Contribution of Non-Wood Forest Product to The Local Community Living Near Mangrove Forest in Kudat, Sabah Article Swipe
Andy Russel Mojiol
,
Julius Kodoh
,
Razak Wahab
,
Medy Majuki
,
Wahyudi Wahyudi
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.47253/jtrss.v4i1.578
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.47253/jtrss.v4i1.578
This study was conducted to identify the types of non-wood forest products from the mangrove forests that are used by people of the mangrove fringe, reviewing the contribution of non-wood forest product sales of mangrove forest on the edge of the mangrove population income sources and investigate the local use of mangrove’s non-wood forest products of socio-economic development of the mangrove fringe population. The method which was used is by distributing the questionnaires and carried out formal interviews with the respondents. The locations which were studied are Kampung Limau Limauan, Kampung Bukit Kelapa, Kampung Longgom Kecil and Kampung Indrasun Laut. The questionnaires comprises of three parts which the first, second and third parts are containing the information regarding on the demographic of the respondent, the inventory of the mangrove’s non-wood forest products which sells by the respondent and the contribution of the mangrove’s non-wood forest product to the development respondent’s socioeconomy respectively. The respondents as a whole are more than 53 people and only 13 people only involved in the recruitment of mangroves. Of the total, found only three respondents whoactually depend on the mangrove’s non-wood forest products, while 10 others were only made to take the job as a sideline of mangrove forests. The types of mangrove’s non-wood forest products stated are mangrove crab (Scylla sarrata), shell (Cerithidea obtuse), cat fish (Plotosus sp.), mullet fish (Valamugil seheli) and marine shell (Polymesuda expansa). However, only four out of six products are marketed which are marine shell, shell, and mangrove crab and cat fish while the other is for domestic purposes. Based on data collected on correlation of the relationship between the average incomes of non-wood forest product sales of mangrove forests with a total average monthly income of respondents, it shows a positive relationship with r=0.527. The value of contribution of the average income from the selling of mangrove’s non-wood forest product over the total average of monthly income is 28.7 %. The Local usage value of mangrove’s product is calculated based on the formula of Local usage value = ?Pi Qi – Ci. The value of the local use non-wood forest products from the mangrove forests which are marketed by RM 1924.40 per month while the total value of products marketed locally applied to each individual is at RM 148.03 a month. As a conclusion,mangrove forests do contribute to the development of residence’s socio-economy although the value is low.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.47253/jtrss.v4i1.578
- OA Status
- diamond
- Cited By
- 6
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2769719663Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.47253/jtrss.v4i1.578Digital Object Identifier
- Title
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Contribution of Non-Wood Forest Product to The Local Community Living Near Mangrove Forest in Kudat, SabahWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-08-08Full publication date if available
- Authors
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Andy Russel Mojiol, Julius Kodoh, Razak Wahab, Medy Majuki, Wahyudi WahyudiList of authors in order
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https://doi.org/10.47253/jtrss.v4i1.578Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.47253/jtrss.v4i1.578Direct OA link when available
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Mangrove, Forest product, Respondent, Geography, Population, Forestry, Agroforestry, Ecology, Environmental science, Forest management, Biology, Demography, Law, Political science, SociologyTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2023: 1, 2022: 2, 2021: 1, 2020: 1, 2019: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.as | 154, 198 |
| abstract_inverted_index.at | 378 |
| abstract_inverted_index.by | 19, 69, 134, 360 |
| abstract_inverted_index.do | 387 |
| abstract_inverted_index.in | 168 |
| abstract_inverted_index.is | 68, 256, 319, 329, 377, 398 |
| abstract_inverted_index.it | 289 |
| abstract_inverted_index.of | 8, 21, 28, 33, 39, 50, 55, 58, 103, 121, 126, 140, 171, 201, 206, 237, 266, 273, 278, 287, 298, 300, 307, 316, 326, 335, 346, 369, 392 |
| abstract_inverted_index.on | 36, 118, 182, 261, 264, 332 |
| abstract_inverted_index.to | 4, 146, 194, 374, 389 |
| abstract_inverted_index.?Pi | 340 |
| abstract_inverted_index.Ci. | 343 |
| abstract_inverted_index.The | 63, 81, 100, 152, 204, 296, 322, 344 |
| abstract_inverted_index.and | 45, 73, 96, 110, 137, 162, 228, 247, 250 |
| abstract_inverted_index.are | 17, 86, 113, 157, 212, 240, 243, 358 |
| abstract_inverted_index.cat | 220, 251 |
| abstract_inverted_index.for | 257 |
| abstract_inverted_index.job | 197 |
| abstract_inverted_index.out | 75, 236 |
| abstract_inverted_index.per | 363 |
| abstract_inverted_index.six | 238 |
| abstract_inverted_index.the | 6, 13, 22, 26, 37, 40, 47, 59, 71, 79, 107, 115, 119, 122, 124, 127, 135, 138, 141, 147, 169, 174, 183, 196, 254, 267, 270, 301, 305, 313, 333, 347, 354, 366, 390, 396 |
| abstract_inverted_index.use | 49, 349 |
| abstract_inverted_index.was | 2, 66 |
| abstract_inverted_index.– | 342 |
| abstract_inverted_index.28.7 | 320 |
| abstract_inverted_index.This | 0 |
| abstract_inverted_index.crab | 214, 249 |
| abstract_inverted_index.data | 262 |
| abstract_inverted_index.each | 375 |
| abstract_inverted_index.edge | 38 |
| abstract_inverted_index.fish | 221, 225, 252 |
| abstract_inverted_index.four | 235 |
| abstract_inverted_index.from | 12, 304, 353 |
| abstract_inverted_index.low. | 399 |
| abstract_inverted_index.made | 193 |
| abstract_inverted_index.more | 158 |
| abstract_inverted_index.only | 163, 166, 177, 192, 234 |
| abstract_inverted_index.over | 312 |
| abstract_inverted_index.take | 195 |
| abstract_inverted_index.than | 159 |
| abstract_inverted_index.that | 16 |
| abstract_inverted_index.used | 18, 67 |
| abstract_inverted_index.were | 84, 191 |
| abstract_inverted_index.with | 78, 281, 294 |
| abstract_inverted_index.Based | 260 |
| abstract_inverted_index.Bukit | 91 |
| abstract_inverted_index.Kecil | 95 |
| abstract_inverted_index.Laut. | 99 |
| abstract_inverted_index.Limau | 88 |
| abstract_inverted_index.Local | 323, 336 |
| abstract_inverted_index.based | 331 |
| abstract_inverted_index.found | 176 |
| abstract_inverted_index.local | 48, 348 |
| abstract_inverted_index.month | 364 |
| abstract_inverted_index.other | 255 |
| abstract_inverted_index.parts | 105, 112 |
| abstract_inverted_index.sales | 32, 277 |
| abstract_inverted_index.sells | 133 |
| abstract_inverted_index.shell | 217, 230 |
| abstract_inverted_index.shows | 290 |
| abstract_inverted_index.sp.), | 223 |
| abstract_inverted_index.study | 1 |
| abstract_inverted_index.third | 111 |
| abstract_inverted_index.three | 104, 178 |
| abstract_inverted_index.total | 283, 314, 367 |
| abstract_inverted_index.types | 7, 205 |
| abstract_inverted_index.usage | 324, 337 |
| abstract_inverted_index.value | 297, 325, 338, 345, 368, 397 |
| abstract_inverted_index.which | 65, 83, 106, 132, 242, 357 |
| abstract_inverted_index.while | 188, 253, 365 |
| abstract_inverted_index.whole | 156 |
| abstract_inverted_index.148.03 | 380 |
| abstract_inverted_index.depend | 181 |
| abstract_inverted_index.first, | 108 |
| abstract_inverted_index.forest | 10, 30, 35, 53, 130, 144, 186, 209, 275, 310, 351 |
| abstract_inverted_index.formal | 76 |
| abstract_inverted_index.fringe | 61 |
| abstract_inverted_index.income | 43, 286, 303, 318 |
| abstract_inverted_index.marine | 229, 244 |
| abstract_inverted_index.method | 64 |
| abstract_inverted_index.month. | 382 |
| abstract_inverted_index.mullet | 224 |
| abstract_inverted_index.others | 190 |
| abstract_inverted_index.people | 20, 161, 165 |
| abstract_inverted_index.second | 109 |
| abstract_inverted_index.shell, | 245, 246 |
| abstract_inverted_index.stated | 211 |
| abstract_inverted_index.total, | 175 |
| abstract_inverted_index.(Scylla | 215 |
| abstract_inverted_index.1924.40 | 362 |
| abstract_inverted_index.Kampung | 87, 90, 93, 97 |
| abstract_inverted_index.Kelapa, | 92 |
| abstract_inverted_index.Longgom | 94 |
| abstract_inverted_index.applied | 373 |
| abstract_inverted_index.average | 271, 284, 302, 315 |
| abstract_inverted_index.between | 269 |
| abstract_inverted_index.carried | 74 |
| abstract_inverted_index.forests | 15, 280, 356, 386 |
| abstract_inverted_index.formula | 334 |
| abstract_inverted_index.fringe, | 24 |
| abstract_inverted_index.incomes | 272 |
| abstract_inverted_index.locally | 372 |
| abstract_inverted_index.monthly | 285, 317 |
| abstract_inverted_index.product | 31, 145, 276, 311, 328 |
| abstract_inverted_index.seheli) | 227 |
| abstract_inverted_index.selling | 306 |
| abstract_inverted_index.sources | 44 |
| abstract_inverted_index.studied | 85 |
| abstract_inverted_index.However, | 233 |
| abstract_inverted_index.Indrasun | 98 |
| abstract_inverted_index.Limauan, | 89 |
| abstract_inverted_index.although | 395 |
| abstract_inverted_index.domestic | 258 |
| abstract_inverted_index.forests. | 203 |
| abstract_inverted_index.identify | 5 |
| abstract_inverted_index.involved | 167 |
| abstract_inverted_index.mangrove | 14, 23, 34, 41, 60, 202, 213, 248, 279, 355 |
| abstract_inverted_index.marketed | 241, 359, 371 |
| abstract_inverted_index.non-wood | 9, 29, 52, 129, 143, 185, 208, 274, 309, 350 |
| abstract_inverted_index.obtuse), | 219 |
| abstract_inverted_index.positive | 292 |
| abstract_inverted_index.products | 11, 54, 131, 210, 239, 352, 370 |
| abstract_inverted_index.r=0.527. | 295 |
| abstract_inverted_index.sideline | 200 |
| abstract_inverted_index.(Plotosus | 222 |
| abstract_inverted_index.collected | 263 |
| abstract_inverted_index.comprises | 102 |
| abstract_inverted_index.conducted | 3 |
| abstract_inverted_index.expansa). | 232 |
| abstract_inverted_index.inventory | 125 |
| abstract_inverted_index.locations | 82 |
| abstract_inverted_index.products, | 187 |
| abstract_inverted_index.purposes. | 259 |
| abstract_inverted_index.regarding | 117 |
| abstract_inverted_index.reviewing | 25 |
| abstract_inverted_index.sarrata), | 216 |
| abstract_inverted_index.(Valamugil | 226 |
| abstract_inverted_index.calculated | 330 |
| abstract_inverted_index.containing | 114 |
| abstract_inverted_index.contribute | 388 |
| abstract_inverted_index.individual | 376 |
| abstract_inverted_index.interviews | 77 |
| abstract_inverted_index.mangroves. | 172 |
| abstract_inverted_index.population | 42 |
| abstract_inverted_index.respondent | 136 |
| abstract_inverted_index.(Cerithidea | 218 |
| abstract_inverted_index.(Polymesuda | 231 |
| abstract_inverted_index.correlation | 265 |
| abstract_inverted_index.demographic | 120 |
| abstract_inverted_index.development | 57, 148, 391 |
| abstract_inverted_index.information | 116 |
| abstract_inverted_index.investigate | 46 |
| abstract_inverted_index.population. | 62 |
| abstract_inverted_index.recruitment | 170 |
| abstract_inverted_index.respondent, | 123 |
| abstract_inverted_index.respondents | 153, 179 |
| abstract_inverted_index.whoactually | 180 |
| abstract_inverted_index.contribution | 27, 139, 299 |
| abstract_inverted_index.distributing | 70 |
| abstract_inverted_index.mangrove’s | 51, 128, 142, 184, 207, 308, 327 |
| abstract_inverted_index.relationship | 268, 293 |
| abstract_inverted_index.respondents, | 288 |
| abstract_inverted_index.respondents. | 80 |
| abstract_inverted_index.socioeconomy | 150 |
| abstract_inverted_index.residence’s | 393 |
| abstract_inverted_index.respectively. | 151 |
| abstract_inverted_index.socio-economy | 394 |
| abstract_inverted_index.questionnaires | 72, 101 |
| abstract_inverted_index.respondent’s | 149 |
| abstract_inverted_index.socio-economic | 56 |
| abstract_inverted_index.conclusion,mangrove | 385 |
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| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 5 |
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| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |