Understanding　processes　and　mechanisms　driving　patterns　of　species　distribution　and　diversity　is　a　vital　theme　in　community　ecology　and　conservation　biology.　There　has　been　a　continuous　increase　in　studies　focusing　on　diversity　patterns　in　freshwater　ecosystems　during　the　last　few　decades.　However,　comparative　studies　of　species　distributions,　diversity　patterns　and　underlying　processes　across　trophic　levels　remain　limited.　The　unique　characteristics　of　the　study　area　(i.e.　Hun-Tai　River　in　Northeast　China)　generates　a　wide　range　of　environmental　conditions　to　advance　our　understanding　of　what　drives　community　assembly　and　diversity　pattern　of　three　stream　organism　groups.　We　applied　variance　partitioning　(VPA)　to　correlate　community　compositions　with　environmental　and　spatial　factors　to　infer　stochastic　and　deterministic　assembly　processes,　respectively.　Linear　regression　(LR)　models　were　used　to　identify　the　main　drivers　of　species　richness　and　local　contributions　to　beta　diversity　(LCBD)　as　a　function　of　different　factors,　including　local　environmental　(e.g.,　in　situ　parameters,　hydrology,　nutrients),　geo-climatic　variables　(e.g.,　land　use,　topography,　climate)　and　spatial　factors.　Results　indicated　that　species　compositions　of　stream　biota　showed　significant　correlations　with　local　environmental,　geo-climatic　and　spatial　factors.　VPA　demonstrated　that　both　paradigms　(i.e.　deterministic　and　stochastic　processes)　interact　to　influence　the　biota　distributions　with　stochastic　process　contributing　more　than　deterministic　process.　In　addition,　the　strongest　stochastic　process　was　found　in　fishes　(10%),　followed　by　benthic　algae　and　macroinvertebrates　with　the　same　effects　(8%).　Notably,　geo-climatic　factors　explained　a　substantial　fraction　of　species　composition,　richness　and　beta　diversity,　although　their　effects　were　partially　manifested　via　local　and　spatial　variables.　We　demonstrate　the　relative　importance　of　both　stochastic　and　deterministic　processes　in　shaping　community　composition　and　biodiversity　of　three　stream　organism　groups　in　a　large　basin.　This　emphasizes　the　need　to　move　beyond　observed　patterns　and　consider　metacommunity　theory　into　river　management　and　conservation　practices.　©　2020　Elsevier　Ltd