Search Results (9)

Old-growth forests provide many ecosystem services and benefits. However, they are becoming increasingly rare and thus are an urgent priority for conservation. Accurately mapping old-growth forests is a critical step in this process. Here, we used LiDAR, an improved individual tree crown delineation algorithm for broadleaved forests, Gaussian mixture modelling, and a rule-based classification key to map the extent and location of old-growth forests across a topographically and ecologically complex landscape of 337,548 ha in southeastern Australia. We found that variation in old growth extent was largely driven by the old growth definition, which is a human construct, rather than by uncertainty in the technical aspect of the work. Current regulations define a stand as old growth if it was recruited prior to 1900 (i.e., >120 years old) and is undisturbed (i.e., <10% regrowth canopy cover and no visible disturbance traces). Only 2.7% (95% confidence intervals ranging from 1.4 to 4.9%) of the forests in the study landscape met these criteria. However, this definition is overly restrictive as it leaves many multi-aged stands with ecologically mature elements (e.g., one or more legacy trees amid regrowth) unprotected. Removing the regrowth filter, an indicator of past disturbances, increased the proportion of old-growth forests from 2.7% to 15% of the landscape. Our analyses also revealed that 60% of giant trees (>250 cm in diameter at breast height) were located within 50 m of cool temperate rainforests and cool temperate mixed forests (i.e., streamlines). We discuss the implication of our findings for the conservation and management of high-conservation-value forests in the region. Full article

Extreme climate anomalies are expected to become more frequent under climate change, and rare extreme events, such as the 2021 western North American heat wave, provide an opportunity for comparative empirical analysis of ecosystem resilience. This study evaluates anomalies in a remotely sensed enhanced vegetation index (EVI) in the aftermath of the record-setting western North American heat wave in 2021, with temperatures approaching 50 °C in coastal and interior regions of the Pacific Northwest. The results show that the forest ecosystems most affected were not necessarily those that experienced the highest absolute temperature values. Instead, the greatest reductions in greenness were observed across northern coastal temperate rainforests. Most affected were the cooler, very wet, hyper-maritime ecosystems that are normally buffered from large temperature fluctuation by a strong oceanic influence. In contrast, moisture-limited forests of the interior plateau of British Columbia, where most of the all-time record temperatures occurred, generally showed normal or even increased productivity during and after the heat wave. A putative explanation for this heat resistance of interior forests was normal or above average precipitation leading up to the heat event, allowing for transpirational cooling. Nevertheless, the data suggest that the largest protected coastal temperate rainforest in the world, with 6.4 million hectares, is comparatively more vulnerable to extreme heat waves, which are expected to become more frequent under climate warming, than other ecosystems of the Pacific Northwest. Full article

Soil seed banks play an important role in plant species persistence in fire-prone systems. Response to fire related germination cues often reflect historical fire regimes and can be important in maintaining ecotones between different forest types. We assessed the effects of heat and/or smoke on the soil stored seed banks across an ecotone of eucalypt to rainforest overstorey comprising wet forest, cool temperate mixed forest, and cool temperate rainforest in south-eastern Australia. Soils from five replicates of each forest type were subjected to very low (45 °C), low (65 °C) and high (90 °C) heat with or without two different smoke treatments: –smoke-infused vermiculite, and karrikinolide—a phytoreactive compound derived from smoke. Soils were placed in a glasshouse and germinants were identified and counted at weekly intervals. Response to fire cues was consistent among forest types despite underlying differences in the diversity of soil seed banks. There was no overall response of species richness, abundance, or composition to fire cues. Phanerophytes and ant-dispersed species with hard seed coats demonstrated positive response, and endozoochores negative response, to high heat independent of smoke. Endozoochores were concentrated (albeit at low densities) in cool temperate rainforest with no overall effect of seral affiliation on response to fire cues. Given the lack of response to karrikinolide, response to soil disturbance would most likely be associated with mechanical seed abrasion and/or exposure to increased light availability than to non-fire related production of smoke products. Forest type was a stronger determinant of floristics in the germinated soil seed bank than simulated fire related germination cues. Both smoke treatments had little influence on floristics in the germinated seed bank suggesting other, non-fire disturbances such as treefalls and soil turnover by fauna may be more important for germination for many of the species in these forest types. Full article

Heat waves are becoming more frequent due to climate change. Summer heat waves can be particularly deadly in cities, where temperatures are already inflated by abundant impervious, dark surfaces (i.e., the heat island effect). Urban heat waves might be ameliorated by planting and maintaining urban forests. Previous observational research has suggested that conifers may be particularly effective in cooling cities. However, the observational nature of these studies has prevented the identification of the direct and indirect mechanisms that drive this differential cooling. Here, we develop a systems dynamics representation of urban forests to model the effects of the percentage cover of either conifers or broadleaf trees on temperature. Our model includes physiological and morphological differences between conifers and broadleaf trees, and physical feedback among temperature and energy fluxes. We apply the model to a case study of Vancouver, BC, Canada. Our model suggests that in temperate rainforest cities, conifers may by 1.0 °C cooler than broadleaf trees; this differential increases to 1.2 °C when percentage tree cover increases from 17% to 22% and to 1.7 °C at 30% cover. Our model suggests that these differences are due to three key tree traits: leaf area index, leaf boundary layer resistance, and dry mass per leaf area. Creating urban forests that optimize these three variables may not only sequester CO₂ to mitigate global climate change but also be most effective at locally minimizing deadly urban heat waves. Full article

Predictive vegetation mapping is an essential tool for managing and conserving high conservation-value forests. Cool temperate rainforests (Rainforest) and cool temperate mixed forests (Mixed Forest, i.e., rainforest spp. overtopped by large remnant Eucalyptus trees) are threatened forest types in the Central Highlands of Victoria. Logging of these forest types is prohibited; however, the surrounding native Eucalyptus forests can be logged in some areas of the landscape. This requires accurate mapping and delineation of these vegetation types. In this study, we combine niche modelling, multispectral imagery, and LiDAR data to improve predictive vegetation mapping of these two threatened ecosystems in southeast Australia. We used a dataset of 1586 plots partitioned into four distinct forest types that occur in close proximity in the Central Highlands: Eucalyptus, Tree fern, Mixed Forest, and Rainforest. We calibrated our model on a training dataset and validated it on a spatially distinct testing dataset. To avoid overfitting, we used Bayesian regularized multinomial regression to relate predictors to our four forest types. We found that multispectral predictors were able to distinguish Rainforest from Eucalyptus forests due to differences in their spectral signatures. LiDAR-derived predictors were effective at discriminating Mixed Forest from Rainforest based on forest structure, particularly LiDAR predictors based on existing domain knowledge of the system. For example, the best predictor of Mixed Forest was the presence of Rainforest-type understorey overtopped by large Eucalyptus crowns, which is effectively aligned with the regulatory definition of Mixed Forest. Environmental predictors improved model performance marginally, but helped discriminate riparian forests from Rainforest. However, the best model for classifying forest types was the model that included all three classes of predictors (i.e., spectral, structural, and environmental). Using multiple data sources with differing strengths improved classification accuracy and successfully predicted the identity of 88% of the plots. Our study demonstrated that multi-source methods are important for capturing different properties of the data that discriminate ecosystems. In addition, the multi-source approach facilitated adding custom metrics based on domain knowledge which in turn improved the mapping of high conservation-value forest. Full article

The genus Bactrocera (Diptera: Tephritidae) is endemic to the monsoonal rainforests of South-east Asia and the western Pacific where the larvae breed in ripe, fleshy fruits. While most Bactrocera remain rainforest restricted, species such as Bactrocera dorsalis, Bactrocera zonata and Bactrocera tryoni are internationally significant pests of horticulture, being both highly invasive and highly polyphagous. Almost universally in the literature it is assumed that Bactrocera breed continuously if temperature and hosts are not limiting. However, despite that, these flies show distinct seasonality. If discussed, seasonality is generally attributed to the fruiting of a particular breeding host (almost invariably mango or guava), but the question appears not to have been asked why flies do not breed at other times of the year despite other hosts being available. Focusing initially on B. tryoni, for which more literature is available, we demonstrate that the seasonality exhibited by that species is closely correlated with the seasons of its endemic rainforest environment as recognised by traditional Aboriginal owners. Evidence suggests the presence of a seasonal reproductive arrest which helps the fly survive the first two-thirds of the dry season, when ripe fruits are scarce, followed by a rapid increase in breeding at the end of the dry season as humidity and the availability of ripe fruit increases. This seasonal phenology continues to be expressed in human-modified landscapes and, while suppressed, it also partially expresses in long-term cultures. We subsequently demonstrate that B. dorsalis, across both its endemic and invasive ranges, shows a very similar seasonality although reversed in the northern hemisphere. While high variability in the timing of B. dorsalis population peaks is exhibited across sites, a four-month period when flies are rare in traps (Dec–Mar) is highly consistent, as is the fact that nearly all sites only have one, generally very sharp, population peak per year. While literature to support or deny a reproductive arrest in B. dorsalis is not available, available data is clear that continuous breeding does not occur in this species and that there are seasonal differences in reproductive investment. Throughout the paper we reinforce the point that our argument for a complex reproductive physiology in Bactrocera is based on inductive reasoning and requires specific, hypothesis-testing experiments to confirm or deny, but we do believe there is ample evidence to prioritise such research. If it is found that species in the genus undergo a true reproductive diapause then there are very significant implications for within-field management, market access, and biosecurity risk planning which are discussed. Arguably the most important of these is that insects in diapause have greater stress resistance and cold tolerance, which could explain how tropical Bactrocera species have managed to successfully invade cool temperate regions. Full article

Anonychomyrma is a dolichoderine ant genus of cool-temperate Gondwanan origin with a current distribution that extends from the north of southern Australia into the Australasian tropics. Despite its abundance and ecological dominance, little is known of its species diversity and distribution throughout its range. Here, we describe the diversity and distribution of Anonychomyrma in the Australian Wet Tropics bioregion, where only two of the many putative species are described. We hypothesise that the genus in tropical Australia retains a preference for cool wet rainforests reminiscent of the Gondwanan forests that once dominated Australia, but now only exist in upland habitats of the Wet Tropics. Our study was based on extensive recent surveys across five subregions and along elevation and vertical (arboreal) gradients. We integrated genetic (CO1) data with morphology to recognise 22 species among our samples, 20 of which appeared to be undescribed. As predicted, diversity and endemism were concentrated in uplands above 900 m a.s.l. Distribution modelling of the nine commonest species identified maximum temperature of the warmest month, rainfall seasonality, and rainfall of the wettest month as correlates of distributional patterns across subregions. Our study supported the notion that Anonychomyrma radiated from a southern temperate origin into the tropical zone, with a preference for areas of montane rainforest that were stably cool and wet over the late quaternary. Full article

Modern approaches to predictive ecosystem mapping (PEM) have not thoroughly explored the use of ‘characteristic’ gradients, which describe vegetation structure (e.g., light detection and ranging (lidar)-derived structural profiles). In this study, we apply a PEM approach by classifying the dominant stand types within the Central Highlands region of south-eastern Australia using both lidar and species distribution models (SDMs). Similarity percentages analysis (SIMPER) was applied to comprehensive floristic surveys to identify five species which best separated stand types. The predicted distributions of these species, modelled using random forests with environmental (i.e., climate, topography) and optical characteristic gradients (Landsat-derived seasonal fractional cover), provided an ecological basis for refining stand type classifications based only on lidar-derived structural profiles. The resulting PEM model represents the first continuous distribution map of stand types across the study region that delineates ecotone stands, which are seral communities comprised of species typical of both rainforest and eucalypt forests. The spatial variability of vegetation structure incorporated into the PEM model suggests that many stand types are not as continuous in cover as represented by current ecological vegetation class distributions that describe the region. Improved PEM models can facilitate sustainable forest management, enhanced forest monitoring, and informed decision making at landscape scales. Full article

Here we investigate the interaction between ecology and climate concerning the distribution of rainforest species differentially distributed along altitudinal gradients of eastern Australia. The potential distributions of the two species closely associated with different rainforest types were modelled to infer the potential contribution of post-glacial warming on spatial distribution and altitudinal range shift. Nothofagus moorei is an integral element of cool temperate rainforest, including cloud forests at high elevation. This distinct climatic envelope is at increased risk with future global warming. Elaeocarpus grandis on the other hand is a lowland species and typical element of subtropical rainforest occupying a climatic envelope that may shift upwards into areas currently occupied by N. moorei. Climate envelope models were used to infer range shift differences between the two species in the past (21 thousand years ago), current and future (2050) scenarios, and to provide a framework to explain observed genetic diversity/structure of both species. The models suggest continuing contraction of the highland cool temperate climatic envelope and expansion of the lowland warm subtropical envelope, with both showing a core average increase in elevation in response to post-glacial warming. Spatial and altitudinal overlap between the species climatic envelopes was at a maximum during the last glacial maximum and is predicted to be a minimum at 2050. Full article