1. Conservation and ecology research and practice is most effective when theory and models that underly species management are well explored and understood in experimental systems. Microcosm studies can provide experimental evidence to support theory, test model performance in different conditions, and suggest generality. However these benefits have been limited to primarily extinction and population studies, while habitat models have largely remained unexplored in newer systems. 2. There is presently lacking an experimental system that uses benchtop temperature and food manipulation combined with automated, in situ non-destructive sampling – necessary for conducting habitat and spatial structure studies in microcosms. 3. We developed Climate, Resource, and Image Tracking in Tiny, Ecologically Representative Systems (CRITTERS), an experimental microcosm system that manipulates habitat through abiotic temperature and biotic components (resources) in a benchtop design, and automates data collection through in situ observations. We propose it as a system in which to test a variety of models and theories in conservation and ecology. 4. We present the counting accuracy of CRITTERS and population responses of Paramecium caudatum to the temperature and resource availability. Using a modified version of the software Wellcounter, the correlation between automated and manual counts was r = 0.98. In logistic models, P. caudatum growth rate r responded to temperature quadratically, and carrying capacity K responded to resources (concentration of carbon in media) log-linearly, allowing independent control of r and K. 5. This system can be used to test a variety of habitat models in which climate and/or resources require manipulation when in situ sampling and high replication is important. We describe potential uses for testing adaptive management strategies, occupancy and N-mixture models, and Species Distribution Models.

Spatial patterns of sessile organisms, such as plants, reflect past processes and affect future changes. We introduce a spatial birth-death process with birth/death rates that explicitly depend on distances to other points. These demographic rates are defined to represent the combined effect of the ecological mechanisms that affect individual organisms. We show that the constructed spatio-temporal process converges exponentially fast to a saturated pairwise interaction Gibbs point process. This allows for statistical inference through an analysis of either the locations where births/deaths occur, or (assuming stationarity) of the sequence of recorded spatial patterns. A simulation study demonstrates that either of these inference techniques recovers the parameters of the spatial birth-death process with relatively few temporal observations. We then applied our model to 20 forest plots in northern Queensland, Australia, which were censused a dozen times. We find that births are more likely around conspecifics, and that this may explain the species' clustered spatial patterns. This work unifies two distinct streams of research and provides a route to inference and prediction of evolving spatial structures in communities from ecological mechanisms that influence demographic rates.

ABSTRACT Ecological data are increasingly collected by networks of collaborators using replicated designs and methods, which can significantly improve the quality and quantity of data throughout the ecological niche and geographic range of species or communities. The coordinated generation and management of data is critical for producing datasets (Standard Data Products) across multiple sites that can be used by different researchers, over extended time periods and for multiple purposes. We describe and use a Quality Assurance framework for the design, collection and production of reproducible Standard Data Products for distributed ecology projects. We identified six critical project elements of a Quality Assurance framework (QA1‐6) to produce ecological Standard Data Products with high immediate and future value. We applied the Quality Assurance framework to the Plantpopnet project as a case‐study. Plantpopnet is a coordinated distributed system for population macroecology using the model species Plantago lanceolata. We mapped Plantpopnet activities to the Quality Assurance Framework as follows: (QA1) Measurable objectives: research project objectives with data requirements, (QA2) Process control: governance policies, (QA3) Project specific procedures: model organism selection and data collection protocol, (QA4) Supporting production of high quality data: recruitment, retention and engagement of participants, (QA5) Data management: data management plan and reproducible data cleaning workflow, (QA6) Production and management of outputs: Standard Data Products and papers. Explicit use of Quality Assurance, project and data management tools together with standardised ecological methods facilitated the design, collection, maintenance and sustainability of high‐quality data products. We provide a Quality Assurance framework together with governance documents, code and data for a reproducible Standard Data Product. This framework supports a distributed funding model which can be sustainably applied to facilitate future research and applications of coordinated distributed ecology projects.

Plant functional traits are quantifiable elements of ecological strategies. Studying them can thus offer insights into the ecological and evolutionary processes shaping natural plant communities. Despite evidence that leaf and root traits may coordinate or diverge at the species level, community-level root traits and strategies are often assumed to mirror those of aboveground traits in natural communities. Thus, belowground functional traits and their influence on community responses to environmental variation remain less well understood than their aboveground counterparts. This study addresses this knowledge gap by evaluating community above- and belowground resource-use strategies along biotic and abiotic environmental gradients in a diverse semi-arid annual plant system. Using specific leaf area (SLA) and specific root length (SRL) as comparable above- and belowground traits, we anticipated that plant communities would shift towards acquisitive strategies in both leaf and root trait values in resource-rich environments with mild climate conditions, aligning with the fast-slow plant economic spectrum. Our results show that community-level SLA and SRL align with the fast-slow economic spectrum along gradients of temperature, precipitation and canopy cover. Yet, community-level above- and belowground resource-use strategies are governed by different environmental factors. We found that maximum temperature most strongly predicted SLA, while precipitation was the strongest predictor of SRL at the community level. Above- and belowground community traits varied in their response direction and magnitude to the same environmental factors. While community-level SLA and SRL responded in a coordinated manner to remnant-level predictors, they diverged in response to micro-environmental variation. Our findings suggest that community-level above- and belowground traits reveal different but complementary community responses to the environment, highlighting the importance of incorporating root traits into ecological studies. Our results provide new insights into which plant traits are best suited to predicting annual plant community assembly under environmental change.

Identifying overarching processes that maintain biodiversity in natural communities remains a challenge in ecology. Although functional traits help explain regional species distributions, they often fall short at the local community level. We investigate whether traits can offer mechanism-based insights into local diversity maintenance due to associations with the sign and strength of plant interactions. We examine the effect of 12 plant functional traits on the sign and strength of pairwise species interactions across two Mediterranean annual plant communities. Results show that traits mediate a spectrum from facilitative to competitive interactions and are influenced by neighbor density and identity. At low densities, species with conservative resource-use traits are consistently stronger facilitators than acquisitive species. The traits of the focal species, however, explain facilitation at low densities better than the traits of neighbors or the pairwise differences in traits. When neighbor density increases, facilitation switches to competition, a pattern we hypothesize reflects a density-mediated reduction in how much neighbors' traits drive interactions. Moreover, species frequently receiving heterospecific facilitation also display traits associated with self-competition and low intrinsic population growth rate. This study of community-level trait sorting provides insights into the persistence of co-occurring populations, showing trait-based generalizable insights into the local context dependency of species interactions.

ABSTRACTWith many species interacting in nature, determining which interactions describe community dynamics is nontrivial. By applying a computational modeling approach to an extensive field survey, we assessed the importance of interactions from plants (both inter‐ and intra‐specific), pollinators and insect herbivores on plant performance (i.e., viable seed production). We compared the inclusion of interaction effects as aggregate guild‐level terms versus terms specific to taxonomic groups. We found that a continuum from positive to negative interactions, containing mostly guild‐level effects and a few strong taxonomic‐specific effects, was sufficient to describe plant performance. While interactions with herbivores and intraspecific plants varied from weakly negative to weakly positive, heterospecific plants mainly promoted competition and pollinators facilitated plants. The consistency of these empirical findings over 3 years suggests that including the guild‐level effects and a few taxonomic‐specific groups rather than all pairwise and high‐order interactions, can be sufficient for accurately describing species variation in plant performance across natural communities.

Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Microcosms, or miniature experimental systems, have been used to develop models and theories in ecology. However, their contribution to conservation science is unclear. We explored the application, design, and impact of microcosms in conservation science from 469 systematically identified articles published from 1986 to 2023. We used generalized linear modeling to compare cumulative citations over time for each microcosm article with those of 71,738 nonmicrocosm articles in conservation science. We also surveyed the proportion of microcosm articles and nonmicrocosm articles focused on conservation science that were cited in policy documents. Two types of microcosms were used in conservation research: generalized microcosms (i.e., simplified analogies of systems used to test general theories and mathematical models) and specialized microcosms (i.e., recreations of specific ecosystems or species assemblages that test specific hypotheses). Microcosms were used to study biodiversity, invasive species, extinction, pollution, and climate change and were applied to a broad array of ecosystems and species. Microcosm experiments tended to be small (systems were liters in size or smaller) and conducted over short periods (weeks or months); could monitor study species for up to hundreds of generations; and had high sample replication. On average, microcosm studies were cited up to twice as often as nonmicrocosm studies 25 years after publication. Microcosm articles and nonmicrocosm articles focused on conservation science were cited in policy documents at similar rates to each other. We recommend that conservation science, which often focuses on urgent topics and rare or threatened ecosystems and species, may benefit from the manipulability and replicability that microcosms offer. Microcosm experiments may also be low risk for the study systems involved. Future uses of microcosms include providing experimental evidence and testing of conservation theories, models, and hypotheses.

1 Abstract Climate change is expected to bring about changes in precipitation and temperature regimes that, together with rising atmospheric CO 2 concentrations, will likely reorganise the functional trait composition of ecosystems. Predicting plant trait responses to emerging environmental conditions including, in particular, water availability, is a tremendous challenge, but is one that eco-evolutionary optimality theory (EEO) can help us undertake. However, most EEO approaches are based on the hypothesis that traits are selected to maximise carbon assimilation which omits the important role that size growth plays in determining fitness outcomes. Using a height-growth based EEO framework, we predict magnitude and directional shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to variation in soil moisture availability, atmospheric aridity, CO 2 and light availability. Consistent with empirical patterns, we predict that trait optima shift from resource-acquisitive strategies characterised by low tissue constructions costs and high rates of tissue turnover and sapwood conductivity to resource-conservative strategies - characterised by low rates of tissue turnover and greater xylem embolism resistance - as conditions become increasingly dry. The EEO model that we use here highlights the important role that both carbon assimilation and tissue construction costs jointly play in predicting the response of trait optima to the environment, laying the groundwork for future height-growth based EEO models aiming to predict shifts in the functional composition of ecosystems in response to global change.

Trees in private yards are subject to a complex assortment of interacting ecological, social, cultural and economic factors, including individual preferences, social networks, multiple stakeholders and social constraints. This study explored residents’ attitudes towards yard trees in China and determined the social factors shaping yard trees and yard tree planting. Nearly 300 questionnaires were collected in-person and online in urban and rural villages and communities in Zhoukou city, Henan. Most trees planted in yards were intentionally planted. Yard size was the main constraint on the number of trees in a yard with respondents repeatedly citing the lack of space as a deterrent to planting trees or planting more trees. The most popular attributes for trees planted in yards were symbolism and edibility. Residents’ attitudes were based upon tree functions. The willingness and attitudes of residents towards yard trees suggested that an increase in yard trees would be supported by residents, who appeared to be yearning for a green living environment. However, a lack of preference found for native species suggests a challenging future for native trees in yards in regard to their role in biodiversity and habitat formation. Men played the dominant role in activities associated with yard trees. Residents were keen to aid wider ambitions for greening through their own tree planting in yards, but need guidance via policies and incentives. Such moves at high levels of government will assist the achievement of sustainable development goals in the future China, such as increased city canopy and carbon targets.

Private residential yards are an important component of urban green space and a major contributor to the urban environment. Trees in private yards provide physical and psychological benefits, but little research has been done, for example, in China. This study examined the characteristics of 143 private residential yards and 955 yard trees across a range of villages and communities along a gradient from rural to peri-urban to urban in Zhoukou city, central China. Overall, 65

Future changes in climate, together with rising atmospheric CO 2 CO2 , may reorganise the functional composition of ecosystems. Without long-term historical data, predicting how traits will respond to environmental conditions-in particular, water availability-remains a challenge. While eco-evolutionary optimality theory (EEO) can provide insight into how plants adapt to their environment, EEO approaches to date have been formulated on the assumption that plants maximise carbon gain, which omits the important role of tissue construction and size in determining growth rates and fitness. Here, we show how an expanded optimisation framework, focussed on individual growth rate, enables us to explain shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to soil moisture, atmospheric aridity, CO 2 CO2 and light availability. In particular, we predict that as conditions become increasingly dry, height-growth optimising traits shift from resource-acquisitive strategies to resource-conservative strategies, consistent with empirical responses across current environmental gradients of rainfall. These findings can explain both the shift in traits and turnover of species along existing environmental gradients and changing future conditions and highlight the importance of both carbon assimilation and tissue construction in shaping the functional composition of vegetation across climates.

AimsEnvironmental managers require reliable and cost-efficient monitoring methods for effective decision-making. Understanding forage availability is important for managing wild, vertebrate herbivore populations. We developed a process for exploring the accuracy and cost efficiency of various biomass estimation techniques for a case study where semi-arid woodland restoration is threatened by kangaroo grazing, with the aim of determining which method was most fit for purpose in a given decision context.LocationWyperfeld National Park, southeastern Australia.MethodsGrass biomass was estimated using a variety of methods, then compared to clipped biomass using linear models. Biomass estimation methods were either field-based (i.e., rising plate meter, multispectral radiometer) or satellite-based (i.e., Landsat satellite imagery, AussieGRASS forage production model). Sampling occurred across open and wooded semi-arid vegetation types. We compared methods based on accuracy, the ability of each method to accurately predict a 'forage-switch' threshold, cost, and the suitability for the management context.ResultsFor this case study, the multispectral radiometer was the most precise, yet most expensive, biomass estimation method over a single survey. However, satellite imagery proved to be the most cost-efficient and fit for purpose, as it was inexpensive and most accurately estimated biomass around a forage-switch threshold, second only to the multispectral radiometer. Accuracy of all methods was improved by including tree cover in the regression models.ConclusionsWe demonstrate a process for exploring which biomass estimation tool might be preferred for a given decision context, highlighting accuracy, consideration of tolerance to uncertainty and risk, the spatial and temporal scale of information required, and budget constraints. We compared the performance, cost, and suitability of multiple field and satellite-based grass biomass estimation methods. We demonstrated a process for method selection for a case study of kangaroo management for semi-arid woodland restoration in south-eastern Australia. The choice of method will ultimately depend on accuracy, cost, the scale of information required, and managers' tolerance to uncertainty and risk.image

Traits with intuitive names, a clear scope and explicit description are essential for all trait databases. The lack of unified, comprehensive, and machine-readable plant trait definitions limits the utility of trait databases, including reanalysis of data from a single database, or analyses that integrate data across multiple databases. Both can only occur if researchers are confident the trait concepts are consistent within and across sources. Here we describe the AusTraits Plant Dictionary (APD), a new data source of terms that extends the trait definitions included in a recent trait database, AusTraits. The development process of the APD included three steps: review and formalisation of the scope of each trait and the accompanying trait description; addition of trait metadata; and publication in both human and machine-readable forms. Trait definitions include keywords, references, and links to related trait concepts in other databases, enabling integration of AusTraits with other sources. The APD will both improve the usability of AusTraits and foster the integration of trait data across global and regional plant trait databases.

The global decline in the extent and condition of ecological communities has resulted in an increasing demand for recovery and conservation plans. Conservation plans for ecological communities require a management framework with measurable, time-bound objectives, a targeted management strategy, and indicators that enable actions to be evaluated in relation to objectives. Methods that allow for the transfer of knowledge among similar systems and facilitate consistent and comparable plans are essential, especially when resources are constrained. We describe a process to streamline the development of conservation plans by combining functionally similar community sub-types into a multi-community State and Transition Model. We demonstrate this approach in a case study where we use the combined expertise of Australian ecologists to build a multi-community State and Transition Model for eucalypt woodlands of southern Australia – an ecosystem which occupies a vast geographical range across temperate Australia and includes many distinct vegetation communities, a growing number of which are endangered or threatened. We identify commonalities and differences among three broad woodland sub-types including a set of eight general condition states, a list of drivers of transitions among condition states, and the uncertainties and time-frames associated with each transition. Two key findings across all models are that management is state-dependent, and transition directly to the ‘Exemplar’ state from any other state is considered highly unlikely. Other examples of State and Transition Models in the literature are focused on single communities or a significantly smaller scale, and this is the first attempt to construct a nationally relevant multi-community State and Transition Model via a structured and consultative process. Based on this case study, we propose a repeatable protocol for developing multi-community State and Transition Models. This process could improve and streamline the development of robust conservation plans for threatened ecological communities more broadly.

The ultimate goal of threatened plant translocations is to establish self-sustaining populations. Lessons learnt from plant translocations can inform future translocations and improve conservation outcomes via adaptive management. We assessed translocation success for 76 translocations of 50 species established as part of recovery programmes between 1998 and 2016 in the Southwest Australian Floristic Region (SWAFR), a biodiversity hotspot with Mediterranean-type climate. We used a series of Bayesian hierarchical models to assess translocation success as measured by plant survival, height growth, crown growth, and reproduction (flowering and fruiting). We found that fencing to prevent vertebrate herbivory improved survival, irrigating plants over the first two summer dry periods improved the likelihood of reproduction, and where the rainfall increased above the 30-year average in the two years following planting, it positively influenced survival, growth, and reproduction. We recommend that fencing to prevent herbivory should be broadly considered in threatened plant translocations, while irrigation to improve translocation success would benefit plant species in Mediterranean-type ecosystems and other dryland environments.

As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predictions about the replicability of research. This process is a structured expert elicitation approach based on a modified Delphi technique applied to the evaluation of research claims in social and behavioural sciences. The utility of processes to predict replicability is their capacity to test scientific claims without the costs of full replication. Experimental data supports the validity of this process, with a validation study producing a classification accuracy of 84% and an Area Under the Curve of 0.94, meeting or exceeding the accuracy of other techniques used to predict replicability. The repliCATS process provides other benefits. It is highly scalable, able to be deployed for both rapid assessment of small numbers of claims, and assessment of high volumes of claims over an extended period through an online elicitation platform, having been used to assess 3000 research claims over an 18 month period. It is available to be implemented in a range of ways and we describe one such implementation. An important advantage of the repliCATS process is that it collects qualitative data that has the potential to provide insight in understanding the limits of generalizability of scientific claims. The primary limitation of the repliCATS process is its reliance on human-derived predictions with consequent costs in terms of participant fatigue although careful design can minimise these costs. The repliCATS process has potential applications in alternative peer review and in the allocation of effort for replication studies.

Context The radiation of eucalypts into almost every Australian environment offers valuable insights to plant ecological strategies. Aims We aimed to assess the degree to which functional traits across different organs are independent or reflect coordinated strategies in southern eucalypts. Methods We applied ordinary and phylogenetic generalised least squares regressions to 164 southern Australian taxa, examining the network of pairwise relationships between 10 functional traits representing aspects of stature, leaf economics, reproduction and post-fire regeneration. We examined coordination and modularity in this network and estimated how phylogeny affects observed trait correlations. Results Stem and stature traits were generally independent of reproductive traits, with Specific Leaf Area the most connected trait, being correlated with traits from all organs. Resprouting ability was also connected to several traits. Species able to resprout basally, but not epicormically, were on average shorter, stouter, with higher stem sapwood density, thinner bark, smaller leaves and lower Specific Leaf Area than those able to resprout using both methods. Taxa resembled their relatives; phylogenetic signal was significant for all continuous traits except Relative Height, ranging from Pagel’s Lambda λ = 0.37 (Relative Bark Thickness) to λ = 0.82 (Specific Leaf Area). Phylogenetic analyses showed weakened correlations for most (but not all) trait pairs. However, most moderate relationships on the trait correlation network also displayed correlated evolution. Conclusions Stature, stem, leaf and reproductive traits and fire response of eucalypts are somewhat coordinated, principally through leaf economics. Trait combinations that confer ecological competence on eucalypt taxa in present-day conditions are likely to have been similarly favoured throughout their evolutionary history. Implications This supports theory of coordinated plant strategies.