“Robinia pseudoacacia” espeziearen banaketa potentziala Euskal Autonomia Erkidegoan

Abstract

[EUS] Hainbat espezie dira Euskal Autonomia Erkidegoan (EAE) aloktonoak eta aldi berean inbaditzaileak kontsideratzen direnak. Horietako bat Robinia pseudoacacia zuhaitza da. Sasiakazia deitzen zaion espezie hau Robinia generokoa eta Fabaceae familiakoa da. Jatorriz AEBetakoa den arren, hainbat herrialdetan barneratu da, eta hainbat ikerketa lanek erakutsi dute espezie honek zenbait haltzadi eta harizti ordezkatu dituela EAEn. Lan honen helburua sasiakaziaren banaketa potentziala modelizatzea izan da, bere agerpenean eragin gehien duten faktoreak erabiliz. Horretarako, Global Biodiversity Information Facility GBIF erakundeak bildutako sasiakaziaren agerpen puntuetatik abiatuz, Maxent softwarea erabili da zenbait aldagai espazialetan oinarrituta (konkretuki altitudea, hezetasuna eta tenperatura, Geografi Informazioko Sistema-GIS baten laguntzaz prestatu direnak) sasiakaziaren banaketa potentziala lortzeko. Analisi honetan Ikusi da espeziea modelizatzeko aldagai garrantzizkoenak altitudea eta hezetasuna direla, batetik. Bestetik, espeziea izateko probabilitate gehien paduretako landaretzak duela, eta haltzadi eta hariztiek ere probabilitate handia erakutsi dutela, aurrez egindako ikerketek esandakoa bermatuz. Ikerketa honen emaitzek espezie honen kontrako neurriak ezartzeko informazio baliagarria eta espazialki esplizitua ematen du, 1 km-ko bereizmenean.

[EN] There are several species in the Autonomous Community of the Basque Country (CAPV) that are considered allochthonous and invasive. Robinia pseudoacacia is one of them. This species belongs to the Robinia genus in the Fabaceae family and it is also known as false acacia. Native to the United States, it has been introduced in several countries and sometimes replaced alder and oak groves in the CAPV as several studies have shown. The aim of this work was to model the potential distribution of the false acacia, using factors that most influence its appearance. The Maxent software has been used to obtain the potential distribution of the false acacia from various spatial variables (in particular terrain elevation, humidity and temperature, which were prepared using a Geographic Information System-GIS) and departing from appearance points of the false acacia compiled by the Global Biodiversity Information Facility GBIF organization. In this analysis it has been observed that the most important variables for modelling the distribution of the species are the terrain elevation and the humidity. Additionally, it was found the marshland vegetation is most likely to adopt this species, as well as alder and oak groves, confirming what previous research studies have shown. The results of this study provide useful and explicit spatial information to a resolution of 1 km, to effectively implement measures against the spread of this species.