How do you measure ecosystem resilience in the face of climate change?

I. Define indicators: Identify specific indicators reflecting ecosystem health. II. Collect data: Gather data on indicators using surveys, remote sensing, and modeling. III. Analyze trends: Assess changes in indicators due to climate change stressors. IV. Calculate resilience metrics: Quantify resilience using metrics like resistance and recovery time. V. Interpret results: Understand ecosystem state, identify vulnerabilities, and inform management strategies.

The concept of ecological or ecosystem integrity is one that has been gaining traction in the past few years, and can be defined as the composition, structure and function (i.e., its ability to provide ecosystem services). In short, an ecosystem with high integrity is one that is in a good state, with vibrant ecology that provides all it's ecosystem services to a high standard. In effect, a high-integrity ecosystem is also likely to be more resilient to climate change. Using this concept, you can look at indicators associated with composition (e.g., species abundance), structure (e.g., connectivity), and function (e.g., flood prevention) to assess resilience.

Some indicators: key species, basic niches filled, ecossystems manages the energy on it in a dynamics equilibrium, high liquid production, medium restore area.

The biggest failure in ecological monitoring is too narrow a focus on the data that is collected. There are many indicators and many interactions that will impose themselves on those indicators at many scales in the landscape (i.e., micro, macro, local, regional, global). Consult widely with the literature and peers before designing your monitoring program. Be prepared to alter, modify, change your design throughout the life of the monitoring based on the data you collect. Always keep the understanding that the science has not caught up with the complexity and dynamic nature of systems being studied, that is why they are being studied. Do not fall into the trap that monitoring will result in absolute statements - change is inevitable.

Ecological indicators such as biodiversity indicators including species richness, evenness and population trends are useful to find out the number of different species present in an ecosystem, the distribution of individual species and changes in the population sizes of key species over time respectively. For instance, Bird Population Indices evaluate the trends in bird populations as indicators of habitat quality and environmental changes.

Case study: monitoring the restoration of a mangrove to combat rising sea levels through natural sediment accretion. Can the mangrove accrete sediment at a faster rate than the sea level can rise to protect a coastline? In this scenario, you would use the following indicators: - annual rate of sediment accretion - annual rate of sea level rise - ecosystem condition (composition, structure and function) to indicate whether the habitat is likely to survive or is subject to degradation

Resilience indicators will emerge from your data. You may have an idea of what they could be, just don't be surprised if they are not that useful, and be surprised if you were spot on.

Concordo com a importância dos indicadores de resiliência como parte dos indicadores ecológicos. Eles são essenciais para entender como os ecossistemas lidam com distúrbios climáticos. Classificados em resistência, recuperação e capacidade adaptativa, esses indicadores mostram a habilidade dos ecossistemas em resistir a perturbações, se recuperar rapidamente ou se adaptar a novas condições. O uso de inteligência artificial e imagens de satélite é crucial para coletar e analisar esses dados, oferecendo uma visão detalhada e em tempo real das respostas dos ecossistemas às mudanças climáticas.

Rising threats (extreme climatic events, disease & pests outbreaks, etc.) make preserving resilient ecosystems a priority (e.g. K-M Global Biodiversity Framework GoalA, Target3, Decision15/4). Yet research into what makes a terrestrial ecosystem resilient is complex: a wide range of abiotic and biotic attributes have been proposed. IPBES (2019) describes ecosystem resilience in two ways: - Capacity to bounce back: "capacity of a socio-ecological system to absorb or withstand perturbations and other stressors such that the system remains within the same regime, essentially maintaining its structure and functions." - Adaptive resilience: an ecosystem’s capacity to adapt to change without dramatic shifts in its structure and functioning.

Biodiversity Assessment: Species Diversity: Evaluate the diversity and composition of species within an ecosystem. A resilient ecosystem often has a higher species diversity, which can enhance its ability to adapt to changes.

Indeed, resilience assessment frameworks are essential tools for environmental monitoring experts to gauge the resilience of ecosystems and communities in the face of various stressors and disturbances. These frameworks provide a structured approach for selecting appropriate indicators, measuring resilience, and interpreting the results in a consistent manner. Developed by the Resilience Alliance, this workbook offers a comprehensive guide for assessing the resilience of social-ecological systems. It emphasizes the importance of understanding the dynamics, interactions, and feedbacks within systems, and provides practical tools and methods for resilience assessment.

After all of them the ecossystem must be in a climax level and have enough species to fill it's basic niches to keep alive normally.

When collecting data, always start with Secondary datasets: - Search online for open source data e.g., bio data sets, old maps to indicate restoration possibilities, soil maps etc. - Contact relevant NGOs, Gov Agencies etc., to find what existing data is available that can be reviewed. - Use this data to help you determine what may be present within your site and understand what may be best to collect for primary data. Primary data: - Design your primary data collection based on the knowledge you have at hand. - Where possible, ensure quantitative data is collected, as qualitative can only tell you so much. - Design your primary data collection with long-term monitoring in mind. Can this be used as an effective baseline starting point?

To do monitoring over time and among sites, the first crucial step is to ensure that that the data actually are comparable. Hence, either apply already established guidelines or make sure that you design your monitoring to be relevant for the purpose as well as for others to adopt later. A mayor obstacle to monitoring extensive in time or space is funding. Longterm monitoring programs are not always found attractive for short term funding as the results are often predicted in the longer time frame. Likewise, a randomised spatial monitoring face similar, as confounders are more challenging to control. However, if standardised and harmonised monitoring schemes are applied, this allows combing results for a broader systematic understanding.

Remote Sensing and GIS: Land Cover Changes: Use remote sensing and Geographic Information Systems (GIS) to monitor land cover changes over time. Changes in land cover can provide insights into ecosystem health and potential stressors.

Your explanation provides a comprehensive overview of data collection methods used by environmental monitoring experts to gather information on resilience indicators. Employing a combination of primary and secondary, quantitative and qualitative, as well as direct and indirect data collection methods, environmental monitoring experts can gather comprehensive and robust information to assess resilience indicators effectively.

Dados secundários são uma fonte valiosa para análises ambientais. Além de economizar tempo e recursos, esses dados podem oferecer uma perspectiva histórica, permitindo a avaliação de mudanças e tendências ao longo do tempo. Utilizar esse tipo de dados facilita a identificação de padrões, a medição da eficácia de intervenções e a compreensão da evolução dos ecossistemas, apoiando uma gestão ambiental mais informada e adaptativa.

Data analysis is dependent on the robustness of the data, the manner in which it has been collected, and ultimately, the questions that are being asked. Do not fall for the lure of some novel rock-star analysis just because others use it (but usually cannot explain it or why they use it). Always start from the simplest analyses of the data and let it tell you what it can (as simple as means, averages, creating charts). Always think hard about the systems you are studying. Not all will fall neatly into parametric methods, nor will frequentist statistics be the most appropriate means of seeking answers.

A qualidade da análise de dados está intimamente ligada a um bom desenho amostral. Sem uma amostragem bem planejada, a base de dados pode ser enviesada e inadequada, comprometendo a validade e a precisão das análises e, consequentemente, colocando o trabalho em risco. Um desenho amostral robusto garante que os dados coletados sejam representativos e relevantes, permitindo análises mais precisas e confiáveis. Para tomar decisões assertivas, é essencial ter uma base de dados sólida que suporte análises de qualidade.

If you are monitoring, you are likely to have had scientific training. Put the scientific method and the scientific ethos front and center into everything you do - no short-cuts. Monitoring can get very tedious very quickly. You end up doing the same thing, in the same place, at the same time over and over again. That repetitiveness can breed complacency, but good monitoring relies on good data. My final word is that you will never know everything and you can never expect to know everything. Treat monitoring as an intimate journey learning the very minutia of details about your subject. There will always be something different to experience and always something worth learning.

Reporting and communication methods in environmental monitoring convey resilience assessments to stakeholders through various channels. Written methods include detailed reports, academic papers, informative articles, and newsletters. Oral methods involve presentations, speeches, webinars, and podcasts. Formal methods follow established standards, using technical language and providing comprehensive data. These approaches ensure clear, accurate communication, tailored to both technical and non-technical audiences.