Phylogeography,population genetics and distribution modelling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change

A proactive approach to conservation must be predictive, anticipating how habitats will change and which species are likely to decline or prosper. We use composite species distribution modelling to identify suitable habitats for 18 members of the North American Atlantic Coastal Plain Flora (ACPF) since the Last Glacial Maximum and project these into the future. We then use Scirpus longii (Cyperaceae), a globally imperiled ACPF sedge with many of the characteristics of extinction vulnerability, as a case study. We integrate phylogeographical and population genetic analyses and species distribution modelling to develop a broad view of its current condition and prognosis for conservation. We use genotyping‐by‐sequencing to characterize the genomes of 142 S. longii individuals from 20 populations distributed throughout its range (New Jersey to Nova Scotia). We measure the distribution of genetic diversity in the species and reconstruct its phylogeographical history using the snapp and rase models. Extant populations of S. longii originated from a single refugium south of the Laurentide ice sheet around 25 ka. The genetic diversity of S. longii is exceedingly low, populations exhibit little genetic structure and the species is slightly inbred. Projected climate scenarios indicate that nearly half of extant populations of S. longii will be exposed to unsuitable climate by 2070. Similar changes in suitable habitat will occur for many other northern ACPF species—centres of diversity will shift northward and Nova Scotia may become the last refuges for those species not extinguished.     

A hybrid kinetic and constraint-based model of leaf metabolism allows predictions of metabolic fluxes in different environments

While flux balance analysis (FBA) provides a framework for predicting steady-state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e-photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e-photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e-photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field-grown soybean at two CO₂ concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO₂ on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch–sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO₂. Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.     

Assessment of yield loss of wheat cultivars caused by Heterodera filipjevi under field conditions

Among the cereal cyst nematodes, Heterodera filipjevi is the dominant species of Cereal cyst nematodes (CCNs) in most cereal growing areas of Iran. To evaluate the impact of H. filipjevi on wheat cultivars, a field trial was performed in two infested fields in Isfahan province, Iran 2014 and 2015. The trials were conducted in a factorial experiment based on the complete randomized block design. The treatments consisted of three winter wheat cultivars (Back‐cross Rowshan, Pishtaz and Parsi) which were planted with and without applying nematicide aldicarb Each cultivar was planted in 6 m² (2 × 3 m) plots which were replicated five times. The nematode reproduction factor was calculated after determining the initial and final population of H. filipjevi in each plot before sowing the seeds and after harvesting. The grain yields and growth parameters were recorded and the variables of 2 years experiment evaluated by linear regression analysis. Cultivar × nematicide treatment combinations in the first and second years showed that H. filipjevi significantly affected grain yield and growth parameters in all three cultivars. The results revealed significant reduction of grain yield by 24.8%, 24.8% and 20.4% in Back‐cross Rowshan, Pishtaz and Parsi cultivars, respectively. The nematode reproduction factor ranged from 0.32 to 1.76 in plots plus and minus nematicide application, respectively. The analysis showed linear inverse relationships between the initial population (Pi) and the yields of wheat cultivars in check plots without aldicarb application.     

Landscape effects on gene flow for a climate‐sensitive montane species,the American pika

Climate change is arguably the greatest challenge to conservation of our time. Most vulnerability assessments rely on past and current species distributions to predict future persistence but ignore species' abilities to disperse through landscapes, which may be particularly important in fragmented habitats and crucial for long‐term persistence in changing environments. Landscape genetic approaches explore the interactions between landscape features and gene flow and can clarify how organisms move among suitable habitats, but have suffered from methodological uncertainties. We used a landscape genetic approach to determine how landscape and climate‐related features influence gene flow for American pikas (Ochotona princeps) in Crater Lake National Park. Pikas are heat intolerant and restricted to cool microclimates; thus, range contractions have been predicted as climate changes. We evaluated the correlation between landscape variables and genetic distance using partial Mantel tests in a causal modelling framework, and used spatially explicit simulations to evaluate methods of model optimization including a novel approach based on relative support and reciprocal causal modelling. We found that gene flow was primarily restricted by topographic relief, water and west‐facing aspects, suggesting that physical restrictions related to small body size and mode of locomotion, as well as exposure to relatively high temperatures, limit pika dispersal in this alpine habitat. Our model optimization successfully identified landscape features influencing resistance in the simulated data for this landscape, but underestimated the magnitude of resistance. This is the first landscape genetic study to address the fundamental question of what limits dispersal and gene flow in the American pika.     

Modelling as a tool for analysing the temperature‐dependent future of the Colorado potato beetle in Europe

A warmer climate may increase the risk of attacks by insect pests on agricultural crops, and questions on how to adapt management practice have created a need for impact models. Phenological models driven by climate data can be used for assessing the potential distribution and voltinism of different insect species, but the quality of the simulations is influenced by a range of uncertainties. In this study, we model the temperature‐dependent activity and development of the Colorado potato beetle, and analyse the influence of uncertainty associated with parameterization of temperature and day length response. We found that the developmental threshold has a major impact on the simulated number of generations per year. Little is known about local adaptations and individual variations, but the use of an upper and a lower developmental threshold gave an indication on the potential variation. The day length conditions triggering diapause are known only for a few populations. We used gridded observed temperature data to estimate local adaptations, hypothesizing that cold autumns can leave a footprint in the population genetics by low survival of individuals not reaching the adult stage before winter. Our study indicated that the potential selection pressure caused by climate conditions varies between European regions. Provided that there is enough genetic variation, a local adaption at the northern distribution limit would reduce the number of unsuccessful initiations and thereby increase the potential for spreading to areas currently not infested. The simulations of the impact model were highly sensitive to biases in climate model data, i.e. systematic deviations in comparison with observed weather, highlightening the need of improved performance of regional climate models. Even a moderate temperature increase could change the voltinism of Leptinotarsa decemlineata in Europe, but knowledge on agricultural practice and strategies for countermeasures is needed to evaluate changes in risk of attacks.     

Using maximum entropy to predict the potential distribution of an invasive freshwater snail

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Evolutionary and demographic history of the Californian scrub white oak species complex: an integrative approach

Understanding the factors promoting species formation is a major task in evolutionary research. Here, we employ an integrative approach to study the evolutionary history of the Californian scrub white oak species complex (genus Quercus). To infer the relative importance of geographical isolation and ecological divergence in driving the speciation process, we (i) analysed inter‐ and intraspecific patterns of genetic differentiation and employed an approximate Bayesian computation (ABC) framework to evaluate different plausible scenarios of species divergence. In a second step, we (ii) linked the inferred divergence pathways with current and past species distribution models (SDMs) and (iii) tested for niche differentiation and phylogenetic niche conservatism across taxa. ABC analyses showed that the most plausible scenario is the one considering the divergence of two main lineages followed by a more recent pulse of speciation. Genotypic data in conjunction with SDMs and niche differentiation analyses support that different factors (geography vs. environment) and modes of speciation (parapatry, allopatry and maybe sympatry) have played a role in the divergence process within this complex. We found no significant relationship between genetic differentiation and niche overlap, which probably reflects niche lability and/or that multiple factors, have contributed to speciation. Our study shows that different mechanisms can drive divergence even among closely related taxa representing early stages of species formation and exemplifies the importance of adopting integrative approaches to get a better understanding of the speciation process.     

Interglacial microrefugia and diversification of a cactus species complex: phylogeography and palaeodistributional reconstructions for Pilosocereus aurisetus and allies

The role of Pleistocene climate changes in promoting evolutionary diversification in global biota is well documented, but the great majority of data regarding this subject come from North America and Europe, which were greatly affected by glaciation. The effects of Pleistocene changes on cold‐ and/or dry‐adapted species in tropical areas where glaciers were not present remain sparsely investigated. Many such species are restricted to small areas surrounded by unfavourable habitats, which may represent potential interglacial microrefugia. Here, we analysed the phylogeographic structure and diversification history of seven cactus species in the Pilosocereus aurisetus complex that are restricted to rocky areas with high diversity and endemism within the Neotropical savannas of eastern South America. We combined palaeodistributional estimates with standard phylogeographic approaches based on two chloroplast DNA regions (trnT‐trnL and trnS‐trnG), exon 1 of the nuclear gene PhyC and 10 nuclear microsatellite loci. Our analyses revealed a phylogeographic history marked by multiple levels of distributional fragmentation, isolation leading to allopatric differentiation and secondary contact among divergent lineages within the complex. Diversification and demographic events appear to have been affected by the Quaternary climatic cycles as a result of isolation in multiple patches of xerophytic vegetation. These small patches presently harbouring P. aurisetus populations seem to operate as microrefugia, both at present and during Pleistocene interglacial periods; the role of such microrefugia should be explored and analysed in greater detail.     

Strong thermal acclimation of photosynthesis in tropical and temperate wet‐forest tree species: the importance of altered Rubisco content

Understanding of the extent of acclimation of light‐saturated net photosynthesis (A_n) to temperature (T), and associated underlying mechanisms, remains limited. This is a key knowledge gap given the importance of thermal acclimation for plant functioning, both under current and future higher temperatures, limiting the accuracy and realism of Earth system model (ESM) predictions. Given this, we analysed and modelled T‐dependent changes in photosynthetic capacity in 10 wet‐forest tree species: six from temperate forests and four from tropical forests. Temperate and tropical species were each acclimated to three daytime growth temperatures (T_growth): temperate – 15, 20 and 25 °C; tropical – 25, 30 and 35 °C. CO₂ response curves of A_n were used to model maximal rates of RuBP (ribulose‐1,5‐bisphosphate) carboxylation (V_cmax) and electron transport (J_max) at each treatment's respective T_growth and at a common measurement T (25 °C). SDS‐PAGE gels were used to determine abundance of the CO₂‐fixing enzyme, Rubisco. Leaf chlorophyll, nitrogen (N) and mass per unit leaf area (LMA) were also determined. For all species and T_growth, A_n at current atmospheric CO₂ partial pressure was Rubisco‐limited. Across all species, LMA decreased with increasing T_growth. Similarly, area‐based rates of V_cmax at a measurement T of 25 °C (V_cmax²⁵) linearly declined with increasing T_growth, linked to a concomitant decline in total leaf protein per unit leaf area and Rubisco as a percentage of leaf N. The decline in Rubisco constrained V_cmax and A_n for leaves developed at higher T_growth and resulted in poor predictions of photosynthesis by currently widely used models that do not account for T_growth‐mediated changes in Rubisco abundance that underpin the thermal acclimation response of photosynthesis in wet‐forest tree species. A new model is proposed that accounts for the effect of T_growth‐mediated declines in V_cmax²⁵ on A_n, complementing current photosynthetic thermal acclimation models that do not account for T sensitivity of V_cmax²⁵.     

Modelled net carbon gain responses to climate change in boreal trees: Impacts of photosynthetic parameter selection and acclimation

Boreal forests are crucial in regulating global vegetation‐atmosphere feedbacks, but the impact of climate change on boreal tree carbon fluxes is still unclear. Given the sensitivity of global vegetation models to photosynthetic and respiration parameters, we determined how predictions of net carbon gain (C‐gain) respond to variation in these parameters using a stand‐level model (MAESTRA). We also modelled how thermal acclimation of photosynthetic and respiratory temperature sensitivity alters predicted net C‐gain responses to climate change. We modelled net C‐gain of seven common boreal tree species under eight climate scenarios across a latitudinal gradient to capture a range of seasonal temperature conditions. Physiological parameter values were taken from the literature together with different approaches for thermally acclimating photosynthesis and respiration. At high latitudes, net C‐gain was stimulated up to 400% by elevated temperatures and CO₂ in the autumn but suppressed at the lowest latitudes during midsummer under climate scenarios that included warming. Modelled net C‐gain was more sensitive to photosynthetic capacity parameters (V_cmax, J_max, Arrhenius temperature response parameters, and the ratio of J_max to V_cmax) than stomatal conductance or respiration parameters. The effect of photosynthetic thermal acclimation depended on the temperatures where it was applied: acclimation reduced net C‐gain by 10%–15% within the temperature range where the equations were derived but decreased net C‐gain by 175% at temperatures outside this range. Thermal acclimation of respiration had small, but positive, impacts on net C‐gain. We show that model simulations are highly sensitive to variation in photosynthetic parameters and highlight the need to better understand the mechanisms and drivers underlying this variability (e.g., whether variability is environmentally and/or biologically driven) for further model improvement.     

The difficulty of using species distribution modelling for the conservation of refugee species – the example of European bison

Refugee species have been confined to suboptimal habitat through historic anthropogenic factors. If this is unknown, management might actively conserve these species in suboptimal habitat assuming it represents optimal habitat. Similarly, species distribution modelling (SDM) might misguide conservation management of refugee species by only using presence data from suboptimal habitats. We illustrate this by commenting on a recent SDM for European bison that reconstructed the historic distribution of the species. We challenge the interpretation of this model by suggesting an alternative historic biogeography based on the refugee species concept. We argue that, in the case of refugee species, historic reconstructions using SDM cannot be used as a template for conservation management. Rather, experimental re‐introduction programmes should provide us with population performance and life history data from a range of suboptimal to optimal habitats. Such data could be used in mechanistic niche modelling to predict potential distribution of refugee species.     

Early response of the platypus to climate warming

Combining a climatic envelope modelling technique with more than two centuries (1800–2009) of distribution records has revealed the effects of a changing climate on the egg‐laying monotreme, the platypus, Ornithorhynchus anatinus. We show that the main factor associated with platypus occurrence switched from aquatic habitat availability (estimated by rainfall) to thermal tolerances (estimated by annual maximum temperature) in the 1960s. This correlates directly with the change in the annual maximum temperature anomaly from cooler to warmer conditions in southeastern Australia. Modelling of platypus habitat under emission scenarios (A1B, A2, B1 and B2) revealed large decreases (>30%) in thermally suitable habitat by 2070. This reduction, compounded by increasing demands for water for agriculture and potable use, suggests that there is real cause for concern over the future status of this species, and highlights the need for restoration of thermal refugia within the platypus’ modelled range.     

Modelling the potential distribution of endangered Prunus africana (Hook.f.) Kalkm. in East Africa

Continued harvesting and climate change are affecting the distributions of many plant species and may lead to numerous extinctions over the next century. Endangered species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modelling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, of tree species. We used MaxEnt algorithm for species distribution modelling to assess the potential distribution and climate change risks for a threatened Prunus africana, in East Africa. Data from different herbaria on its distribution were linked to data on climate to test hypotheses on the factors determining its distribution. Predictive models were developed and projected onto a climate scenario for 2050 to assess climate change risks. Precipitation of driest quarter and annual precipitation appeared to be the main factors influencing its distribution. Climate change was predicted to result in reductions of the species' habitats (e.g. Erasmus et al., Glob. Change Biol. 2002; 8 : 679). Prunus africana distribution is thus highly vulnerable to a warming climate and highlights the fact that both in‐situ and ex‐situ conservation will be a solution to global warming.     

Distance models as a tool for modelling detection probability and density of native bumblebees

Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators.     

Contrasting growth forecasts across the geographical range of Scots pine due to altitudinal and latitudinal differences in climatic sensitivity

Ongoing changes in global climate are altering ecological conditions for many species. The consequences of such changes are typically most evident at the edge of a species’ geographical distribution, where differences in growth or population dynamics may result in range expansions or contractions. Understanding population responses to different climatic drivers along wide latitudinal and altitudinal gradients is necessary in order to gain a better understanding of plant responses to ongoing increases in global temperature and drought severity. We selected Scots pine (Pinus sylvestris L.) as a model species to explore growth responses to climatic variability (seasonal temperature and precipitation) over the last century through dendrochronological methods. We developed linear models based on age, climate and previous growth to forecast growth trends up to year 2100 using climatic predictions. Populations were located at the treeline across a latitudinal gradient covering the northern, central and southernmost populations and across an altitudinal gradient at the southern edge of the distribution (treeline, medium and lower elevations). Radial growth was maximal at medium altitude and treeline of the southernmost populations. Temperature was the main factor controlling growth variability along the gradients, although the timing and strength of climatic variables affecting growth shifted with latitude and altitude. Predictive models forecast a general increase in Scots pine growth at treeline across the latitudinal distribution, with southern populations increasing growth up to year 2050, when it stabilizes. The highest responsiveness appeared at central latitude, and moderate growth increase is projected at the northern limit. Contrastingly, the model forecasted growth declines at lowland‐southern populations, suggesting an upslope range displacement over the coming decades. Our results give insight into the geographical responses of tree species to climate change and demonstrate the importance of incorporating biogeographical variability into predictive models for an accurate prediction of species dynamics as climate changes.