invertebrates that are more chemically than visually oriented, so that: (1) material used for dummy caterpillars is important, (2) background matching is relatively unimportant, and (3) being large may have less of a cost. These patterns in predation might facilitate polyphagy and evolution of large body size in tropical Lepidoptera.     

基于MaxEnt模型的人类干扰对滇金丝猴潜在分布的影响

滇金丝猴 (Rhinopithecus bieti) 是我国特有的濒危灵长类动物,预测其栖息地变化,评估人类活动影响,进而识别保护空缺,对该物种的保护具有重要意义。本文使用出行大数据估计人类出行密度,并将这一指标引入栖息地模型的构建;运用MaxEnt模型和空间分析技术分别构建自然环境和人类干扰两种情景下滇金丝猴的适宜栖息地模型,并分析自然环境与人类干扰两类共计11个变量对栖息地的影响。结果显示：(1) MaxEnt模型的预测精度较高,基于出行大数据的人类出行密度这一指标能很好表征人类干扰对栖息地的影响。(2) 模型预测得到滇金丝猴高适宜栖息地面积3 487.28 km²,认为影响滇金丝猴潜在分布的主要环境变量是海拔、年降水量、人类出行密度和距道路距离。(3) 人类干扰对滇金丝猴栖息地有明显的负影响 (使适宜栖息地面积相较于自然环境下减少9.32%),其中人类出行活动对滇金丝猴的栖息地干扰最为明显;同时还发现研究区78.8%的区域均受到一个或多个人类变量的较强干扰。(4) 在现有15个滇金丝猴群的活动斑块中,3个同时具有较高栖息地适宜性和较多人类干扰的斑块,可作为重点保护区域;同时发现栖息地质量在距道路和居民点约2 500 m处均出现明显拐点,可作为开展保护工作的缓冲区参考距离。降低这些区域的人类干扰强度,对滇金丝猴的生存具有更重要的现实保护意义。     

Simulating the effects of climate change on the distribution of an invasive plant,using a high resolution,local scale,mechanistic approach: challenges and insights

The growing economic and ecological damage associated with biological invasions, which will likely be exacerbated by climate change, necessitates improved projections of invasive spread. Generally, potential changes in species distribution are investigated using climate envelope models; however, the reliability of such models has been questioned and they are not suitable for use at local scales. At this scale, mechanistic models are more appropriate. This paper discusses some key requirements for mechanistic models and utilises a newly developed model (PSS[gt]) that incorporates the influence of habitat type and related features (e.g., roads and rivers), as well as demographic processes and propagule dispersal dynamics, to model climate induced changes in the distribution of an invasive plant (Gunnera tinctoria) at a local scale. A new methodology is introduced, dynamic baseline benchmarking, which distinguishes climate‐induced alterations in species distributions from other potential drivers of change. Using this approach, it was concluded that climate change, based on IPCC and C4i projections, has the potential to increase the spread‐rate and intensity of G. tinctoria invasions. Increases in the number of individuals were primarily due to intensification of invasion in areas already invaded or in areas projected to be invaded in the dynamic baseline scenario. Temperature had the largest influence on changes in plant distributions. Water availability also had a large influence and introduced the most uncertainty in the projections. Additionally, due to the difficulties of parameterising models such as this, the process has been streamlined by utilising methods for estimating unknown variables and selecting only essential parameters.     

Plant and soil effects on bacterial communities associated with Miscanthus × giganteus rhizosphere and rhizomes

Bacterial assemblages, especially diazotroph assemblages residing in the rhizomes and the rhizosphere soil of Miscanthus × giganteus, contribute to plant growth and nitrogen use efficiency. However, the composition of these microbial communities has not been adequately explored nor have the potential ecological drivers for these communities been sufficiently studied. This knowledge is needed for understanding and potentially improving M. × giganteus – microbe interactions, and further enhancing sustainability of M. × giganteus production. In this study, cultivated M. × giganteus from four sites in Illinois, Kentucky, Nebraska, and New Jersey were collected to examine the relative influences of soil conditions and plant compartments on assembly of the M. × giganteus‐associated microbiome. Automated ribosomal intergenic spacer (ARISA) and terminal restriction fragment length polymorphism (T‐RFLP) targeting the nifH gene were applied to examine the total bacterial communities and diazotroph assemblages that reside in the rhizomes and the rhizosphere. Distinct microbial assemblages were detected in the endophytic and rhizosphere compartments. Site soil conditions had strong correlation with both total bacterial and diazotroph assemblages, but in different ways. Nitrogen treatments showed no significant effect on the composition of diazotroph assemblages in most sites. Endophytic compartments of different M. × giganteus plants tended to harbor similar microbial communities across all sites, whereas the rhizosphere soil of different plant tended to harbor diverse microbial assemblages that were distinct among sites. These observations offer insight into better understanding of the associative interactions between M. × giganteus and diazotrophs, and how this relationship is influenced by agronomic and edaphic factors.     

Process,correlation and parameter fitting in species distribution models: a response to Kriticos et al

In a recent article (Dormann et al., 2012, Journal of Biogeography, 39, 2119–2131), we compared different approaches to species distribution modelling and depicted modelling approaches along an axis from purely ‘correlative’ to ‘forward process‐based’ models. In their correspondence, Kriticos et al. (2013, Journal of Biogeography, doi: 10.1111/j.1365‐2699.2012.02791.x ) challenge this view, claiming that our continuum representation neglects differences among models and does not consider the ability of fitted process‐based models to combine the advantages of both process‐based and correlative modelling approaches. Here we clarify that the continuum view resulted from recognition of the manifold differences between models. We also reinforce the point that the current trend towards combining different modelling approaches may lead not only to the desired combination of the advantages but also to the accumulation of the disadvantages of those approaches. This point has not been made sufficiently clear previously.