Hotspots of biogeochemical activity linked to aridity and plant traits across global drylands.

Perennial plants create productive and biodiverse hotspots, known as fertile islands, beneath their canopies. These hotspots largely determine the structure and functioning of drylands worldwide. Despite their ubiquity, the factors controlling fertile islands under conditions of contrasting grazing by livestock, the most prevalent land use in drylands, remain virtually unknown. Here we evaluated the relative importance of grazing pressure and herbivore type, climate and plant functional traits on 24 soil physical and chemical attributes that represent proxies of key ecosystem services related to decomposition, soil fertility, and soil and water conservation. To do this, we conducted a standardized global survey of 288 plots at 88 sites in 25 countries worldwide. We show that aridity and plant traits are the major factors associated with the magnitude of plant effects on fertile islands in grazed drylands worldwide. Grazing pressure had little influence on the capacity of plants to support fertile islands. Taller and wider shrubs and grasses supported stronger island effects. Stable and functional soils tended to be linked to species-rich sites with taller plants. Together, our findings dispel the notion that grazing pressure or herbivore type are linked to the formation or intensification of fertile islands in drylands. Rather, our study suggests that changes in aridity, and processes that alter island identity and therefore plant traits, will have marked effects on how perennial plants support and maintain the functioning of drylands in a more arid and grazed world.

The importance of expert selection when identifying threatened ecosystems.

Identifying threatened ecosystem types is fundamental to conservation and management decision-making. When identification relies on expert judgment, decisions are vulnerable to inconsistent outcomes and can lack transparency. We elicited judgements of the occurrence of a widespread, critically endangered Australian ecosystem from a diverse pool of 83 experts. We asked 4 questions. First, how many experts are required to reliably conclude that the ecosystem is present? Second, how many experts are required to build a reliable model for predicting ecosystem presence? Third, given expert selection can narrow the range opinions, if enough experts are selected, do selection strategies affect model predictions? Finally, does a diverse selection of experts provide better model predictions? We used power and sample size calculations with a finite population of 200 experts to calculate the number of experts required to reliably assess ecosystem presence in a theoretical scenario. We then used boosted regression trees to model expert elicitation of 122 plots based on real-world data. For a reliable consensus (90% probability of correctly identifying presence and absence) in a relatively certain scenario (85% probability of occurrence), at least 17 experts were required. More experts were required when occurrence was less certain, and fewer were needed if permissible error rates were relaxed. In comparison, only ∼20 experts were required for a reliable model that could predict for a range of scenarios. Expert selection strategies changed modeled outcomes, often overpredicting presence and underestimating uncertainty. However, smaller but diverse pools of experts produced outcomes similar to a model built from all contributing experts. Combining elicited judgements from a diverse pool of experts in a model-based decision support tool provided an efficient aggregation of a broad range of expertise. Such models can improve the transparency and consistency of conservation and management decision-making, especially when ecosystems are defined based on complex criteria.

La importancia de seleccionar expertos para identificar ecosistemas amenazados Resumen La identificación de los tipos de ecosistemas amenazados es fundamental para decidir sobre su conservación y gestión. Cuando la identificación se basa en la opinión de expertos, las decisiones son vulnerables a resultados incoherentes y pueden carecer de transparencia. Recabamos la opinión de 83 expertos sobre la presencia de un ecosistema australiano extendido y en peligro crítico. Se plantearon cuatro preguntas: ¿Cuántos expertos son necesarios para concluir con fiabilidad que el ecosistema está presente?; ¿Cuántos expertos son necesarios para construir un modelo fiable de predicción de la presencia del ecosistema?; ya que la selección de expertos puede reducir el rango de opiniones, si se seleccionan suficientes expertos, ¿afectan las estrategias de selección a las predicciones del modelo; y ¿Una selección diversa de expertos proporciona mejores predicciones del modelo? Utilizamos cálculos de potencia y tamaño de muestra con una población finita de 200 expertos para obtener el número de expertos necesarios para evaluar de forma fiable la presencia de ecosistemas en un escenario teórico. Después usamos árboles de regresión reforzada para modelar la consulta de expertos de 122 parcelas basadas en datos del mundo real. Para obtener un consenso fiable (90% de probabilidad de identificar correctamente la presencia y la ausencia) en un escenario relativamente seguro (85% de probabilidad de ocurrencia), se necesitaban al menos 17 expertos. Se necesitaban más expertos cuando la ocurrencia era menos segura, y menos si se relajaban los porcentajes de error permitidos. En comparación, sólo se necesitaron unos 20 expertos para obtener un modelo fiable que pudiera predecir una serie de escenarios. Las estrategias de selección de expertos modificaron los resultados modelados, a menudo con sobre predicción de la presencia y subestimación de la incertidumbre. Sin embargo, los grupos de expertos más pequeños pero diversos produjeron resultados similares a los de un modelo construido a partir de todos los expertos participantes. La combinación de las opiniones obtenidas de un grupo diverso de expertos en una herramienta de apoyo a la toma de decisiones basada en un modelo proporcionó una agregación eficiente de una amplia gama de conocimientos. Estos modelos pueden mejorar la transparencia y coherencia de la toma de decisiones en materia de conservación y gestión, especialmente cuando los ecosistemas se definen en función de criterios complejos.

Reference state and benchmark concepts for better biodiversity conservation in contemporary ecosystems.

Measuring the status and trends of biodiversity is critical for making informed decisions about the conservation, management or restoration of species, habitats and ecosystems. Defining the reference state against which status and change are measured is essential. Typically, reference states describe historical conditions, yet historical conditions are challenging to quantify, may be difficult to falsify, and may no longer be an attainable target in a contemporary ecosystem. We have constructed a conceptual framework to help inform thinking and discussion around the philosophical underpinnings of reference states and guide their application. We characterize currently recognized historical reference states and describe them as Pre-Human, Indigenous Cultural, Pre-Intensification and Hybrid-Historical. We extend the conceptual framework to include contemporary reference states as an alternative theoretical perspective. The contemporary reference state framework is a major conceptual shift that focuses on current ecological patterns and identifies areas with higher biodiversity values relative to other locations within the same ecosystem, regardless of the disturbance history. We acknowledge that past processes play an essential role in driving contemporary patterns of diversity. The specific context for which we design the contemporary conceptual frame is underpinned by an overarching goal-to maximize biodiversity conservation and restoration outcomes in existing ecosystems. The contemporary reference state framework can account for the inherent differences in the diversity of biodiversity values (e.g. native species richness, habitat complexity) across spatial scales, communities and ecosystems. In contrast to historical reference states, contemporary references states are measurable and falsifiable. This 'road map of reference states' offers perspective needed to define and assess the status and trends in biodiversity and habitats. We demonstrate the contemporary reference state concept with an example from south-eastern Australia. Our framework provides a tractable way for policy-makers and practitioners to navigate biodiversity assessments to maximize conservation and restoration outcomes in contemporary ecosystems.

Modeling biodiversity benchmarks in variable environments.

Effective environmental assessment and management requires quantifiable biodiversity targets. Biodiversity benchmarks define these targets by focusing on specific biodiversity metrics, such as species richness. However, setting fixed targets can be challenging because many biodiversity metrics are highly variable, both spatially and temporally. We present a multivariate, hierarchical Bayesian method to estimate biodiversity benchmarks based on the species richness and cover of native terrestrial vegetation growth forms. This approach uses existing data to quantify the empirical distributions of species richness and cover within growth forms, and we use the upper quantiles of these distributions to estimate contemporary, "best-on-offer" biodiversity benchmarks. Importantly, we allow benchmarks to differ among vegetation types, regions, and seasons, and with changes in recent rainfall. We apply our method to data collected over 30 yr at ~35,000 floristic plots in southeastern Australia. Our estimated benchmarks were broadly consistent with existing expert-elicited benchmarks, available for a small subset of vegetation types. However, in comparison with expert-elicited benchmarks, our data-driven approach is transparent, repeatable, and updatable; accommodates important spatial and temporal variation; aligns modeled benchmarks directly with field data and the concept of best-on-offer benchmarks; and, where many benchmarks are required, is likely to be more efficient. Our approach is general and could be used broadly to estimate biodiversity targets from existing data in highly variable environments, which is especially relevant given rapid changes in global environmental conditions.

Expert predictions of changes in vegetation condition reveal perceived risks in biodiversity offsetting.

Biodiversity offsetting typically involves the trade of certain losses of habitat with uncertain future conservation benefits. Predicting the latter requires estimates of two outcomes; the biodiversity losses without conservation management (averted loss), and the biodiversity gains with conservation management (management gain). However, because empirical data to inform these estimates are limited, they are normally guided by expert opinion, often derived via unstructured methods without consideration of uncertainty. Here we used a structured elicitation with 29 experts to gather estimates of averted loss and management gain at offset sites. We used two methods; (i) experts estimated change in an aggregate biodiversity value (vegetation condition) and; (ii) experts provided probabilistic estimates of change for individual vegetation condition attributes, such as the richness and cover of plant growth forms. On average, experts predicted there would be only modest improvements with conservation management, yet uncertainty and variation among experts was large; in some cases, conservation benefits were not predicted. Estimates of change in vegetation condition suggested that benefits were from both averted loss and management gains and were thought to most likely arise in cases where starting condition was low to moderate. Similar patterns were observed for individual vegetation condition attributes, with management gains, relative to a reference, tending to be negatively correlated with starting value. Our study finds that: (i) on average, gains at offset sites are expected to be small, (ii) at many sites, experts do not believe gains can be obtained, and (iii) experts' opinions can be divergent resulting in elevated levels of uncertainty. The potential for losses under conservation management highlights the need to: identify those components of biodiversity most likely to benefit from conservation management; better understand those situations when offset obligations are most likely to be met and conversely those situations with higher risk; and further develop offset mechanisms that encourage early or prior gains. These findings together with the global proliferation of biodiversity offsetting, provide a strong imperative to improve empirical data and investment in long-term, site-based monitoring of biodiversity outcomes at offset sites.

Change in dominance determines herbivore effects on plant biodiversity.

Herbivores alter plant biodiversity (species richness) in many of the world's ecosystems, but the magnitude and the direction of herbivore effects on biodiversity vary widely within and among ecosystems. One current theory predicts that herbivores enhance plant biodiversity at high productivity but have the opposite effect at low productivity. Yet, empirical support for the importance of site productivity as a mediator of these herbivore impacts is equivocal. Here, we synthesize data from 252 large-herbivore exclusion studies, spanning a 20-fold range in site productivity, to test an alternative hypothesis-that herbivore-induced changes in the competitive environment determine the response of plant biodiversity to herbivory irrespective of productivity. Under this hypothesis, when herbivores reduce the abundance (biomass, cover) of dominant species (for example, because the dominant plant is palatable), additional resources become available to support new species, thereby increasing biodiversity. By contrast, if herbivores promote high dominance by increasing the abundance of herbivory-resistant, unpalatable species, then resource availability for other species decreases reducing biodiversity. We show that herbivore-induced change in dominance, independent of site productivity or precipitation (a proxy for productivity), is the best predictor of herbivore effects on biodiversity in grassland and savannah sites. Given that most herbaceous ecosystems are dominated by one or a few species, altering the competitive environment via herbivores or by other means may be an effective strategy for conserving biodiversity in grasslands and savannahs globally.