Shifts in floristic composition and structure in Australian rangelands.

Monitoring shifts in vegetation composition over time is essential for tracking biodiversity changes and for designing ecosystem management strategies. In Australia, the Terrestrial Ecosystem Research Network (TERN) provides a continent-wide network of monitoring sites (AusPlots) that can be used to assess the shifts in vegetation composition and structure of Australian Major Vegetation Groups (MVGs). Here we use time-series site data to quantify the extent and rate of MVG shifts between repeat visits and to recommend the most appropriate sampling frequency for specific MVGs. The research area spans a ~1,500 km latitudinal gradient within south/central Australia from arid rangelands in the north to Mediterranean vegetation in the south. The standardized AusPlots protocol was employed to repeatedly survey 103 one-hectare plots, assessed between 2011 and 2019. Floristic and growth form dissimilarities between visits were calculated with distance metrics and then regressed against survey interval. Multivariate ordination was used to explore temporal floristic shifts. Rank-dominance curves were used to display variations in species' importance. Between repeated visits, sites exhibited high variability for all vegetation parameters and trajectories. However, several trends emerged: (a) Species composition moved away from baseline linearly with intervals between surveys. (b) The rate of species turnover was approximately double in communities that are herbaceous versus woody-dominated. (c) Species abundances and growth forms shift at different speeds. All floristic and structural metrics shifted between re-visits, with varying magnitude and speed, but herbaceous-dominated plots showed higher floristic dynamism. Although the expanse, logistics, and the short time between visits constrained our analysis and interpretation, our results suggest that shorter revisit intervals may be appropriate for herbaceous compared to woody systems to track change most efficiently.

Plant families exhibit unique geographic trends in C4 richness and cover in Australia.

Numerous studies have analysed the relationship between C4 plant cover and climate. However, few have examined how different C4 taxa vary in their response to climate, or how environmental factors alter C4:C3 abundance. Here we investigate (a) how proportional C4 plant cover and richness (relative to C3) responds to changes in climate and local environmental factors, and (b) if this response is consistent among families. Proportional cover and richness of C4 species were determined at 541 one-hectare plots across Australia for 14 families. C4 cover and richness of the most common and abundant families were regressed against climate and local parameters. C4 richness and cover in the monocot families Poaceae and Cyperaceae increased with latitude and were strongly positively correlated with January temperatures, however C4 Cyperaceae occupied a more restricted temperature range. Seasonal rainfall, soil pH, soil texture, and tree cover modified proportional C4 cover in both families. Eudicot families displayed considerable variation in C4 distribution patterns. Proportional C4 Euphorbiaceae richness and cover were negatively correlated with increased moisture availability (i.e. high rainfall and low aridity), indicating they were more common in dry environments. Proportional C4 Chenopodiaceae richness and cover were weakly correlated with climate and local environmental factors, including soil texture. However, the explanatory power of C4 Chenopodiaceae models were poor, suggesting none of the factors considered in this study strongly influenced Chenopodiaceae distribution. Proportional C4 richness and cover in Aizoaceae, Amaranthaceae, and Portulacaceae increased with latitude, suggesting C4 cover and richness in these families increased with temperature and summer rainfall, but sample size was insufficient for regression analysis. Results demonstrate the unique relationships between different C4 taxa and climate, and the significant modifying effects of environmental factors on C4 distribution. Our work also revealed C4 families will not exhibit similar responses to local perturbations or climate.

Applying conservation reserve design strategies to define ecosystem monitoring priorities.

In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long-time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well-known approaches for conservation design, the "minimum set" and the "maximal coverage" problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot-by-plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long-term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range-rarity-richness was balanced in terms of complementarity and representativeness, whereas its richness-corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision-making.

The photosynthetic pathways of plant species surveyed in Australia's national terrestrial monitoring network.

The photosynthetic pathway of plants is a fundamental trait that influences terrestrial environments from the local to global level. The distribution of different photosynthetic pathways in Australia is expected to undergo a substantial shift due to climate change and rising atmospheric CO2; however, tracking change is hindered by a lack of data on the pathways of species, as well as their distribution and relative cover within plant communities. Here we present the photosynthetic pathways for 2428 species recorded across 541 plots surveyed by Australia's Terrestrial Ecosystem Research Network (TERN) between 2011 and 2017. This dataset was created to facilitate research exploring trends in vegetation change across Australia. Species were assigned a photosynthetic pathway using published literature and stable carbon isotope analysis of bulk tissue. The photosynthetic pathway of species can be extracted from the dataset individually, or used in conjunction with vegetation surveys to study the occurrence and abundance of pathways across the continent. This dataset will be updated as TERN's plot network expands and new information becomes available.

Effective ecosystem monitoring requires a multi-scaled approach.

Ecosystem monitoring is fundamental to our understanding of how ecosystem change is impacting our natural resources and is vital for developing evidence-based policy and management. However, the different types of ecosystem monitoring, along with their recommended applications, are often poorly understood and contentious. Varying definitions and strict adherence to a specific monitoring type can inhibit effective ecosystem monitoring, leading to poor program development, implementation and outcomes. In an effort to develop a more consistent and clear understanding of ecosystem monitoring programs, we here review the main types of monitoring and recommend the widespread adoption of three classifications of monitoring, namely, targeted, surveillance and landscape monitoring. Landscape monitoring is conducted over large areas, provides spatial data, and enables questions relating to where and when ecosystem change is occurring to be addressed. Surveillance monitoring uses standardised field methods to inform on what is changing in our environments and the direction and magnitude of that change, whilst targeted monitoring is designed around testable hypotheses over defined areas and is the best approach for determining the causes of ecosystem change. The classification system is flexible and can incorporate different interests, objectives, targets and characteristics as well as different spatial scales and temporal frequencies, while also providing valuable structure and consistency across distinct ecosystem monitoring programs. To support our argument, we examine the ability of each monitoring type to inform on six key types of questions that are routinely posed for ecosystem monitoring programs, such as where and when change is occurring, what is the magnitude of change, and how can the change be managed? As we demonstrate, each type of ecosystem monitoring has its own strengths and weaknesses, which should be carefully considered relative to the desired results. Using this scheme, scientists and land managers can design programs best suited to their needs. Finally, we assert that for our most serious environmental challenges, it is essential that we include information from each of these monitoring scales to inform on all facets of ecosystem change, and this is best achieved through close collaboration between the scales. With a renewed understanding of the importance of each monitoring type, along with greater commitment to monitor cooperatively, we will be well placed to address some of our greatest environmental challenges.

A benthic bioindicator reveals distinct land and ocean-Based influences in an urbanized coastal embayment.

Biogeochemical maps of coastal regions can be used to identify important influences and inputs that define nearshore environments and biota. Biogeochemical tracers can also track animal movement and their diet, monitor human coastal development, and evaluate the condition of habitats and species. However, the beneficial applications of spatial biogeochemical analysis are hindered by a limited understanding of how tracer distribution is affected by different land and ocean-based influences. To help address these knowledge gaps, we determined the spatial trends of three stable isotopes (δ13C-carbon, δ15N-nitrogen, δ34S-sulfur) and 13 major and trace elements in an urbanized coastal embayment (Moreton Bay, Australia), as incorporated into the muscle tissue of a marine consumer, the eastern king prawn Melicertus plebejus. Results were used to identify unique biochemical regions within the bay and to discuss how spatial patterns in tracers could be used to indicate the relative importance of catchment, urban and offshore drivers in coastal bays. Discriminant analysis identified seven biogeochemical regions that were likely distinguished by variation in catchment, urban, and offshore input, and habitat type. δ13C and δ15N patterns suggested nearshore areas could be distinguished by increased sediment resuspension and higher wastewater inputs from catchments. High inshore lead (Pb) and copper (Cu) concentrations were likely the result of urban input. Arsenic (As) and cadmium (Cd) increased further from shore. This trend implied oceanic influences were a significant control over As and Cd bioavailability. Cobalt (Co) and rare earths were also used to differentiate some nearshore areas, but incongruent distribution patterns in Co suggested it may be less reliable. Overall, results indicated that δ15N, δ13C, Cd, Cu, Pb and rare earth elements were the most reliable tracers to differentiate nearshore and offshore environments, and catchment-based effects. We encourage future studies to consider using a similar multivariate approach in coastal spatial analysis, and to include unrelated tracers that reflect distinct coastal influences.

Spatial attachment-site preferences of macroectoparasites on Atlantic sturgeons Acipenser oxyrinchus in Minas Basin, Bay of Fundy, Canada.

Although parasite habitat preference is well studied, it is rarely rigorously evaluated statistically because of many zero intensities. Attachment-site preference and intensities of 2 macroectoparasite species ( Caligus elongatus and Calliobdella vivida ) of Atlantic sturgeon, Acipenser oxyrinchus Mitchill, in Minas Basin, Bay of Fundy, Canada, were characterized with the use of zero-inflated negative binomial statistical models that included a fork-length offset to control for body size. Three other parasites were encountered, sometimes in high numbers on various body sites, but too few counts overall prevented construction of meaningful statistical models. Of 26 sturgeons, prevalence of (1) C. elongatus (Copepoda) was 85%, mainly on caudal fins and nonfin body sites; (2) C. vivida (Hirudinea) was 81%, mainly on the pelvic and pectoral fins, and dorsal and ventral-lateral body sites; (3) Dichelesthium oblongum (Copepoda) was 31% within the gills or burrowed into the musculature at the base of fins; (4) Argulus stizostethii (Crustacea: Branchiura) was 8%; and (5) Nitzschia sturionis (Monogenea) was 12%. Only D. oblongum was associated with visible damage, mainly as lesions on gills and soft tissues. Characterizing parasite prevalences within the Bay of Fundy is important because some parasites affect fish health and population biology.