Evidence map›Paper›PMID 35284679›Full record

ArticleHeliyon2022

Livestock water and land productivity in Kenya and their implications for future resource use.

Caroline K Bosire, Nadhem Mtimet, Dolapo Enahoro, Joseph O Ogutu, Maarten S Krol, Jan de Leeuw, Nicholas Ndiwa, Arjen Y Hoekstra

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.9field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 3 countries.

Caroline K BosireInternational Livestock Research Institute (ILRI), P.O. Box 30709, 00100 Nairobi, Kenya.
Nadhem MtimetInternational Fund for Agricultural Development (IFAD), 1191 Nile Corniche, Boulaq, Cairo, Egypt.
Dolapo EnahoroInternational Livestock Research Institute (ILRI), P.O. Box 30709, 00100 Nairobi, Kenya.
Joseph O OgutuUniversity of Hohenheim, Institute for Crop Science, Biostatistics Unit, 70599 Stuttgart, Germany.
Maarten S KrolTwente Water Centre, University of Twente, P.O. Box 217, 7522AE Enschede, the Netherlands.
Jan de LeeuwDownforce Technologies, Enschede, Overijssel, Netherlands.
Nicholas NdiwaInternational Livestock Research Institute (ILRI), P.O. Box 30709, 00100 Nairobi, Kenya.
Arjen Y HoekstraTwente Water Centre, University of Twente, P.O. Box 217, 7522AE Enschede, the Netherlands.
International Livestock Research Institute · KEUniversity of Twente · NLUniversity of Hohenheim · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population growth and rising affluence increase the demand for agricultural commodities. Associated growth in production increases dependency on natural resources in countries that attempt to meet part or all of the new demand locally. This study assesses the impact of changing meat and milk production on natural resource use in Kenya under three plausible scenarios of socio-economic development, namely Business-As-Usual (BAU), Sustainable Development (SDP) and Kenya Vision 2030 (V2030) scenarios. The IMPACT model is used to estimate projected cattle, sheep, goats and camel production parameters for meat and milk. The BAU and SDP represent standard scenarios for Kenya of a global economic model, IMPACT, while V2030 incorporates in the model features specific to Kenya's medium-term national development plan. We use calculations of water footprint and land footprint as resource use indicators to quantify the anticipated appropriation of water and land resources for meat and milk production and trade by 2040. Though camel dairy production numbers increase the most by quadrupling between 2005 and 2040, it is cattle dairy production that significantly determined gains in production between the scenarios. Productivity gains under the SDP scenario does not match the investments made thereby leading to only slightly better values for water and land productivity than those achieved under the BAU scenario. Relative to the BAU scenario, improvement in land productivity under the V2030 scenario is the most dramatic for shoat milk production in the arid and semi-arid systems but the least marked for cattle milk production in the humid system. By quantifying water and land productivity across heterogenous production systems, our findings can aid decision-makers in Kenya and other developing countries to understand the implications of strategies aimed at increasing domestic agricultural and livestock production on water and land resources both locally and through trade with other countries.

Indexed as

KenyaLand productivityLivestockProductionResource use efficiencyScenariosWater productivity

Identifiers

PMID35284679
PMCPMC8904406
OpenAlexW4214549013

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.