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Evaluating Timber And Agriculture Assets

ASecurity

Assesses timberland and agricultural investments with biological growth rates, harvest economics, and land value appreciation. Use when evaluating timber investments, analyzing farmland, or assessing biological asset returns.

22 stars
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Added 9/20/2026
businessgoapiperformance

Works with

cliapi

Security Analysis

A100/100

Scanned 9/20/2026

Install to Claude Code

$npx -y skills add lev-os/agents --skill evaluating-timber-and-agriculture-assets --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: evaluating-timber-and-agriculture-assets
description: Assesses timberland and agricultural investments with biological growth rates, harvest economics, and land value appreciation. Use when evaluating timber investments, analyzing farmland, or assessing biological asset returns.
tags:
  - analysis
  - real-assets-and-natural-resources
  - investment
metadata:
  author: casemark
  practice_areas:
    - Natural Resources
    - Energy Capital
    - Commodity Investment
  document_types:
    - Evaluation Report
  skill_modes:
    - Analysis
    - Assessment
---
# Evaluating Timber And Agriculture Assets

## When To Use

- Underwriting a timberland acquisition or disposition for a TIMO, REIT, or institutional portfolio
- Evaluating row-crop, permanent-crop, or ranch land as a direct investment or within a fund vehicle
- Benchmarking biological asset returns against competing real-asset classes (infrastructure, minerals, farmland indices)
- Conducting annual revaluation of timber or agriculture holdings under IAS 41 / ASC 905 fair-value requirements
- Assessing carbon-credit or ecosystem-services revenue overlays on existing timber or ag properties

## Inputs To Gather

- **Property profile**: acreage, location, soil classification (NRCS Web Soil Survey or equivalent), topography, water rights status
- **Timber inventory**: species mix, age-class distribution, standing merchantable volume (MBF or m³), mean annual increment (MAI), and periodic annual increment (PAI)
- **Agricultural profile**: crop type, rotation schedule, historical yield per acre, input costs (seed, fertilizer, chemicals, irrigation), lease rate comps
- **Market data**: delivered log prices by grade/species from regional mill surveys, USDA crop price forecasts, NCREIF Farmland and Timberland Index benchmarks
- **Financial terms**: acquisition price or appraised value, financing structure, target hold period, discount rate / hurdle rate, tax treatment (capital gains, depletion, 1031 eligibility) [VERIFY: jurisdiction-specific tax treatment]
- **Regulatory factors**: harvest permits, reforestation obligations, ESA-listed species constraints, conservation easement overlays, water-use permits [VERIFY: state/provincial forestry and ag regulations]

## Workflow

1. **Classify the asset type and investment structure**
   - Distinguish timberland (biological growth + land appreciation) from agriculture (annual cash yield + land appreciation)
   - Identify ownership vehicle: direct fee simple, TIMO-managed separate account, LP/LLC fund, REIT, or JV
   - Note whether carbon or ecosystem-services income layers apply

2. **Build the biological growth model (timber)**
   - Map current inventory by species and age class against regional yield tables
   - Project merchantable volume forward using MAI/PAI curves; adjust for mortality, thinning schedules, and rotation length
   - Assign log-grade distribution (sawlog vs. pulpwood vs. chip-n-saw) at each projected harvest entry
   - Sensitivity-test growth assumptions: ±10% MAI, alternate rotation ages, bark-beetle or fire-loss scenarios

3. **Build the production model (agriculture)**
   - Project crop yields using 5–10 year county-level USDA NASS data; adjust for soil quality and irrigation access
   - Model input-cost escalation (fertilizer, fuel, labor) against commodity price forecasts
   - For permanent crops (orchards, vineyards), model non-bearing development years, peak production plateau, and declining-yield tail
   - Include government program payments (ARC/PLC) and crop-insurance assumptions where material [VERIFY: current farm-bill program eligibility]

4. **Determine land value and appreciation trajectory**
   - Establish current per-acre value from comparable sales, county assessor data, and broker opinion of value
   - Apply regional land-appreciation rate informed by NCREIF indices and local transaction evidence
   - Separate bare-land value from standing-timber or crop-infrastructure value for depreciation and depletion scheduling

5. **Construct the DCF and return analysis**
   - Build annual cash-flow projections: harvest/crop revenue minus silvicultural or farming costs, management fees, property taxes, insurance
   - Apply appropriate discount rate — typically 5–8% real for institutional timberland, 6–10% for farmland depending on crop risk [VERIFY: current market discount-rate benchmarks]
   - Calculate IRR, equity multiple, and NPV; segment returns into biological growth, land appreciation, and cash yield components
   - Run scenario analysis: base case, downside (commodity price crash, drought/fire), upside (carbon premiums, HBU conversion)

6. **Assess risk factors**
   - **Biological risk**: fire, pest/disease, drought, windthrow — quantify insured vs. uninsured exposure
   - **Market risk**: commodity price cyclicality, regional mill capacity changes, export-market dependence
   - **Regulatory risk**: endangered-species harvest restrictions, water-rights curtailment, zoning/HBU limitations
   - **Liquidity risk**: typical hold periods (10–15 yr timber, 7–12 yr agriculture), secondary-market depth
   - **Climate risk**: shifting growing zones, precipitation pattern changes, wildfire frequency trends

7. **Benchmark and synthesize**
   - Compare projected returns to NCREIF Timberland / Farmland indices and peer-fund performance
   - Evaluate portfolio-level benefits: inflation hedge, low equity-market correlation, Sharpe-ratio contribution
   - Summarize go / no-go recommendation with key sensitivities clearly flagged

## Output

- **Executive summary**: asset description, recommended action, headline IRR/multiple, and top-three risk factors
- **Biological growth / production model**: tabular projection of volume or yield by year with assumptions stated
- **DCF model summary**: annual cash flows, discount rate rationale, NPV, IRR, and equity multiple
- **Return attribution**: percentage of total return from biological growth (or crop yield), land appreciation, and income
- **Scenario matrix**: base / downside / upside return outcomes with probability-weighted expected return
- **Risk register**: ranked risk factors with mitigation measures and residual exposure
- **Comparable benchmarks**: NCREIF index comparison, peer transactions, and implied pricing metrics (price per MBF, price per productive acre)

## Quality Checks

- Verify that growth-rate assumptions align with published regional yield tables or USDA NASS data — do not use national averages as proxies for site-specific properties
- Confirm discount rate is consistent with asset-class conventions and the fund's stated return targets
- Ensure land-value appreciation rates are supported by transaction evidence, not assumed from long-run index averages alone
- Check that all tax and depletion assumptions reflect the correct jurisdiction and entity type [VERIFY]
- Validate that scenario analysis covers at least one severe but plausible downside (e.g., 30% commodity price decline, major fire/drought event)
- Confirm that any carbon-credit or ecosystem-services revenue is supported by a credible registry, protocol, and buyer pipeline — not speculative pricing
- Cross-check acreage, volume, and yield figures against source documents to prevent unit-conversion errors (MBF vs. m³, short tons vs. metric tons, bushels vs. cwt)

Attribution

lev-oslev-os
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