Climate predicts wildland fire extent across China.

Wildland fire extent varies seasonally and interannually in response to climatic and landscape-level drivers, yet predicting wildfires remains a challenge. Existing linear models that characterize climate and wildland fire relationships fail to account for non-stationary and non-linear associations, thus limiting prediction accuracy. To account for non-stationary and non-linear effects, we use time-series climate and wildfire extent data from across China with unit root methods, thus providing an approach for improved wildfire prediction. Results from this approach suggest that wildland area burned is sensitive to vapor pressure deficit (VPD) and maximum temperature changes over short and long-term scenarios. Moreover, repeated fires constrain system variability resulting in non-stationarity responses. We conclude that an autoregressive distributed lag (ARDL) approach to dynamic simulation models better elucidates interactions between climate and wildfire compared to more commonly used linear models. We suggest that this approach will provide insights into a better understanding of complex ecological relationships and represents a significant step toward the development of guidance for regional planners hoping to address climate-driven increases in wildfire incidence and impacts.

Seasonal weather and climate prediction over area burned in grasslands of northeast China.

Grassland fire dynamics are subject to myriad climatic, biological, and anthropogenic drivers, thresholds, and feedbacks and therefore do not conform to assumptions of statistical stationarity. The presence of non-stationarity in time series data leads to ambiguous results that can misinform regional-level fire management strategies. This study employs non-stationarity in time series data among multiple variables and multiple intensities using dynamic simulations of autoregressive distributed lag models to elucidate key drivers of climate and ecological change on burned grasslands in Xilingol, China. We used unit root methods to select appropriate estimation methods for further analysis. Using the model estimations, we developed scenarios emulating the effects of instantaneous changes (i.e., shocks) of some significant variables on climate and ecological change. Changes in mean monthly wind speed and maximum temperature produce complex responses on area burned, directly, and through feedback relationships. Our framework addresses interactions among multiple drivers to explain fire and ecosystem responses in grasslands, and how these may be understood and prioritized in different empirical contexts needed to formulate effective fire management policies.

Pollen adaptation to ant pollination: a case study from the Proteaceae.

BACKGROUND AND AIMS: Ant-plant associations are widely diverse and distributed throughout the world, leading to antagonistic and/or mutualistic interactions. Ant pollination is a rare mutualistic association and reports of ants as effective pollinators are limited to a few studies. Conospermum (Proteaceae) is an insect-pollinated genus well represented in the south-western Australia biodiversity hotspot, and here we aimed to evaluate the role of ants as pollinators of C. undulatum. METHODS: Pollen germination after contact with several species of ants and bees was tested for C. undulatum and five co-flowering species for comparison. We then sampled the pollen load of floral visitors of C. undulatum to assess whether ants carried a pollen load sufficient to enable pollination. Lastly, we performed exclusion treatments to assess the relative effect of flying- and non-flying-invertebrate floral visitors on the reproduction of C. undulatum. For this, we measured the seed set under different conditions: ants exclusion, flying-insects exclusion and control. KEY RESULTS: Pollen of C. undulatum, along with the other Conospermum species, had a germination rate after contact with ants of ~80 % which did not differ from the effect of bees; in contrast, the other plant species tested showed a drop in the germination rate to ~10 % following ant treatments. Although ants were generalist visitors, they carried a pollen load with 68-86 % of suitable grains. Moreover, ants significantly contributed to the seed set of C. undulatum. CONCLUSIONS: Our study highlights the complexity of ant-flower interactions and suggests that generalizations neglecting the importance of ants as pollinators cannot be made. Conospermum undulatum has evolved pollen with resistance to the negative effect of ant secretions on pollen grains, with ants providing effective pollination services to this threatened species.

Floral display and habitat fragmentation: Effects on the reproductive success of the threatened mass-flowering Conospermum undulatum (Proteaceae).

Fragmentation of natural vegetation is currently one of the largest threats to plant populations and their interactions with pollinators. Plant reproductive susceptibility to habitat fragmentation has been investigated in many species; however, the response of wild mass-flowering species is poorly known, with research limited to mainly boreal plant species.Here, we studied twelve remnant populations of the threatened mass-flowering shrub Conospermum undulatum in the southwest Australian biodiversity hotspot, each presenting different population size, level of isolation, and floral display. We assessed the impact of fragmentation on (a) fruit and seed production; and (b) seed germination. To gain a deeper understanding of factors influencing the reproductive success of C. undulatum, we performed pollinator exclusion and self-pollination treatments to experimentally assess the mating system of this threatened shrub.We found C. undulatum to be strictly self-incompatible and totally reliant on pollinators visiting with an outcrossed pollen load to complete the reproductive cycle. Further, we found that fruit production dropped from 35% to <20% as a result of decreasing floral display. A reduction in population size from 880 to 5 plants and from ~700 to 0.21 in the floral display index led to a decrease in seed output, while a similar reduction in seed output, from 6% to 3%, was observed as a result of increasing isolation index from -21.41 to -0.04. Overall, seed germination was positively related to population size, and a negative relationship was found between germination and isolation. Synthesis and applications. Our results demonstrate the important relationship between pollinators and floral morphology in plants of southwest Australia that have coevolved with native pollinators and developed characteristic flower morphologies over long time frames. Indeed, due to its characteristic pollination mechanism, the self-incompatible C. undulatum can only rely on specialized native pollinators for pollen flow and cannot rely on its mass-flowering trait to attract generalist pollinators from coflowering species; neither can it compensate for the lack of visitors by promoting geitonogamy. Consequently, fragmentation has a significant effect on the reproductive output of C. undulatum, and size, isolation, and floral display of populations are important factors to be considered when planning conservation actions for the species.

Isolation, characterization, and cross-amplification of 20 microsatellite markers for Conospermum undulatum (Proteaceae).

PREMISE: Recent habitat fragmentation is posing a risk to the wavy-leaved smokebush, Conospermum undulatum (Proteaceae), a rare plant species endemic to southwestern Western Australia. Microsatellite markers are required to characterize the genetic diversity and structure of the species for conservation purposes and to facilitate ecological studies. METHODS AND RESULTS: Illumina MiSeq high-throughput sequencing was used to develop 20 novel microsatellite markers for C. undulatum. Polymorphism at each locus was assessed using 72 individuals from three natural populations. Nineteen markers were polymorphic, with the number of alleles per locus ranging from two to 21, and observed and expected heterozygosity ranging from 0.000 to 1.000 and 0.117 to 0.919, respectively. All markers successfully amplified in three congeneric species (C. stoechadis, C. canaliculatum and C. triplinervium). CONCLUSIONS: The microsatellite markers will be useful for revealing patterns of genetic diversity, dispersal dynamics, and hybridization events for C. undulatum to inform future conservation efforts.

Incorporating Field Studies into Species Distribution and Climate Change Modelling: A Case Study of the Koomal Trichosurus vulpecula hypoleucus (Phalangeridae).

Species distribution models (SDMs) are an effective way of predicting the potential distribution of species and their response to environmental change. Most SDMs apply presence data to a relatively generic set of predictive variables such as climate. However, this weakens the modelling process by overlooking the responses to more cryptic predictive variables. In this paper we demonstrate a means by which data gathered from an intensive animal trapping study can be used to enhance SDMs by combining field data with bioclimatic modelling techniques to determine the future potential distribution for the koomal (Trichosurus vulpecula hypoleucus). The koomal is a geographically isolated subspecies of the common brushtail possum, endemic to south-western Australia. Since European settlement this taxon has undergone a significant reduction in distribution due to its vulnerability to habitat fragmentation, introduced predators and tree/shrub dieback caused by a virulent group of plant pathogens of the genus Phytophthora. An intensive field study found: 1) the home range for the koomal rarely exceeded 1 km in in length at its widest point; 2) areas heavily infested with dieback were not occupied; 3) gap crossing between patches (>400 m) was common behaviour; 4) koomal presence was linked to the extent of suitable vegetation; and 5) where the needs of koomal were met, populations in fragments were demographically similar to those found in contiguous landscapes. We used this information to resolve a more accurate SDM for the koomal than that created from bioclimatic data alone. Specifically, we refined spatial coverages of remnant vegetation and dieback, to develop a set of variables that we combined with selected bioclimatic variables to construct models. We conclude that the utility value of an SDM can be enhanced and given greater resolution by identifying variables that reflect observed, species-specific responses to landscape parameters and incorporating these responses into the model.