Skip to content
cccskills
FreePublished on GitHub

agronomy-for-sustainable-development

Use when targeting Agronomy for Sustainable Development or deciding whether an agronomy / farming-systems manuscript fits this venue. Encodes the journal's fit, the explicit-and-evidenced sustainability-contribution bar, evidence and data-reporting expectations, house style, official-submission re-check, and desk-reject heuristics.

The English summary is being prepared. Showing the original description.

Run score Not tested

See how to install

Files included (1)

  • SKILL.md7.2 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Agronomy for Sustainable Development (agronomy-for-sustainable-development)

Journal positioning

Agronomy for Sustainable Development (ASD), published by Springer, is an agronomy journal defined by an explicit sustainability framing: cropping and farming systems studied because, and insofar as, they advance the sustainability of agriculture — environmental, economic, and social. It publishes field research alongside reviews and meta-analyses, but in every case the sustainability contribution must be explicit and evidenced, not asserted in the abstract and dropped thereafter. A competent agronomy study whose only contribution is a yield or management result, with sustainability mentioned as decoration, is a poor fit. This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current author guidelines. Before submitting, re-check the live ASD author guidance.

When to trigger

  • The author names ASD and wants a fit/framing check for a sustainability-oriented agronomy or farming-systems paper.
  • An agronomy result must be re-framed so its sustainability contribution is explicit, measured, and load-bearing rather than rhetorical.
  • The author is planning a review or meta-analysis of sustainable cropping/farming systems and needs the venue's synthesis bar.
  • The author is choosing between ASD, field-crops-research, and agriculture-ecosystems-and-environment.

Scope & topic fit

  • Cropping and farming systems designed or evaluated for sustainability: diversification, conservation agriculture, agroecology, organic and integrated systems.
  • Resource-use efficiency and input reduction (nutrients, water, pesticides, energy) tied to sustainability outcomes and trade-offs.
  • Soil health, biodiversity, and ecosystem-service outcomes of agronomic management framed for sustainability.
  • Climate-change adaptation and mitigation in agronomic systems, including carbon and GHG considerations.
  • Reviews and meta-analyses that synthesize evidence on sustainable practices across studies and regions.
  • Socio-economic and multi-criteria assessments of farming systems where they evidence the sustainability contribution.

Method & evidence bar

  • The sustainability contribution must be explicit and evidenced: the relevant environmental, economic, and/or social dimension is measured or analyzed, with trade-offs acknowledged, not asserted.
  • Field studies need adequate replication and design and, where claims generalize, multi-site/ multi-season or systems-level evidence; pseudoreplication is disqualifying.
  • Reviews and meta-analyses need a reproducible, transparent protocol: search strategy, inclusion criteria, effect-size handling, heterogeneity, and bias assessment.
  • Statistics must match the design (mixed models for multi-environment data; appropriate meta-analytic models) with uncertainty reported.
  • Data and, for syntheses, the extracted dataset/code should be available per Springer policy; agronomic and environmental metadata must be documented.

Structure & house style

  • Standard structured article (research or review/meta-analysis); ASD favours a clearly stated novel sustainability contribution highlighted up front; re-check current article types and highlight/graphical-abstract conventions on the live guide.
  • The introduction must state the sustainability problem and the specific, evidenced contribution — what dimension is improved and how it is measured.
  • Figures/tables should carry the sustainability argument (trade-off plots, effect-size forests for syntheses, multi-criteria comparisons) with variability shown.
  • A data-availability statement and complete methodological/agronomic metadata are expected; for syntheses, the full protocol and dataset belong in supplementary material.

Official-submission checklist

  • Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the official source anchors, then cite the current Agronomy for Sustainable Development page you checked.
  • Search the live site for "Agronomy for Sustainable Development submission guidelines" and follow the current Springer version.
  • Re-check article types (research vs. review/meta-analysis), structure, highlights/graphical abstract, and word/figure expectations.
  • Confirm the data-availability/repository policy and, for syntheses, protocol-reporting expectations.
  • Re-check competing-interests, funding, author-contribution, and AI-use disclosure, and open-access terms.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • The sustainability contribution is explicit, measured, and load-bearing — not decoration.
  • The relevant environmental/economic/social dimension is evidenced, with trade-offs acknowledged.
  • Field claims have adequate replication/design and systems- or multi-environment-level support.
  • Reviews/meta-analyses follow a transparent, reproducible protocol with bias assessment.
  • Statistics match the design (mixed/meta-analytic models) with uncertainty reported.
  • Data-availability statement, metadata, and (for syntheses) the extracted dataset are prepared.

Common desk-reject triggers

  • A competent agronomy result with sustainability asserted but never measured.
  • A single site-year or pseudoreplicated trial generalized to a sustainability claim.
  • A "review" or meta-analysis with no transparent protocol, inclusion criteria, or bias assessment.
  • Trade-offs ignored — a one-dimensional gain presented as overall sustainability.
  • Scope mismatch: a pure yield/management or pure soil-mechanism paper with no sustainability framing.

Re-routing decision

  • Yield/agronomy and resource-use efficiency without a sustainability contribution → field-crops-research.
  • Agroecosystem environmental outcomes (GHG, nutrient losses, biodiversity) at field-landscape scale → agriculture-ecosystems-and-environment.
  • Soil-process mechanism (SOM, microbial function, nutrient cycling) is the core → soil-biology-and-biochemistry.
  • Broad food-systems significance → nature-food.
  • Large-scale climate/global-change ecosystem process dominant → global-change-biology.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] Agronomy for Sustainable Development
[Article type] Research / Review / Meta-analysis
[Topic tags] <2–3 closest sustainable-agronomy topics>
[Sustainability contribution] <the measured dimension improved and the evidence + trade-offs>
[Method/evidence] <does design or synthesis protocol clear ASD's bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / highlights / data + protocol policy / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

The English summary is being prepared. Showing the original description.

brycewang-stanford/Awesome-Journal-Skills1.3KUpdated Sep 27, 2026

Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.

The English summary is being prepared. Showing the original description.

brycewang-stanford/Awesome-Journal-Skills1.3KUpdated Sep 27, 2026

Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.

The English summary is being prepared. Showing the original description.

brycewang-stanford/Awesome-Journal-Skills1.3KUpdated Sep 27, 2026

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

The English summary is being prepared. Showing the original description.

brycewang-stanford/Awesome-Journal-Skills1.3KUpdated Sep 27, 2026

Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to non-specialist reviewers.

The English summary is being prepared. Showing the original description.

brycewang-stanford/Awesome-Journal-Skills1.3KUpdated Sep 27, 2026

Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across AAAI's broad AI scope.

The English summary is being prepared. Showing the original description.

brycewang-stanford/Awesome-Journal-Skills1.3KUpdated Sep 27, 2026

See all skills by brycewang-stanford

Report a problem with this skill