Wednesday, March 06, 2024

 

Enhancing statistical reliability of weather forecasts with machine learning


Peer-Reviewed Publication

INSTITUTE OF ATMOSPHERIC PHYSICS, CHINESE ACADEMY OF SCIENCES

Connecting solar radiation to solar power 

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THE REVIEW PAPER FEATURED ON THE COVER OF THE 8TH ISSUE OF ADVANCES IN ATMOSPHERIC SCIENCES IN 2024 AIMS TO ASSIST READERS IN THE FIELD OF ATMOSPHERIC SCIENCES IN GAINING A THOROUGH UNDERSTANDING OF SOLAR POWER CURVE MODELING AND STAYING UPDATED ON RELEVANT RESEARCH ADVANCEMENTS.

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CREDIT: ADVANCES IN ATMOSPHERIC SCIENCES




A global team of researchers has made strides in refining weather forecasting methods, with a specific focus on addressing the persistent issue of "quantile crossing."  This phenomenon disrupts the order of predicted values in weather forecasts and arises from the numerical weather prediction (NWP) process—a two-step forecasting method involving observations and atmospheric evolution laws.

Despite NWP advancements, models still yield biased and under-scattered forecasts. To mitigate this, past attempts explored nonparametric methods like quantile regression neural networks (QRNN) and their variants, designed to output quantiles reflecting value ranks in the forecast distribution. However, these methods often face "quantile crossing," hindering forecast interpretation.

Ad hoc solutions, like naive sorting, didn't address the core issue. Enter the team's breakthrough: the non-crossing quantile regression neural network (NCQRNN) model.

This innovation, developed by Professor Dazhi Yang and his co-workers from the Harbin Institute of Technology, Karlsruhe Institute of Technology, Chinese Academy of Sciences, National University of Singapore, UK Power Networks, China Meteorological Administration, Heilongjiang Meteorological Bureau, and Budapest University of Technology and Economics, tweaks the traditional QRNN structure.  The NCQRNN model modifies the structure of the traditional QRNN by adding a new layer that preserves the rank order of output nodes, such that the lower quantiles are constrained to be perpetually smaller than higher ones without losing accuracy.

Their findings are published in Advances in Atmospheric Sciences.

Professor Yang emphasizes, "Our NCQRNN model maintains the natural order of forecast values, ensuring lower quantiles stay smaller than higher ones. This boosts accuracy and significantly improves forecast interpretability."

Dr. Martin J. Mayer from the Budapest University of Technology and Economics adds, "The idea is simple but effective: The neural network indirectly learns the differences between the quantiles as intermediate variables and uses these non-negative values in an additive way for estimating the quantiles, inherently guaranteeing their increasing order. Moreover, this non-crossing layer can be added to a wide range of different neural network structures, ensuring the wide applicability of the proposed technique."

Indeed, successfully applied to solar irradiance forecasts, this innovative machine learning approach showcased substantial improvements over existing models. Its adaptable design allows seamless integration into various weather forecasting systems, promising clearer and more reliable predictions for a range of weather variables.

Dr. Sebastian Lerch from the Karlsruhe Institute of Technology commented, "The proposed neural network model for quantile regression is very general and can be applied to other target variables with minimal adaptations. Therefore, the method will also be of interest for other weather and climate applications beyond solar irradiance forecasting."

Dr. Xiang'ao Xia from the Institute of Atmospheric Physics at the Chinese Academy of Sciences concludes, "Machine learning has important application prospects in the field of weather and climate research. This study provides an instructive case study on how to apply advanced machine learning methods to numerical weather prediction models to improve the accuracy of weather forecasts and climate predictions."

The international research team comprises individuals with diverse backgrounds, spanning atmospheric sciences, solar energy, computational statistics, engineering, and data sciences. Notably, certain team members involved in this study have collaborated on a review paper elucidating fundamental concepts and recent advancements in solar power curves. Published on March 1 and featured on the cover of the 8th issue of Advances in Atmospheric Sciences, this review paper not only establishes a robust understanding of solar power curve modeling principles but also functions as a bridgehead for atmospheric scientists, connecting their knowledge on radiation to the practical utilization of solar power.

 

Scientists sort out uncertainties in sea level projections


Peer-Reviewed Publication

INSTITUTE OF ATMOSPHERIC PHYSICS, CHINESE ACADEMY OF SCIENCES





As global temperatures continue to rise, coastal communities are confronted with the pressing challenge of surging sea levels. The urgency to provide decision-makers with reliable forecasts of future sea levels becomes increasingly critical. At the forefront of this predictive effort lies Dynamic Sea Level (DSL), a nuanced variable intricately linked to seawater density and ocean circulation, currently under intensive scrutiny in climate models.

The Ocean Modeling Team at the Institute of Atmospheric Physics, Chinese Academy of Sciences, recently conducted an extensive study, unraveling the uncertainties surrounding DSL projections using the cutting-edge Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble and the expansive FGOALS-g3 super-large ensemble.

Their study reveals that concerning basin-scale dynamics, intermodel uncertainty plays a leading role, contributing over 55%, 80%, and 70% to the total uncertainty of DSL projections in the near term (2021-2040), midterm (2041-2060), and long term (2081-2100), respectively. Following closely is internal variability, accounting for 10-42% in the near term and less than 20% in the midterm. While the impact of scenario uncertainty is initially minimal, it gradually ascends, surpassing contributions from internal variability in the long term.

Professor Hailong Liu, the corresponding author of the series of recently published studies, emphasized, “There are also regional nuances. At the regional scale, internal variability dominates in the near term for the Pacific Ocean, Indian Ocean, and the western boundary of the Atlantic Ocean. Conversely, intermodel uncertainty takes the spotlight in other regions. Contributions evolve over time, with scenario uncertainty becoming significant in the Southern, Pacific, and Atlantic Oceans in the long term.”

The research team also observed that anthropogenic DSL signals are expected to emerge from specific regions by the close of this century. The refinement of the CMIP6 ensemble, achieved by eliminating model differences, enhances our ability to detect these signals in advance.

“Imagine trying to understand Earth's climate using a computer model. Instead of running the model just once, we run it many times with slight variations in the starting conditions. This helps us see how the model responds to different situations,” explained Prof. Liu. “By doing this, we can better measure how the Earth's climate reacts to external factors, like changes in greenhouse gases, and also understand the natural ups and downs that happen on their own. This way, we get a clearer and more reliable picture of how our climate works.”

The team, therefore, gains insights from the FGOALS-g3 Super-Large Ensemble, featuring 110 model members, aligning seamlessly with CMIP6 members in basin-mean DSL projections. A comparative analysis with the CMIP6 ensemble reveals larger estimates of internal variability in the FGOALS-g3 super-large ensemble.

So, what are the implications for tomorrow? The team’s research not only deepens our comprehension of rising sea levels but also lays the groundwork for more accurate and informed climate models. The insights gleaned are instrumental in securing the future of our coastal communities.

These findings have recently been published in the Journal of ClimateAdvances in Atmospheric Sciences, and Geoscience Letters.

 

RISEnergy: Pushing innovations for climate neutrality


KIT-coordinated EU project aims to push and interconnect renewable energy technologies


Business Announcement

KARLSRUHER INSTITUT FÜR TECHNOLOGIE (KIT)

Research into the production of climate-neutral fuels at the Energy Lab, Europe’s largest research infrastructure for the use of renewable energy sources at KIT will also become part of the RISEnergy ecosystem. (Photo: Amadeus Bramsiepe, KIT) 

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RESEARCH INTO THE PRODUCTION OF CLIMATE-NEUTRAL FUELS AT THE ENERGY LAB, EUROPE’S LARGEST RESEARCH INFRASTRUCTURE FOR THE USE OF RENEWABLE ENERGY SOURCES AT KIT WILL ALSO BECOME PART OF THE RISENERGY ECOSYSTEM. (PHOTO: AMADEUS BRAMSIEPE, KIT)

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CREDIT: AMADEUS BRAMSIEPE




“RISEnergy will create  a European ecosystem covering all areas of renewable energy technologies,” says Dr. Olga Sumińska-Ebersoldt, co-coordinator of RISEnergy and researcher at the Helmholtz Institute Ulm (HIU) that was established by KIT and Ulm University. “We want to push the development of promising technologies from the laboratory level to industrial maturity.” Joint research infrastructure projects have already been launched for certain technologies, but RISEnergy is the first project of this dimension in Europe that covers all areas of renewable energy technologies: Photovoltaics, Concentrated Solar Power, Hydrogen, Biofuels, Wind Energy, OceanEnergy, as well as Integrated Grids, Energy Storage, Materials Research, Information and Communication Technologies.

 

Consortium of Institutions from 22 Countries 

The RISEnergy consortium consists of 69 technology institutes, universities, and industry partners from 22 countries. The partners contribute with their infrastructures, know-how, or provide organizational support. 

 

The core of the network is the European Energy Research Alliance EERA. EERA provides world-leading expertise via 18 Joint Programmes. “To integrate all major stakeholders, we asked EERA Joint Programmes to propose the best research infrastructures and experts for RISEnergy,” says Dr. Myriam E. Gil Bardají, researcher at HIU, coordinator of the EERA Joint Programme on Energy Storage, and co-coordinator of RISEnergy. Participation of organizations from the USA, Canada, and Japan ensures access to innovation outside of Europe. 

 

Researchers Can Apply

Within the framework of RISEnergy, 84 research infrastructures from 19 European countries, the USA, Canada, and Japan will open their facilities to external researchers and company developers, who can apply for access. An expert committee will decide. If approved, RISEnergy will cover the costs of the research facility as well as travel and accommodation expenses. Most of the project budget will be used for this purpose. 

 

The offer is specifically aimed at small and medium-sized companies. Uncomplicated access to major research infrastructures is expected to boost their innovations. “We offer cost-free use of laboratories. Researchers and experts from companies can travel, exchange ideas, and conduct experiments,” Sumińska-Ebersoldt says.

 

Networking, Exchange, and Communication

“When we think of using renewable energy sources, we always refer to combinations of technologies,” says Dr. Peter Holtappels, head of a working group at KIT’s Institute for Micro Process Engineering and scientific project coordinator of RISEnergy. He therefore emphasizes the importance of experts from different disciplines understanding each other. “Those designing energy storage systems or studying photovoltaics, wind and tidal energy usually are members of separate communities. We want to bring these people together and to encourage exchange and interdisciplinary collaboration.” There are plans to organize workshops and advisory services on overarching topics, such as lifecycle assessment and projects to standardise terminology and data processing. “Another focus will lie on digital tools for the energy transition: Artificial intelligence will help optimize the properties of materials and instruments and replace critical materials in supply chains,” says Dr. Holger Ihssen from the Helmholtz Association's Brussels office that helped establish the new research consortium. 

The project team will assess funding measures and identify reasonable ones. It will also develop roadmaps for policy makers. 

 

About RISEnergy (Research Infrastructure Services for Renewable Energy) 

RISEnergy is part of the Horizon Europe Funding Programme for Research and Innovation and of the module “Materials for Energy” of the global Mission Innovation initiative. The core of the project consortium is the European Energy Research Alliance EERA, the biggest research alliance for low-carbon energy technologies in Europe and major stakeholder in the EU’s strategic energy technologies plan (SET). Within the framework of Transnational Access (TNA) programmes, researchers and companies can apply for access to research infrastructures. The project coordinated by KIT is scheduled to start on March 1, 2024 and to expire on August 31, 2028. The project will be kicked off in Brussels on March 12 and 13, 2024. 

 

More Information:
European Energy Research Alliance

KIT Institute for Micro Process Engineering

 

Studies on coffee consumption − New biomarker proposed


N-methylpyridinium could be used as a new, practical food biomarker


Peer-Reviewed Publication

LEIBNIZ-INSTITUT FÜR LEBENSMITTEL-SYSTEMBIOLOGIE AN DER TU MÜNCHEN

Roasted coffee beans 

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ROASTED COFFEE BEANS IN A PILE ON WHITE BACKGROUND.

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CREDIT: GISELA OLIAS / LSB




In order to record coffee consumption in nutrition and health studies, researchers usually rely on self-reporting by participants. However, this is not always reliable. It would therefore be desirable to conduct additional studies to objectively verify individual consumption using biomarkers. A research team led by the Leibniz Institute for Food Systems Biology at the Technical University of Munich has now validated the suitability of a specific roasted coffee compound and proposes it as a new, practical food biomarker.

Millions of people around the world drink coffee every day. The beverage contains a large number of bioactive substances, and its health effects on the human metabolism are therefore frequently subjects of scientific studies. In many of these studies, however, the data on coffee consumption is largely based on self-reporting by the participants and is therefore not always accurate. This can affect the scientific validity of nutritional studies.

Biomarkers could provide a remedy

Reliable biomarkers could remedy this problem by using biological samples to objectively distinguish between coffee drinkers and non-coffee drinkers. "So far, however, only a few substances are known that could be used as coffee markers," says principal investigator Roman Lang from the Leibniz Institute. “However, these are not yet sufficiently validated or available in sufficient quantities to serve as reference substances for comparative measurements in nutritional studies,” he continues.

The research team, which also includes the nutritional physician Thomas Skurk and first author Beate Brandl from the ZIEL - Institute for Food & Health at the Technical University of Munich, has therefore comprehensively validated the roast coffee compound N-methylpyridinium as one such biomarker candidate for its suitability. Researchers at the Technical University of Munich first proposed the substance as a biomarker candidate in 2011 as part of a pilot study.

Data from over 460 people analyzed

As part of the scientific validation, the team analyzed existing literature data. It also analyzed urine, blood and plasma samples from more than 460 people from Freising and Nuremberg who had participated in a nutrition study conducted by the BMBF-funded enable cluster.

As the study shows, N-methylpyridinium is a compound that is specific to roasted Arabica and Robusta coffee. The substance is chemically very stable and its absorption into the organism is concentration-dependent. The substance can also be easily and reproducibly detected in various body fluids after coffee consumption, before leaving the body unchanged in the urine within a few hours to days.

Roman Lang, who heads the Biosystems Chemistry & Human Metabolism research group at the Leibniz Institute, explains: "As we have shown, N-methylpyridinium fulfills all the criteria that science demands of a biomarker to control food intake. Even if we cannot draw direct conclusions about the amount of coffee consumed due to various factors, the roasting substance is still suitable as a marker. This is because it allows us to distinguish objectively and practically between people who have drunk coffee and those who have not. We therefore propose it as a reliable qualitative biomarker for coffee consumption."

Publication: Brandl, B., Czech, C., Wudy, S.I., Beusch, A., Hauner, H., Skurk, T., and Lang, R. (2024). Validation of N-Methylpyridinium as a Feasible Biomarker for Roasted Coffee Intake. Beverages 10, 12. 10.3390/beverages10010012. www.mdpi.com/2306-5710/10/1/12

 

Roasted coffee beans that make the word coffee on white background

CREDIT

Gisela Olias / LSB


More Information:

About N-methylpyridinium:

N-methylpyridinium was already proposed as a biomarker candidate for coffee consumption in 2011: Lang et al., 2011 onlinelibrary.wiley.com/doi/10.1002/mnfr.201000656

N-methylpyridinium is formed from the natural alkaloid trigonelline, which is abundant in green coffee, when exposed to high heat at over 220 °C. Depending on the degree of roasting, roasted Arabica and Robusta coffee beans contain concentrations of around 0.5 to 2 mg/g of the substance - regardless of special processing methods such as steaming or decaffeinating. N-methylpyridinium is contained in brewed coffee (20-40 mg/l) and can be easily detected in blood, plasma and urine samples.


Coffee consumption in Europe and the USA:

In the USA alone, 74 percent of the population over the age of 20 describe themselves as coffee drinkers. In European countries, the calculated per capita consumption of roasted coffee in 2022 ranged from around 4 kilograms in Italy to 10 kilograms in Luxembourg.


Validation criteria:

The validation was based on criteria already proposed in 2018 for food biomarkers: plausibility, dose-response, time-response, robustness, reliability, stability, analytical performance and reproducibility. Dragsted, L.O. et al. 2018. www.ncbi.nlm.nih.gov/pmc/articles/PMC5975465/pdf/12263_2018_Article_603.pdf


Read also: New biomarkers for coffee consumption

www.leibniz-lsb.de/presse-oeffentlichkeit/pressemitteilungen/pm-20221207-pressemitteilung-biomarker-kaffeekonsum/


Information on the enable cluster: www.enable-cluster.de
 

Information about the Institute:

The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz-LSB@TUM) comprises a new, unique research profile at the interface of Food Chemistry & Biology, Chemosensors & Technology, and Bioinformatics & Machine Learning. As this profile has grown far beyond the previous core discipline of classical food chemistry, the institute spearheads the development of a food systems biology. Its aim is to develop new approaches for the sustainable production of sufficient quantities of food whose biologically active effector molecule profiles are geared to health and nutritional needs, but also to the sensory preferences of consumers. To do so, the institute explores the complex networks of sensorically relevant effector molecules along the entire food production chain with a focus on making their effects systemically understandable and predictable in the long term.

The Leibniz-LSB@TUM is a member of the Leibniz Association, which connects 97 independent research institutions. Their orientation ranges from the natural sciences, engineering and environmental sciences through economics, spatial and social sciences to the humanities. Leibniz Institutes devote themselves to social, economic and ecological issues. They conduct knowledge-oriented and application-oriented research, also in the overlapping Leibniz research networks, are or maintain scientific infrastructures and offer research-based services. The Leibniz Association focuses on knowledge transfer, especially with the Leibniz Research Museums. It advises and informs politics, science, business and the public. Leibniz institutions maintain close cooperation with universities - among others, in the form of the Leibniz Science Campuses, industry and other partners in Germany and abroad. They are subject to a transparent and independent review process. Due to their national significance, the federal government and the federal states jointly fund the institutes of the Leibniz Association. The Leibniz Institutes employ around 21,000 people, including almost 12,000 scientists. The entire budget of all the institutes is more than two billion euros.

+++ Stay up to date via our X (Twitter) channel twitter.com/LeibnizLSB +++

 

Labor market researcher Simon Jäger wins the In_equality Research Award


The Cluster of Excellence "The Politics of Inequality" at the University of Konstanz presents In_equality Research Award 2024 to economist Simon Jäger in recognition of his exceptional research achievements and their social relevance



Grant and Award Announcement

UNIVERSITY OF KONSTANZ





The In_equality Research Award honours exceptional research achievements with a large social impact and significant contributions to improving social systems. The Cluster of Excellence "The Politics of Inequality" at the University of Konstanz presents the 2024 award to renowned economist Simon Jäger who studies the origins and consequences of inequality in the labour market as well as the influence of institutions on social and economic participation. His work combines experimental methods with the analysis of large data sets. In his research, Simon Jäger was able to show how psychological factors can cause poverty traps in the labour market.

Marius R. Busemeyer, speaker of the Cluster of Excellence and a member of the award committee, explains: "Our aim is to promote courageous research on inequality that simultaneously initiates social change processes. Our award winner, Simon Jäger, is committed to precisely this goal in his research and understanding of knowledge transfer".

Simon Jäger is a professor at the Massachusetts Institute of Technology (MIT), where he also holds the Silverman (1968) Career Development Chair. In addition, he is a research fellow at the National Bureau of Economic Research (NBER) and other leading research institutions. Since February 2024, he has been advising the Federal Ministry for Economic Affairs and Climate Action (BMWK) led by Robert Habeck. "I am very honoured to receive the In_equality Research Award", Jäger says. "It is especially important for me to translate my research findings into impulses for the public discourse". Danyal Bayaz, Minister of Finance in Baden-Württemberg, will give the welcoming address for the award ceremony. The In_equality Research Award is worth 20,000 euros and can be used to fund future research projects, particularly in collaboration with the Cluster of Excellence "The Politics of Inequality".

The In_equality Conference
The award ceremony will take place at the opening ceremony for the In_equality Conference 2024 on 10 April 2024. Around 300 (inter)national researchers will attend the conference, which the Cluster of Excellence is hosting for the second time at the Bodenseeforum Konstanz. The programme includes 27 interdisciplinary panels focusing on topics like gender, ethnicity, wealth and education inequality, language, and questions involving the welfare state and climate change. In addition to the panels, there will be roundtables on knowledge transfer, open science and the Global South as well as impulses from collaboration partners, the foundation "Bertelsmann Stiftung", the German Institute for Economic Research (DIW) and the Hans-Böckler-Foundation’s Institute of Economic and Social Research (WSI).

 

Key facts

  • Labour market researcher Simon Jäger (MIT) wins the 2024 In_equality Research Award. The award is presented by the Cluster of Excellence "The Politics of Inequality" at the University of Konstanz.
  • Simon Jäger receives the prize for his extraordinary contribution to inequality research as well as his commitment to knowledge transfer. The prize, worth 20,000 euros, can be used to fund future research projects.
  • The award ceremony will take place at the opening ceremony for the In_equality Conference 2024 at the Bodenseeforum in Konstanz.
  • The Cluster of Excellence "The Politics of Inequality" at the University of Konstanz researches the political causes and consequences of inequality from an interdisciplinary perspective. The research is dedicated to some of the most pressing issues of our time: access to and distribution of (economic) resources, the global rise of populists, climate change and unfairly distributed educational opportunities.

 

 

Note to the editors:

Media representatives are welcome to attend the award ceremony on 10 April 2024 at 18:15 in Bodenseeforum Konstanz (Reichenaustraße 21, 78467 Konstanz, Germany). The following people are available for interviews:

  • Simon Jäger, professor of economics at MIT and winner of the In_equality Research Award 2024
  • Marius R. Busemeyer, professor of political science at the University of Konstanz and speaker of the Cluster of Excellence "The Politics of Inequality"

 

A picture can be downloaded here:

https://www.uni-konstanz.de/fileadmin/pi/fileserver/2024_EXTRA/arbeitsmarktforscher.jpg
Caption: Simon Jäger, winner of the In_equality Research Award 2024.

Picture: David Degner

 

Pollution: Impact of agricultural activities on PM2.5 in Lombardy is comparable to that of urbanization, industry and transportation


A research study from Politecnico di Milano published in Chemosphere


Peer-Reviewed Publication

POLITECNICO DI MILANO





Milan, 4th March 2024 – A research study from  Politecnico di Milano on the journal  Chemosphere has quantified the impact of agricultural activities on the spatial distribution of fine dust (PM 2.5) in Lombardy, showing that it is comparable to the impact of other well known sources of pollution, such as  urbanization, industry, and transportation.

Such comparable impact was found not only in the rural areas, but also when considering more densely populated areas.

In particular, the agriculture's contribution resulted correlated more to pollution spikes rather than to a baseline increase, but with a limited duration over time. Among the analyzed crops, while rice fields showed a minimal impact, corn and cereals fields showed a significant contribution to pollution.

 

These results has been obtained using an innovative framework and a data-driven model that includes the evaluation of the impact of the different land use on the spatial distribution of  PM2.5 concentration, particularly suited for the analysis of agricultural land, with a higher precision compared to pre-existing models.

To this aim, both Earth observation data by satellites and atmospheric models of the Copernicus program were utilized to derive the PM2.5 concentration, while information on the land use were obtained from the open access database and the agricultural information system of the Lombardy Region. For the analysis, an innovative GEOAI (Geomatics and Earth Observation Artificial Intelligence) system composed by a three-steps architecture, that allows to measure and interpret spatial dynamics on a local scale and to compare effects of different land use on pollution, was utilized. Thanks to this new approach, it will be possible to generate new evidence on the pollutant concentration due to specific agricultural activities, such as fertilization and manure spills.

This research originated by the D-DUST (Data-driven moDelling of particUlate with Satellite Technology aid) project, funded by Cariplo Foundation, with the aim to evaluate the potential - in terms of operability, cost-efficacy ratio, and accuracy – of a systematic integration of non-conventional data into the traditional PM2.5 monitoring approaches based on ground stations, with a focus on satellite data and agriculture-related pollutants emission.

The project was conducted by professor Maria Brovelli and Dr Daniele Oxoli, from the Department of Civil and Environmental Engineering, in collaboration with professor Enrico Caiani and Dr. Lorenzo Gianquintieri, from the Department of Electronics, Information and Biomedical Engineering at Politecnico di Milano, with Dr. Santoni from Fondazione Politecnico di Milano and with professor Andrea Spinazzè from Università degli Studi dell'Insubria.  

 

The published paper: https://www.sciencedirect.com/science/article/pii/S004565352400331X

 

Conservation value of field research stations grossly misunderstood and underfunded according to 173 conservation scientists in new study


Peer-Reviewed Publication

SAN DIEGO ZOO WILDLIFE ALLIANCE





SAN DIEGO – Funding of field conservation research stations worldwide has been drastically reduced since the beginning of the COVID-19 pandemic, raising the alarm of more than 170 conservation researchers representing 157 field stations in 56 countries in a new paper published in Conservation Letters. The authors contend that field research stations have a high return on investment and are essential and highly effective tools for biodiversity conservation.

Trillions of U.S. dollars were mobilized in economic recovery following the pandemic, yet the authors raise concerns that resources to address biodiversity loss and the climate crises are constrained at a time when they are most urgently needed. The pandemic caused roughly half of the surveyed field stations to close partially, and about one-quarter have remained partially or completely closed, with most field stations seeing a reduction in funding altogether.

Dr. Timothy Eppley, lead author of the paper, Chief Conservation Officer of Wildlife Madagascar, and a former Post Doctoral Research Fellow with San Diego Zoo Wildlife Alliance, said “A fundamental challenge is that governments and other funding agencies aren’t factoring in the true conservation return on investment and don’t realize the critical economic role of ecosystem services being protected by those field stations.”

Eppley and co-authors suggest the work of field research stations is often interdisciplinary, and some of the direct and indirect benefits of the research, education, and public engagement that takes place at field stations have long-term objectives that the current models for cost-benefit analyses do not capture.

“Field stations often function autonomously, with few studies exploring the aggregate impact of their work. Cumulatively, they make a substantial contribution to conservation,” said Eppley.

Dr. Russ Mittermeier, Chief Conservation Officer of Re:wild and senior author on the paper, shared a similar sentiment, saying “Field research stations are a cost-effective and multifaceted tool to addressing global conservation challenges and not just places where esoteric research is conducted, as is often the perception.  Almost invariably, one finds higher densities of wildlife in the vicinity of these field stations than in other parts of a particular region, even within protected areas.”

The study consisted of a survey, which focused on field stations in mostly tropical and subtropical countries, to understand the impact of the pandemic on funding and evaluate the conservation benefits of the field stations. Findings include improved habitat quality of the surrounding areas by reducing nearby deforestation, reducing rates of hunting, and improving enforcement of laws regarding wildlife use and resource extraction. Additionally, 93% hire locals, supporting the local economy, in addition to generating significant scientific output that informs conservation policies.

The authors advocate for greater recognition and investment in field research stations. “The benefits of supporting these stations extend beyond preserving biodiversity to advancing scientific research, education, and local community development,” said Mittermeier.

“Our research underscores the critical need for enhanced support for field research stations to ensure their ability to continue their indispensable work. Failing to include field stations in international policy frameworks that address the global biodiversity crisis represents a profound missed opportunity,” said Eppley.

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About San Diego Zoo Wildlife Alliance 

San Diego Zoo Wildlife Alliance, a nonprofit conservation leader, inspires passion for nature and collaboration for a healthier world. The Alliance supports innovative conservation science through global partnerships. Through wildlife care, science expertise and collaboration, more than 44 endangered species have been reintroduced to native habitats. Annually, the Alliance reaches over 1 billion people, in person at the San Diego Zoo and San Diego Zoo Safari Park, and virtually in 150 countries through media channels, including San Diego Zoo Wildlife Explorers television programming in children’s hospitals in 14 countries. Wildlife Allies—members, donors and guests—make success possible.